Merge pull request #166 from tiqi-group/fix/logging_settings

fix: removes basic configuration of logging system in task module

.github/workflows/publish-to-pypi.yaml

@@ -70,9 +70,9 @@ jobs:
         name: python-package-distributions
         path: dist/
     - name: Sign the dists with Sigstore
-      uses: sigstore/gh-action-sigstore-python@v1.2.3
+      uses: sigstore/gh-action-sigstore-python@v3.0.0
       with:
-        inputs: >-
+        inputs: |
           ./dist/*.tar.gz
           ./dist/*.whl
     - name: Upload artifact signatures to GitHub Release
@@ -85,27 +85,3 @@ jobs:
         gh release upload
         '${{ github.ref_name }}' dist/**
         --repo '${{ github.repository }}'
-
-  # publish-to-testpypi:
-  #   name: Publish Python 🐍 distribution 📦 to TestPyPI
-  #   needs:
-  #   - build
-  #   runs-on: ubuntu-latest
-  #
-  #   environment:
-  #     name: testpypi
-  #     url: https://test.pypi.org/p/pydase
-  #
-  #   permissions:
-  #     id-token: write  # IMPORTANT: mandatory for trusted publishing
-  #
-  #   steps:
-  #   - name: Download all the dists
-  #     uses: actions/download-artifact@v3
-  #     with:
-  #       name: python-package-distributions
-  #       path: dist/
-  #   - name: Publish distribution 📦 to TestPyPI
-  #     uses: pypa/gh-action-pypi-publish@release/v1
-  #     with:
-  #       repository-url: https://test.pypi.org/legacy/

.github/workflows/python-package.yml

@@ -20,9 +20,6 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
-    - uses: chartboost/ruff-action@v1
-      with:
-        src: "./src"
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v4
       with:
@@ -32,6 +29,12 @@ jobs:
         python -m pip install --upgrade pip
         python -m pip install poetry
         poetry install --with dev
+    - name: Check with ruff
+      run: |
+        poetry run ruff check src
+    - name: Check formatting with ruff
+      run: |
+        poetry run ruff format --check src
     - name: Test with pytest
       run: |
         poetry run pytest

.vscode/launch.json

@@ -25,7 +25,7 @@
             "type": "firefox",
             "request": "launch",
             "name": "react: firefox",
-            "url": "http://localhost:3000",
+            "url": "http://localhost:5173",
             "webRoot": "${workspaceFolder}/frontend"
         }
     ]

LICENSE

@@ -1,6 +1,4 @@
-MIT License
-
-Copyright (c) 2023 Mose Müller <mosemueller@gmail.com>
+Copyright (c) 2023-2024 Mose Müller <mosemueller@gmail.com>
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,64 +1,34 @@
-# pydase (Python Data Service) <!-- omit from toc -->
+<!--introduction-start-->
+# pydase <!-- omit from toc -->
 
-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-[![Documentation Status](https://readthedocs.org/projects/pydase/badge/?version=latest)](https://pydase.readthedocs.io/en/latest/?badge=latest)
+[![Version](https://img.shields.io/pypi/v/pydase?style=flat)](https://pypi.org/project/pydase/)
+[![Python Versions](https://img.shields.io/pypi/pyversions/pydase)](https://pypi.org/project/pydase/)
+[![Documentation Status](https://readthedocs.org/projects/pydase/badge/?version=stable)](https://pydase.readthedocs.io/en/stable/)
+[![License: MIT](https://img.shields.io/github/license/tiqi-group/pydase)][License]
 
-`pydase` is a Python library for creating data service servers with integrated web and RPC servers. It's designed to handle the management of data structures, automated tasks, and callbacks, and provides built-in functionality for serving data over different protocols.
+`pydase` is a Python library that simplifies the creation of remote control interfaces for Python objects. It exposes the public attributes of a user-defined class via a [Socket.IO](https://python-socketio.readthedocs.io/en/stable/) web server, ensuring they are always in sync with the service state. You can interact with these attributes using an RPC client, a RESTful API, or a web browser. The web browser frontend is auto-generated, displaying components that correspond to each public attribute of the class for direct interaction.
+`pydase` implements an [observer pattern][Observer Pattern] to provide the real-time updates, ensuring that changes to the class attributes are reflected across all clients.
 
-- [Features](#features)
-- [Installation](#installation)
-- [Usage](#usage)
-  - [Defining a DataService](#defining-a-dataservice)
-  - [Running the Server](#running-the-server)
-  - [Accessing the Web Interface](#accessing-the-web-interface)
-  - [Connecting to the Service via Python Client](#connecting-to-the-service-via-python-client)
-    - [Tab Completion Support](#tab-completion-support)
-    - [Integration within Another Service](#integration-within-another-service)
-- [Understanding the Component System](#understanding-the-component-system)
-  - [Built-in Type and Enum Components](#built-in-type-and-enum-components)
-  - [Method Components](#method-components)
-  - [DataService Instances (Nested Classes)](#dataservice-instances-nested-classes)
-  - [Custom Components (`pydase.components`)](#custom-components-pydasecomponents)
-    - [`DeviceConnection`](#deviceconnection)
-      - [Customizing Connection Logic](#customizing-connection-logic)
-      - [Reconnection Interval](#reconnection-interval)
-    - [`Image`](#image)
-    - [`NumberSlider`](#numberslider)
-    - [`ColouredEnum`](#colouredenum)
-    - [Extending with New Components](#extending-with-new-components)
-- [Understanding Service Persistence](#understanding-service-persistence)
-  - [Controlling Property State Loading with `@load_state`](#controlling-property-state-loading-with-load_state)
-- [Understanding Tasks in pydase](#understanding-tasks-in-pydase)
-- [Understanding Units in pydase](#understanding-units-in-pydase)
-- [Using `validate_set` to Validate Property Setters](#using-validate_set-to-validate-property-setters)
-- [Configuring pydase via Environment Variables](#configuring-pydase-via-environment-variables)
-- [Customizing the Web Interface](#customizing-the-web-interface)
-  - [Enhancing the Web Interface Style with Custom CSS](#enhancing-the-web-interface-style-with-custom-css)
-  - [Tailoring Frontend Component Layout](#tailoring-frontend-component-layout)
-  - [Specifying a Custom Frontend Source](#specifying-a-custom-frontend-source)
-- [Logging in pydase](#logging-in-pydase)
-  - [Changing the Log Level](#changing-the-log-level)
-- [Documentation](#documentation)
-- [Contributing](#contributing)
-- [License](#license)
+Whether you're managing lab sensors, network devices, or any abstract data entity, `pydase` facilitates service development and deployment.
 
 ## Features
 
 <!-- no toc -->
-- [Simple data service definition through class-based interface](#defining-a-dataService)
-- [Integrated web interface for interactive access and control of your data service](#accessing-the-web-interface)
-- [Support for programmatic control and interaction with your service](#connecting-to-the-service-via-python-client)
-- [Component system bridging Python backend with frontend visual representation](#understanding-the-component-system)
-- [Customizable styling for the web interface through user-defined CSS](#customizing-web-interface-style)
-- [Saving and restoring the service state for service persistence](#understanding-service-persistence)
-- [Automated task management with built-in start/stop controls and optional autostart](#understanding-tasks-in-pydase)
-- [Support for units](#understanding-units-in-pydase)
-- [Validating Property Setters](#using-validate_set-to-validate-property-setters)
-<!-- Support for additional servers for specific use-cases -->
+- [Simple service definition through class-based interface][Defining DataService]
+- [Auto-generated web interface for interactive access and control of your service][Web Interface Access]
+- [Python RPC client][Short RPC Client]
+- [Customizable web interface][Customizing Web Interface]
+- [Saving and restoring the service state][Service Persistence]
+- [Automated task management with built-in start/stop controls and optional autostart][Task Management]
+- [Support for units][Units]
+- [Validating Property Setters][Property Validation]
+
+<!--introduction-end-->
+
+<!--getting-started-start-->
 
 ## Installation
 
-<!--installation-start-->
 
 Install `pydase` using [`poetry`](https://python-poetry.org/):
 
@@ -72,26 +42,27 @@ or `pip`:
 pip install pydase
 ```
 
-<!--installation-end-->
 
 ## Usage
 
-<!--usage-start-->
 
-Using `pydase` involves three main steps: defining a `DataService` subclass, running the server, and then connecting to the service either programmatically using `pydase.Client` or through the web interface.
+Using `pydase` involves three main steps: defining a `pydase.DataService` subclass, running the server, and then connecting to the service either programmatically using `pydase.Client` or through the web interface.
 
 ### Defining a DataService
 
-To use pydase, you'll first need to create a class that inherits from `DataService`. This class represents your custom data service, which will be exposed via a web server. Your class can implement class / instance attributes and synchronous and asynchronous tasks.
+To use `pydase`, you'll first need to create a class that inherits from `pydase.DataService`.
+This class represents your custom service, which will be exposed via a web server.<br>
+Your class can implement synchronous and asynchronous methods, some [built-in types](https://docs.python.org/3/library/stdtypes.html) (like `int`, `float`, `str`, `bool`, `list` or `dict`) and [other components][Custom Components] as attributes.
+For more information, please refer to the [components guide][Components].
 
 Here's an example:
 
 ```python
-from pydase import DataService, Server
+import pydase
 from pydase.utils.decorators import frontend
 
 
-class Device(DataService):
+class Device(pydase.DataService):
     _current = 0.0
     _voltage = 0.0
     _power = False
@@ -134,26 +105,30 @@ class Device(DataService):
 
 if __name__ == "__main__":
     service = Device()
-    Server(service).run()
+    pydase.Server(service=service, web_port=8001).run()
 ```
 
-In the above example, we define a Device class that extends DataService. We define a few properties (current, voltage, power) and their getter and setter methods.
+In the above example, we define a `Device` class that inherits from `pydase.DataService`. 
+We define a few properties (current, voltage, power) and their getter and setter methods.
 
 ### Running the Server
 
-Once your DataService is defined, you can create an instance of it and run the server:
+Once your service class is defined, you can create an instance of it and run the server:
 
 ```python
-from pydase import Server
+import pydase
 
 # ... defining the Device class ...
 
 if __name__ == "__main__":
     service = Device()
-    Server(service).run()
+    pydase.Server(service=service, web_port=8001).run()
 ```
 
-This will start the server, making your Device service accessible via RPC and a web server at [http://localhost:8001](http://localhost:8001).
+This will start the server, making your `Device` service accessible on 
+[http://localhost:8001](http://localhost:8001). The port number for the web server can 
+be customised in the server constructor or through environment variables and defaults 
+to `8001`.
 
 ### Accessing the Web Interface
 
@@ -163,7 +138,7 @@ Once the server is running, you can access the web interface in a browser:
 
 In this interface, you can interact with the properties of your `Device` service.
 
-### Connecting to the Service via Python Client
+### Connecting to the Service via Python RPC Client
 
 You can connect to the service using the `pydase.Client`. Below is an example of how to establish a connection to a service and interact with it:
 
@@ -172,7 +147,8 @@ import pydase
 
 # Replace the hostname and port with the IP address and the port of the machine where 
 # the service is running, respectively
-client_proxy = pydase.Client(hostname="<ip_addr>", port=8001).proxy
+client_proxy = pydase.Client(url="ws://<ip_addr>:<web_port>").proxy
+# client_proxy = pydase.Client(url="wss://your-domain.ch").proxy  # if your service uses ssl-encryption
 
 # After the connection, interact with the service attributes as if they were local
 client_proxy.voltage = 5.0
@@ -184,662 +160,27 @@ The proxy acts as a local representative of the remote service, enabling straigh
 
 The proxy class dynamically synchronizes with the server's exposed attributes. This synchronization allows the proxy to be automatically updated with any attributes or methods that the server exposes, essentially mirroring the server's API. This dynamic updating enables users to interact with the remote service as if they were working with a local object.
 
-#### Tab Completion Support
+The RPC client also supports tab completion support in the interpreter, can be used as a context manager and integrates very well with other pydase services. For more information, please refer to the [documentation][Python RPC Client].
 
-In interactive environments such as Python interpreters and Jupyter notebooks, the proxy class supports tab completion, which allows users to explore available methods and attributes.
+### RESTful API
+The `pydase` RESTful API allows for standard HTTP-based interactions and provides access to various functionalities through specific routes. 
 
-#### Integration within Another Service
-
-You can also integrate a client proxy within another service. Here's how you can set it up:
+For example, you can get a value like this:
 
 ```python
-import pydase
+import json
 
-class MyService(pydase.DataService):
-    # Initialize the client without blocking the constructor
-    proxy = pydase.Client(hostname="<ip_addr>", port=8001, block_until_connected=False).proxy
+import requests
 
-if __name__ == "__main__":
-    service = MyService()
-    # Create a server that exposes this service; adjust the web_port as needed
-    server = pydase.Server(service, web_port=8002). run()
+response = requests.get(
+    "http://<hostname>:<web_port>/api/v1/get_value?access_path=<full_access_path>"
+)
+serialized_value = json.loads(response.text)
 ```
 
-In this setup, the `MyService` class has a `proxy` attribute that connects to a `pydase` service located at `<ip_addr>:8001`.
-The `block_until_connected=False` argument allows the service to start up even if the initial connection attempt fails.
-This configuration is particularly useful in distributed systems where services may start in any order.
+For more information, see [here][RESTful API].
 
-<!--usage-end-->
-
-## Understanding the Component System
-
-<!-- Component User Guide Start -->
-
-In `pydase`, components are fundamental building blocks that bridge the Python backend logic with frontend visual representation and interactions. This system can be understood based on the following categories:
-
-### Built-in Type and Enum Components
-
-`pydase` automatically maps standard Python data types to their corresponding frontend components:
-
-- `str`: Translated into a `StringComponent` on the frontend.
-- `int` and `float`: Manifested as the `NumberComponent`.
-- `bool`: Rendered as a `ButtonComponent`.
-- `list`: Each item displayed individually, named after the list attribute and its index.
-- `dict`: Each key-value pair displayed individually, named after the dictionary attribute and its key. **Note** that the dictionary keys must be strings.
-- `enum.Enum`: Presented as an `EnumComponent`, facilitating dropdown selection.
-
-### Method Components
-Within the `DataService` class of `pydase`, only methods devoid of arguments can be represented in the frontend, classified into two distinct categories
-
-1. [**Tasks**](#understanding-tasks-in-pydase): Argument-free asynchronous functions, identified within `pydase` as tasks, are inherently designed for frontend interaction. These tasks are automatically rendered with a start/stop button, allowing users to initiate or halt the task execution directly from the web interface. 
-2. **Synchronous Methods with `@frontend` Decorator**: Synchronous methods without arguments can also be presented in the frontend. For this, they have to be decorated with the `@frontend` decorator.
-
-```python
-import pydase
-import pydase.components
-import pydase.units as u
-from pydase.utils.decorators import frontend
-
-
-class MyService(pydase.DataService):
-    @frontend
-    def exposed_method(self) -> None:
-        ...
-
-    async def my_task(self) -> None:
-        while True:
-            # ...
-```
-
-![Method Components](docs/images/method_components.png)
-
-You can still define synchronous tasks with arguments and call them using a python client. However, decorating them with the `@frontend` decorator will raise a `FunctionDefinitionError`. Defining a task with arguments will raise a `TaskDefinitionError`.
-I decided against supporting function arguments for functions rendered in the frontend due to the following reasons:
-
-1. Feature Request Pitfall: supporting function arguments create a bottomless pit of feature requests. As users encounter the limitations of supported types, demands for extending support to more complex types would grow.
-2. Complexity in Supported Argument Types: while simple types like `int`, `float`, `bool` and `str` could be easily supported, more complicated types are not (representation, (de-)serialization).
-
-### DataService Instances (Nested Classes)
-
-Nested `DataService` instances offer an organized hierarchy for components, enabling richer applications. Each nested class might have its own attributes and methods, each mapped to a frontend component.
-
-Here is an example:
-
-```python
-from pydase import DataService, Server
-
-
-class Channel(DataService):
-    def __init__(self, channel_id: int) -> None:
-        super().__init__()
-        self._channel_id = channel_id
-        self._current = 0.0
-
-    @property
-    def current(self) -> float:
-        # run code to get current
-        result = self._current
-        return result
-
-    @current.setter
-    def current(self, value: float) -> None:
-        # run code to set current
-        self._current = value
-
-
-class Device(DataService):
-    def __init__(self) -> None:
-        super().__init__()
-        self.channels = [Channel(i) for i in range(2)]
-
-
-if __name__ == "__main__":
-    service = Device()
-    Server(service).run()
-```
-
-![Nested Classes App](docs/images/Nested_Class_App.png)
-
-**Note** that defining classes within `DataService` classes is not supported (see [this issue](https://github.com/tiqi-group/pydase/issues/16)).
-
-### Custom Components (`pydase.components`)
-
-The custom components in `pydase` have two main parts:
-
-- A **Python Component Class** in the backend, implementing the logic needed to set, update, and manage the component's state and data.
-- A **Frontend React Component** that renders and manages user interaction in the browser.
-
-Below are the components available in the `pydase.components` module, accompanied by their Python usage:
-
-#### `DeviceConnection`
-
-The `DeviceConnection` component acts as a base class within the `pydase` framework for managing device connections. It provides a structured approach to handle connections by offering a customizable `connect` method and a `connected` property. This setup facilitates the implementation of automatic reconnection logic, which periodically attempts reconnection whenever the connection is lost.
-
-In the frontend, this class abstracts away the direct interaction with the `connect` method and the `connected` property. Instead, it showcases user-defined attributes, methods, and properties. When the `connected` status is `False`, the frontend displays an overlay that prompts manual reconnection through the `connect()` method. Successful reconnection removes the overlay.
-
-```python
-import pydase.components
-import pydase.units as u
-
-
-class Device(pydase.components.DeviceConnection):
-    def __init__(self) -> None:
-        super().__init__()
-        self._voltage = 10 * u.units.V
-
-    def connect(self) -> None:
-        if not self._connected:
-            self._connected = True
-
-    @property
-    def voltage(self) -> float:
-        return self._voltage
-
-
-class MyService(pydase.DataService):
-    def __init__(self) -> None:
-        super().__init__()
-        self.device = Device()
-
-
-if __name__ == "__main__":
-    service_instance = MyService()
-    pydase.Server(service_instance).run()
-```
-
-![DeviceConnection Component](docs/images/DeviceConnection_component.png)
-
-##### Customizing Connection Logic
-
-Users are encouraged to primarily override the `connect` method to tailor the connection process to their specific device. This method should adjust the `self._connected` attribute based on the outcome of the connection attempt:
-
-```python
-import pydase.components
-
-
-class MyDeviceConnection(pydase.components.DeviceConnection):
-    def __init__(self) -> None:
-        super().__init__()
-        # Add any necessary initialization code here
-
-    def connect(self) -> None:
-        # Implement device-specific connection logic here
-        # Update self._connected to `True` if the connection is successful,
-        # or `False` if unsuccessful
-        ...
-```
-
-Moreover, if the connection status requires additional logic, users can override the `connected` property:
-
-```python
-import pydase.components
-
-class MyDeviceConnection(pydase.components.DeviceConnection):
-    def __init__(self) -> None:
-        super().__init__()
-        # Add any necessary initialization code here
-
-    def connect(self) -> None:
-        # Implement device-specific connection logic here
-        # Ensure self._connected reflects the connection status accurately
-        ...
-
-    @property
-    def connected(self) -> bool:
-        # Implement custom logic to accurately report connection status
-        return self._connected
-```
-
-##### Reconnection Interval
-
-The `DeviceConnection` component automatically executes a task that checks for device availability at a default interval of 10 seconds. This interval is adjustable by modifying the `_reconnection_wait_time` attribute on the class instance.
-
-#### `Image`
-
-This component provides a versatile interface for displaying images within the application. Users can update and manage images from various sources, including local paths, URLs, and even matplotlib figures.
-
-The component offers methods to load images seamlessly, ensuring that visual content is easily integrated and displayed within the data service.
-
-```python
-import matplotlib.pyplot as plt
-import numpy as np
-import pydase
-from pydase.components.image import Image
-
-
-class MyDataService(pydase.DataService):
-    my_image = Image()
-
-
-if __name__ == "__main__":
-    service = MyDataService()
-    # loading from local path
-    service.my_image.load_from_path("/your/image/path/")
-
-    # loading from a URL
-    service.my_image.load_from_url("https://cataas.com/cat")
-
-    # loading a matplotlib figure
-    fig = plt.figure()
-    x = np.linspace(0, 2 * np.pi)
-    plt.plot(x, np.sin(x))
-    plt.grid()
-    service.my_image.load_from_matplotlib_figure(fig)
-
-    pydase.Server(service).run()
-```
-
-![Image Component](docs/images/Image_component.png)
-
-#### `NumberSlider`
-
-The `NumberSlider` component in the `pydase` package provides an interactive slider interface for adjusting numerical values on the frontend. It is designed to support both numbers and quantities and ensures that values adjusted on the frontend are synchronized with the backend.
-
-To utilize the `NumberSlider`, users should implement a class that derives from `NumberSlider`. This class can then define the initial values, minimum and maximum limits, step sizes, and additional logic as needed.
-
-Here's an example of how to implement and use a custom slider:
-
-```python
-import pydase
-import pydase.components
-
-
-class MySlider(pydase.components.NumberSlider):
-    def __init__(
-        self,
-        value: float = 0.0,
-        min_: float = 0.0,
-        max_: float = 100.0,
-        step_size: float = 1.0,
-    ) -> None:
-        super().__init__(value, min_, max_, step_size)
-
-    @property
-    def min(self) -> float:
-        return self._min
-
-    @min.setter
-    def min(self, value: float) -> None:
-        self._min = value
-
-    @property
-    def max(self) -> float:
-        return self._max
-
-    @max.setter
-    def max(self, value: float) -> None:
-        self._max = value
-
-    @property
-    def step_size(self) -> float:
-        return self._step_size
-
-    @step_size.setter
-    def step_size(self, value: float) -> None:
-        self._step_size = value
-
-    @property
-    def value(self) -> float:
-        """Slider value."""
-        return self._value
-
-    @value.setter
-    def value(self, value: float) -> None:
-        if value < self._min or value > self._max:
-            raise ValueError("Value is either below allowed min or above max value.")
-
-        self._value = value
-
-
-class MyService(pydase.DataService):
-    def __init__(self) -> None:
-        super().__init__()
-        self.voltage = MySlider()
-
-
-if __name__ == "__main__":
-    service_instance = MyService()
-    service_instance.voltage.value = 5
-    print(service_instance.voltage.value)  # Output: 5
-    pydase.Server(service_instance).run()
-```
-
-In this example, `MySlider` overrides the `min`, `max`, `step_size`, and `value` properties. Users can make any of these properties read-only by omitting the corresponding setter method.
-
-![Slider Component](docs/images/Slider_component.png)
-
-- Accessing parent class resources in `NumberSlider`
-
-  In scenarios where you need the slider component to interact with or access resources from its parent class, you can achieve this by passing a callback function to it. This method avoids directly passing the entire parent class instance (`self`) and offers a more encapsulated approach. The callback function can be designed to utilize specific attributes or methods of the parent class, allowing the slider to perform actions or retrieve data in response to slider events.
-
-  Here's an illustrative example:
-
-  ```python
-  from collections.abc import Callable
-
-  import pydase
-  import pydase.components
-
-
-  class MySlider(pydase.components.NumberSlider):
-      def __init__(
-          self,
-          value: float,
-          on_change: Callable[[float], None],
-      ) -> None:
-          super().__init__(value=value)
-          self._on_change = on_change
-
-      # ... other properties ...
-
-      @property
-      def value(self) -> float:
-          return self._value
-
-      @value.setter
-      def value(self, new_value: float) -> None:
-          if new_value < self._min or new_value > self._max:
-              raise ValueError("Value is either below allowed min or above max value.")
-          self._value = new_value
-          self._on_change(new_value)
-
-
-  class MyService(pydase.DataService):
-      def __init__(self) -> None:
-          self.voltage = MySlider(
-              5,
-              on_change=self.handle_voltage_change,
-          )
-
-      def handle_voltage_change(self, new_voltage: float) -> None:
-          print(f"Voltage changed to: {new_voltage}")
-          # Additional logic here
-
-  if __name__ == "__main__":
-     service_instance = MyService()
-     my_service.voltage.value = 7  # Output: "Voltage changed to: 7"
-     pydase.Server(service_instance).run()
-  ```
-
-- Incorporating units in `NumberSlider`
-
-  The `NumberSlider` is capable of [displaying units](#understanding-units-in-pydase) alongside values, enhancing its usability in contexts where unit representation is crucial. When utilizing `pydase.units`, you can specify units for the slider's value, allowing the component to reflect these units in the frontend.
-
-  Here's how to implement a `NumberSlider` with unit display:
-
-  ```python
-  import pydase
-  import pydase.components
-  import pydase.units as u
-
-  class MySlider(pydase.components.NumberSlider):
-      def __init__(
-          self,
-          value: u.Quantity = 0.0 * u.units.V,
-      ) -> None:
-          super().__init__(value)
-
-      @property
-      def value(self) -> u.Quantity:
-          return self._value
-
-      @value.setter
-      def value(self, value: u.Quantity) -> None:
-          if value.m < self._min or value.m > self._max:
-              raise ValueError("Value is either below allowed min or above max value.")
-          self._value = value
-
-  class MyService(pydase.DataService):
-      def __init__(self) -> None:
-          super().__init__()
-          self.voltage = MySlider()
-
-  if __name__ == "__main__":
-      service_instance = MyService()
-      service_instance.voltage.value = 5 * u.units.V
-      print(service_instance.voltage.value)  # Output: 5 V
-      pydase.Server(service_instance).run()
-  ```
-
-#### `ColouredEnum`
-
-This component provides a way to visually represent different states or categories in a data service using colour-coded options. It behaves similarly to a standard `Enum`, but the values encode colours in a format understood by CSS. The colours can be defined using various methods like Hexadecimal, RGB, HSL, and more.
-
-If the property associated with the `ColouredEnum` has a setter function, the keys of the enum will be rendered as a dropdown menu, allowing users to interact and select different options. Without a setter function, the selected key will simply be displayed as a coloured box with text inside, serving as a visual indicator.
-
-```python
-import pydase
-import pydase.components as pyc
-
-
-class MyStatus(pyc.ColouredEnum):
-    PENDING = "#FFA500"  # Hexadecimal colour (Orange)
-    RUNNING = "#0000FF80"  # Hexadecimal colour with transparency (Blue)
-    PAUSED = "rgb(169, 169, 169)"  # RGB colour (Dark Gray)
-    RETRYING = "rgba(255, 255, 0, 0.3)"  # RGB colour with transparency (Yellow)
-    COMPLETED = "hsl(120, 100%, 50%)"  # HSL colour (Green)
-    FAILED = "hsla(0, 100%, 50%, 0.7)"  # HSL colour with transparency (Red)
-    CANCELLED = "SlateGray"  # Cross-browser colour name (Slate Gray)
-
-
-class StatusTest(pydase.DataService):
-    _status = MyStatus.RUNNING
-
-    @property
-    def status(self) -> MyStatus:
-        return self._status
-
-    @status.setter
-    def status(self, value: MyStatus) -> None:
-        # do something ...
-        self._status = value
-
-# Modifying or accessing the status value:
-my_service = StatusExample()
-my_service.status = MyStatus.FAILED
-```
-
-![ColouredEnum Component](docs/images/ColouredEnum_component.png)
-
-**Note** that each enumeration name and value must be unique.
-This means that you should use different colour formats when you want to use a colour multiple times.
-
-#### Extending with New Components
-
-Users can also extend the library by creating custom components. This involves defining the behavior on the Python backend and the visual representation on the frontend. For those looking to introduce new components, the [guide on adding components](https://pydase.readthedocs.io/en/latest/dev-guide/Adding_Components/) provides detailed steps on achieving this.
-
-<!-- Component User Guide End -->
-
-## Understanding Service Persistence
-
-`pydase` allows you to easily persist the state of your service by saving it to a file. This is especially useful when you want to maintain the service's state across different runs.
-
-To save the state of your service, pass a `filename` keyword argument to the constructor of the `pydase.Server` class. If the file specified by `filename` does not exist, the state manager will create this file and store its state in it when the service is shut down. If the file already exists, the state manager will load the state from this file, setting the values of its attributes to the values stored in the file.
-
-Here's an example:
-
-```python
-from pydase import DataService, Server
-
-class Device(DataService):
-    # ... defining the Device class ...
-
-
-if __name__ == "__main__":
-    service = Device()
-    Server(service, filename="device_state.json").run()
-```
-
-In this example, the state of the `Device` service will be saved to `device_state.json` when the service is shut down. If `device_state.json` exists when the server is started, the state manager will restore the state of the service from this file.
-
-### Controlling Property State Loading with `@load_state`
-
-By default, the state manager only restores values for public attributes of your service. If you have properties that you want to control the loading for, you can use the `@load_state` decorator on your property setters. This indicates to the state manager that the value of the property should be loaded from the state file.
-
-Here is how you can apply the `@load_state` decorator:
-
-```python
-from pydase import DataService
-from pydase.data_service.state_manager import load_state
-
-class Device(DataService):
-    _name = "Default Device Name"
-
-    @property
-    def name(self) -> str:
-        return self._name
-
-    @name.setter
-    @load_state
-    def name(self, value: str) -> None:
-        self._name = value
-```
-
-With the `@load_state` decorator applied to the `name` property setter, the state manager will load and apply the `name` property's value from the file storing the state upon server startup, assuming it exists.
-
-Note: If the service class structure has changed since the last time its state was saved, only the attributes and properties decorated with `@load_state` that have remained the same will be restored from the settings file.
-
-## Understanding Tasks in pydase
-
-In `pydase`, a task is defined as an asynchronous function without arguments contained in a class that inherits from `DataService`. These tasks usually contain a while loop and are designed to carry out periodic functions.
-
-For example, a task might be used to periodically read sensor data, update a database, or perform any other recurring job. One core feature of `pydase` is its ability to automatically generate start and stop functions for these tasks. This allows you to control task execution via both the frontend and python clients, giving you flexible and powerful control over your service's operation.
-
-Another powerful feature of `pydase` is its ability to automatically start tasks upon initialization of the service. By specifying the tasks and their arguments in the `_autostart_tasks` dictionary in your service class's `__init__` method, `pydase` will automatically start these tasks when the server is started. Here's an example:
-
-```python
-from pydase import DataService, Server
-
-class SensorService(DataService):
-    def __init__(self):
-        super().__init__()
-        self.readout_frequency = 1.0
-        self._autostart_tasks["read_sensor_data"] = ()
-
-    def _process_data(self, data: ...) -> None:
-        ...
-
-    def _read_from_sensor(self) -> Any:
-        ...
-
-    async def read_sensor_data(self):
-        while True:
-            data = self._read_from_sensor()
-            self._process_data(data)  # Process the data as needed
-            await asyncio.sleep(self.readout_frequency)
-
-
-if __name__ == "__main__":
-    service = SensorService()
-    Server(service).run()
-```
-
-In this example, `read_sensor_data` is a task that continuously reads data from a sensor. By adding it to the `_autostart_tasks` dictionary, it will automatically start running when `Server(service).run()` is executed.
-As with all tasks, `pydase` will generate `start_read_sensor_data` and `stop_read_sensor_data` methods, which can be called to manually start and stop the data reading task. The readout frequency can be updated using the `readout_frequency` attribute.
-
-## Understanding Units in pydase
-
-`pydase` integrates with the [`pint`](https://pint.readthedocs.io/en/stable/) package to allow you to work with physical quantities within your service. This enables you to define attributes with units, making your service more expressive and ensuring consistency in the handling of physical quantities.
-
-You can define quantities in your `DataService` subclass using `pydase`'s `units` functionality.
-
-Here's an example:
-
-```python
-from typing import Any
-
-import pydase.units as u
-from pydase import DataService, Server
-
-
-class ServiceClass(DataService):
-    voltage = 1.0 * u.units.V
-    _current: u.Quantity = 1.0 * u.units.mA
-
-    @property
-    def current(self) -> u.Quantity:
-        return self._current
-
-    @current.setter
-    def current(self, value: u.Quantity) -> None:
-        self._current = value
-
-
-if __name__ == "__main__":
-    service = ServiceClass()
-
-    service.voltage = 10.0 * u.units.V
-    service.current = 1.5 * u.units.mA
-
-    Server(service).run()
-```
-
-In the frontend, quantities are rendered as floats, with the unit displayed as additional text. This allows you to maintain a clear and consistent representation of physical quantities across both the backend and frontend of your service.
-![Web interface with rendered units](./docs/images/Units_App.png)
-
-Should you need to access the magnitude or the unit of a quantity, you can use the `.m` attribute or the `.u` attribute of the variable, respectively. For example, this could be necessary to set the periodicity of a task:
-
-```python
-import asyncio
-from pydase import DataService, Server
-import pydase.units as u
-
-
-class ServiceClass(DataService):
-    readout_wait_time = 1.0 * u.units.ms
-
-    async def read_sensor_data(self):
-        while True:
-            print("Reading out sensor ...")
-            await asyncio.sleep(self.readout_wait_time.to("s").m)
-
-
-if __name__ == "__main__":
-    service = ServiceClass()
-
-    Server(service).run()
-```
-
-For more information about what you can do with the units, please consult the documentation of [`pint`](https://pint.readthedocs.io/en/stable/).
-
-## Using `validate_set` to Validate Property Setters
-
-The `validate_set` decorator ensures that a property setter reads back the set value using the property getter and checks it against the desired value.
-This decorator can be used to validate that a parameter has been correctly set on a device within a specified precision and timeout.
-
-The decorator takes two keyword arguments: `timeout` and `precision`. The `timeout` argument specifies the maximum time (in seconds) to wait for the value to be within the precision boundary.
-If the value is not within the precision boundary after this time, an exception is raised.
-The `precision` argument defines the acceptable deviation from the desired value.
-If `precision` is `None`, the value must be exact.
-For example, if `precision` is set to `1e-5`, the value read from the device must be within ±0.00001 of the desired value.
-
-Here’s how to use the `validate_set` decorator in a `DataService` class:
-
-```python
-import pydase
-from pydase.observer_pattern.observable.decorators import validate_set
-
-
-class Service(pydase.DataService):
-    def __init__(self) -> None:
-        super().__init__()
-        self._device = RemoteDevice()  # dummy class
-
-    @property
-    def value(self) -> float:
-        # Implement how to get the value from the remote device...
-        return self._device.value
-
-    @value.setter
-    @validate_set(timeout=1.0, precision=1e-5)
-    def value(self, value: float) -> None:
-        # Implement how to set the value on the remote device...
-        self._device.value = value
-
-
-if __name__ == "__main__":
-    pydase.Server(Service()).run()
-```
+<!--getting-started-end-->
 
 ## Configuring pydase via Environment Variables
 
@@ -856,7 +197,6 @@ Configuring `pydase` through environment variables enhances flexibility, securit
     ```
 
 - **`SERVICE_WEB_PORT`**: Defines the port number for the web server. This has to be different for each services running on the same host. Default is 8001.
-- **`SERVICE_RPC_PORT`**: Defines the port number for the rpc server. This has to be different for each services running on the same host. Default is 18871.
 - **`GENERATE_WEB_SETTINGS`**: When set to true, generates / updates the `web_settings.json` file. If the file already exists, only new entries are appended.
 
 Some of those settings can also be altered directly in code when initializing the server: 
@@ -871,7 +211,6 @@ from your_service_module import YourService
 server = Server(
     YourService(),
     web_port=8080,
-    rpc_port=18880,
     config_dir=pathlib.Path("other_config_dir"),  # note that you need to provide an argument of type pathlib.Path
     generate_web_settings=True
 ).run()
@@ -879,62 +218,14 @@ server = Server(
 
 ## Customizing the Web Interface
 
-### Enhancing the Web Interface Style with Custom CSS
+`pydase` allows you to enhance the user experience by customizing the web interface's appearance through
 
-`pydase` allows you to enhance the user experience by customizing the web interface's appearance. You can apply your own styles globally across the web interface by passing a custom CSS file to the server during initialization.
+1. a custom CSS file, and
+2. tailoring the frontend component layout and display style.
 
-Here's how you can use this feature:
+You can also provide a custom frontend source if you need even more flexibility.
 
-1. Prepare your custom CSS file with the desired styles.
-
-2. When initializing your server, use the `css` parameter of the `Server` class to specify the path to your custom CSS file.
-
-```python
-from pydase import Server, DataService
-
-class MyService(DataService):
-    # ... your service definition ...
-
-if __name__ == "__main__":
-    service = MyService()
-    server = Server(service, css="path/to/your/custom.css").run()
-```
-
-This will apply the styles defined in `custom.css` to the web interface, allowing you to maintain branding consistency or improve visual accessibility.
-
-Please ensure that the CSS file path is accessible from the server's running location. Relative or absolute paths can be used depending on your setup.
-
-### Tailoring Frontend Component Layout
-
-`pydase` enables users to customize the frontend layout via the `web_settings.json` file. Each key in the file corresponds to the full access path of public attributes, properties, and methods of the exposed service, using dot-notation.
-
-- **Custom Display Names**: Modify the `"displayName"` value in the file to change how each component appears in the frontend.
-- **Control Component Visibility**: Utilize the `"display"` key-value pair to control whether a component is rendered in the frontend. Set the value to `true` to make the component visible or `false` to hide it.
-<!-- - **Adjustable Component Order**: The `"displayOrder"` values determine the order of components. Alter these values to rearrange the components as desired. -->
-
-The `web_settings.json` file will be stored in the directory specified by `SERVICE_CONFIG_DIR`. You can generate a `web_settings.json` file by setting the `GENERATE_WEB_SETTINGS` to `True`. For more information, see the [configuration section](#configuring-pydase-via-environment-variables).
-
-### Specifying a Custom Frontend Source
-
-To further personalize your web interface, you can provide `pydase` with a custom frontend GUI. To do so, you can use the `frontend_src` keyword in the `pydase.Server`:
-
-```python
-from pathlib import Path
-
-import pydase
-
-
-class MyService(pydase.DataService):
-    # Service definition
-
-
-if __name__ == "__main__":
-    service = MyService()
-    pydase.Server(
-        service,
-        frontend_src=Path("path/to/your/frontend/directory"),
-    ).run()
-```
+For details, please see [here](https://pydase.readthedocs.io/en/stable/user-guide/interaction/main/#customization-options).
 
 ## Logging in pydase
 
@@ -979,12 +270,27 @@ You have two primary ways to adjust the log levels in `pydase`:
 
 ## Documentation
 
-The full documentation provides more detailed information about `pydase`, including advanced usage examples, API references, and tips for troubleshooting common issues. See the [full documentation](https://pydase.readthedocs.io/en/latest/) for more information.
+The full documentation provides more detailed information about `pydase`, including advanced usage examples, API references, and tips for troubleshooting common issues. See the [full documentation](https://pydase.readthedocs.io/en/stable/) for more information.
 
 ## Contributing
 
-We welcome contributions! Please see [contributing.md](https://pydase.readthedocs.io/en/latest/about/contributing/) for details on how to contribute.
+We welcome contributions! Please see [contributing.md](https://pydase.readthedocs.io/en/stable/about/contributing/) for details on how to contribute.
 
 ## License
 
-`pydase` is licensed under the [MIT License](https://github.com/tiqi-group/pydase/blob/main/LICENSE).
+`pydase` is licensed under the [MIT License][License].
+
+[License]: ./LICENSE
+[Observer Pattern]: https://pydase.readthedocs.io/en/docs/dev-guide/Observer_Pattern_Implementation/
+[Service Persistence]: https://pydase.readthedocs.io/en/stable/user-guide/Service_Persistence
+[Defining DataService]: #defining-a-dataService
+[Web Interface Access]: #accessing-the-web-interface
+[Short RPC Client]: #connecting-to-the-service-via-python-rpc-client
+[Customizing Web Interface]: #customizing-the-web-interface
+[Task Management]: https://pydase.readthedocs.io/en/stable/user-guide/Tasks/
+[Units]: https://pydase.readthedocs.io/en/stable/user-guide/Understanding-Units/
+[Property Validation]: https://pydase.readthedocs.io/en/stable/user-guide/Validating-Property-Setters/
+[Custom Components]: https://pydase.readthedocs.io/en/stable/user-guide/Components/#custom-components-pydasecomponents
+[Components]: https://pydase.readthedocs.io/en/stable/user-guide/Components/
+[RESTful API]: https://pydase.readthedocs.io/en/stable/user-guide/interaction/main/#restful-api
+[Python RPC Client]: https://pydase.readthedocs.io/en/stable/user-guide/interaction/main/#python-rpc-client

docs/dev-guide/Adding_Components.md

@@ -111,7 +111,7 @@ Write the React component code, following the structure and patterns used in exi
 
 For example, for the `Image` component, a template could look like this:
 
-```tsx
+```ts
 import React, { useEffect, useRef, useState } from 'react';
 import { Card, Collapse, Image } from 'react-bootstrap';
 import { DocStringComponent } from './DocStringComponent';
@@ -203,8 +203,7 @@ There are two different events a component might want to trigger: updating an at
     
     For illustration, take the `ButtonComponent`. When the button state changes, we want to send this update to the backend:
 
-    ```tsx
-    // file: frontend/src/components/ButtonComponent.tsx
+    ```ts title="frontend/src/components/ButtonComponent.tsx"
     // ... (import statements)
     
     type ButtonComponentProps = {
@@ -249,7 +248,7 @@ There are two different events a component might want to trigger: updating an at
 
     To see how to use the `MethodComponent` in your component, have a look at the `DeviceConnection.tsx` file. Here is an example that demonstrates the usage of the `runMethod` function (also, have a look at the `MethodComponent.tsx` file):
 
-    ```tsx
+    ```ts title="frontend/src/components/_YourComponent_.tsx"
     import { runMethod } from '../socket';
     // ... (other imports)
 
@@ -287,9 +286,7 @@ The `GenericComponent` is responsible for rendering different types of component
 
 At the beginning of the `GenericComponent` file, import the newly created `ImageComponent`:
 
-```tsx
-// file: frontend/src/components/GenericComponent.tsx
-
+```ts title="frontend/src/components/GenericComponent.tsx"
 import { ImageComponent } from './ImageComponent';
 ```
 
@@ -299,7 +296,7 @@ Update the `AttributeType` type definition to include the new type for the `Imag
 
 For example, if the new attribute type is `'Image'` (which should correspond to the name of the backend component class), you can add it to the union:
 
-```tsx
+```ts
 type AttributeType =
   | 'str'
   | 'bool'
@@ -318,7 +315,7 @@ type AttributeType =
 
 Inside the `GenericComponent` function, add a new conditional branch to render the `ImageComponent` when the attribute type is `'Image'`:
 
-```tsx
+```ts
 } else if (attribute.type === 'Image') {
   return (
     <ImageComponent
@@ -348,7 +345,7 @@ For example, updating an `Image` component corresponds to setting a very long st
 
 To create a custom notification message, you can update the message passed to the `addNotification` method in the `useEffect` hook in the component file file. For the `ImageComponent`, this could look like this:
 
-```tsx
+```ts
 const fullAccessPath = [parentPath, name].filter((element) => element).join('.');
 
 useEffect(() => {

docs/dev-guide/Observer_Pattern_Implementation.md

@@ -2,7 +2,7 @@
 
 ## Overview
 
-The Observer Pattern is a fundamental design pattern in the `pydase` package, serving as the central communication mechanism for state updates to clients connected to a service.
+The [Observer Pattern](https://en.wikipedia.org/wiki/Observer_pattern) is a fundamental design pattern in the `pydase` package, serving as the central communication mechanism for state updates to clients connected to a service.
 
 ## How it Works
 

docs/dev-guide/api.md

@@ -0,0 +1,45 @@
+::: pydase.data_service
+    handler: python
+
+::: pydase.server.server
+    handler: python
+
+::: pydase.server.web_server
+    handler: python
+
+::: pydase.client
+    handler: python
+
+::: pydase.components
+    handler: python
+
+::: pydase.task
+    handler: python
+    options:
+      inherited_members: false
+      show_submodules: true
+
+::: pydase.utils.serialization.serializer
+    handler: python
+
+::: pydase.utils.serialization.deserializer
+    handler: python
+    options:
+      show_root_heading: true
+      show_root_toc_entry: false
+      show_symbol_type_heading: true
+      show_symbol_type_toc: true
+
+::: pydase.utils.serialization.types
+    handler: python
+
+::: pydase.utils.decorators
+    handler: python
+    options:
+      filters: ["!render_in_frontend"]
+
+::: pydase.units
+    handler: python
+
+::: pydase.config
+    handler: python

docs/getting-started.md

@@ -1,14 +1,11 @@
 # Getting Started
-## Installation
 {%
    include-markdown "../README.md"
-   start="<!--installation-start-->"
-   end="<!--installation-end-->"
+   start="<!--getting-started-start-->"
+   end="<!--getting-started-end-->"
 %}
 
-## Usage
-{%
-   include-markdown "../README.md"
-   start="<!--usage-start-->"
-   end="<!--usage-end-->"
-%}
+[RESTful API]: ./user-guide/interaction/README.md#restful-api
+[Python RPC Client]: ./user-guide/interaction/README.md#python-rpc-client
+[Custom Components]: ./user-guide/Components.md#custom-components-pydasecomponents
+[Components]: ./user-guide/Components.md

docs/index.md

@@ -1 +1,16 @@
-{% include-markdown "../README.md" %}
+{%
+   include-markdown "../README.md"
+   start="<!--introduction-start-->"
+   end="<!--introduction-end-->"
+%}
+
+[License]: ./about/license.md
+[Observer Pattern]: ./dev-guide/Observer_Pattern_Implementation.md
+[Service Persistence]: ./user-guide/Service_Persistence.md
+[Defining DataService]: ./getting-started.md#defining-a-dataservice
+[Web Interface Access]: ./getting-started.md#accessing-the-web-interface
+[Short RPC Client]: ./getting-started.md#connecting-to-the-service-via-python-rpc-client
+[Customizing Web Interface]: ./user-guide/interaction/README.md#customization-options
+[Task Management]: ./user-guide/Tasks.md
+[Units]: ./user-guide/Understanding-Units.md
+[Property Validation]: ./user-guide/Validating-Property-Setters.md

docs/requirements.txt

@@ -1,20 +1,38 @@
+babel==2.15.0 ; python_version >= "3.10" and python_version < "4.0"
+beautifulsoup4==4.12.3 ; python_version >= "3.10" and python_version < "4.0"
+certifi==2024.7.4 ; python_version >= "3.10" and python_version < "4.0"
+charset-normalizer==3.3.2 ; python_version >= "3.10" and python_version < "4.0"
 click==8.1.7 ; python_version >= "3.10" and python_version < "4.0"
-colorama==0.4.6 ; python_version >= "3.10" and python_version < "4.0" and platform_system == "Windows"
+colorama==0.4.6 ; python_version >= "3.10" and python_version < "4.0"
 ghp-import==2.1.0 ; python_version >= "3.10" and python_version < "4.0"
-jinja2==3.1.2 ; python_version >= "3.10" and python_version < "4.0"
-markdown==3.4.4 ; python_version >= "3.10" and python_version < "4.0"
-markupsafe==2.1.3 ; python_version >= "3.10" and python_version < "4.0"
+griffe==1.1.0 ; python_version >= "3.10" and python_version < "4.0"
+idna==3.7 ; python_version >= "3.10" and python_version < "4.0"
+jinja2==3.1.4 ; python_version >= "3.10" and python_version < "4.0"
+markdown==3.6 ; python_version >= "3.10" and python_version < "4.0"
+markupsafe==2.1.5 ; python_version >= "3.10" and python_version < "4.0"
 mergedeep==1.3.4 ; python_version >= "3.10" and python_version < "4.0"
-mkdocs-autorefs==0.5.0 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs-autorefs==1.0.1 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs-get-deps==0.2.0 ; python_version >= "3.10" and python_version < "4.0"
 mkdocs-include-markdown-plugin==3.9.1 ; python_version >= "3.10" and python_version < "4.0"
-mkdocs==1.5.3 ; python_version >= "3.10" and python_version < "4.0"
-mkdocstrings==0.22.0 ; python_version >= "3.10" and python_version < "4.0"
-packaging==23.1 ; python_version >= "3.10" and python_version < "4.0"
-pathspec==0.11.2 ; python_version >= "3.10" and python_version < "4.0"
-platformdirs==3.10.0 ; python_version >= "3.10" and python_version < "4.0"
-pymdown-extensions==10.3 ; python_version >= "3.10" and python_version < "4.0"
-python-dateutil==2.8.2 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs-material-extensions==1.3.1 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs-material==9.5.31 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs-swagger-ui-tag==0.6.10 ; python_version >= "3.10" and python_version < "4.0"
+mkdocs==1.6.0 ; python_version >= "3.10" and python_version < "4.0"
+mkdocstrings-python==1.10.8 ; python_version >= "3.10" and python_version < "4.0"
+mkdocstrings==0.25.2 ; python_version >= "3.10" and python_version < "4.0"
+mkdocstrings[python]==0.25.2 ; python_version >= "3.10" and python_version < "4.0"
+packaging==24.1 ; python_version >= "3.10" and python_version < "4.0"
+paginate==0.5.6 ; python_version >= "3.10" and python_version < "4.0"
+pathspec==0.12.1 ; python_version >= "3.10" and python_version < "4.0"
+platformdirs==4.2.2 ; python_version >= "3.10" and python_version < "4.0"
+pygments==2.18.0 ; python_version >= "3.10" and python_version < "4.0"
+pymdown-extensions==10.9 ; python_version >= "3.10" and python_version < "4.0"
+python-dateutil==2.9.0.post0 ; python_version >= "3.10" and python_version < "4.0"
 pyyaml-env-tag==0.1 ; python_version >= "3.10" and python_version < "4.0"
 pyyaml==6.0.1 ; python_version >= "3.10" and python_version < "4.0"
+regex==2024.7.24 ; python_version >= "3.10" and python_version < "4.0"
+requests==2.32.3 ; python_version >= "3.10" and python_version < "4.0"
 six==1.16.0 ; python_version >= "3.10" and python_version < "4.0"
-watchdog==3.0.0 ; python_version >= "3.10" and python_version < "4.0"
+soupsieve==2.5 ; python_version >= "3.10" and python_version < "4.0"
+urllib3==2.2.2 ; python_version >= "3.10" and python_version < "4.0"
+watchdog==4.0.1 ; python_version >= "3.10" and python_version < "4.0"

docs/user-guide/Components.md

@@ -1,6 +1,435 @@
 # Components Guide
-{%
-   include-markdown "../../README.md"
-   start="<!-- Component User Guide Start -->"
-   end="<!-- Component User Guide End -->"
-%}
+
+In `pydase`, components are fundamental building blocks that bridge the Python backend logic with frontend visual representation and interactions. This system can be understood based on the following categories:
+
+## Built-in Type and Enum Components
+
+`pydase` automatically maps standard Python data types to their corresponding frontend components:
+
+- `str`: Translated into a `StringComponent` on the frontend.
+- `int` and `float`: Manifested as the `NumberComponent`.
+- `bool`: Rendered as a `ButtonComponent`.
+- `list`: Each item displayed individually, named after the list attribute and its index.
+- `dict`: Each key-value pair displayed individually, named after the dictionary attribute and its key. **Note** that the dictionary keys must be strings.
+- `enum.Enum`: Presented as an `EnumComponent`, facilitating dropdown selection.
+
+## Method Components
+Within the `DataService` class of `pydase`, only methods devoid of arguments can be represented in the frontend, classified into two distinct categories
+
+1. [**Tasks**](./Tasks.md): Argument-free asynchronous functions, identified within `pydase` as tasks, are inherently designed for frontend interaction. These tasks are automatically rendered with a start/stop button, allowing users to initiate or halt the task execution directly from the web interface. 
+2. **Synchronous Methods with `@frontend` Decorator**: Synchronous methods without arguments can also be presented in the frontend. For this, they have to be decorated with the `@frontend` decorator.
+
+```python
+import pydase
+import pydase.components
+import pydase.units as u
+from pydase.utils.decorators import frontend
+
+
+class MyService(pydase.DataService):
+    @frontend
+    def exposed_method(self) -> None:
+        ...
+
+    async def my_task(self) -> None:
+        while True:
+            # ...
+```
+
+![Method Components](../images/method_components.png)
+
+You can still define synchronous tasks with arguments and call them using a python client. However, decorating them with the `@frontend` decorator will raise a `FunctionDefinitionError`. Defining a task with arguments will raise a `TaskDefinitionError`.
+I decided against supporting function arguments for functions rendered in the frontend due to the following reasons:
+
+1. Feature Request Pitfall: supporting function arguments create a bottomless pit of feature requests. As users encounter the limitations of supported types, demands for extending support to more complex types would grow.
+2. Complexity in Supported Argument Types: while simple types like `int`, `float`, `bool` and `str` could be easily supported, more complicated types are not (representation, (de-)serialization).
+
+## DataService Instances (Nested Classes)
+
+Nested `DataService` instances offer an organized hierarchy for components, enabling richer applications. Each nested class might have its own attributes and methods, each mapped to a frontend component.
+
+Here is an example:
+
+```python
+from pydase import DataService, Server
+
+
+class Channel(DataService):
+    def __init__(self, channel_id: int) -> None:
+        super().__init__()
+        self._channel_id = channel_id
+        self._current = 0.0
+
+    @property
+    def current(self) -> float:
+        # run code to get current
+        result = self._current
+        return result
+
+    @current.setter
+    def current(self, value: float) -> None:
+        # run code to set current
+        self._current = value
+
+
+class Device(DataService):
+    def __init__(self) -> None:
+        super().__init__()
+        self.channels = [Channel(i) for i in range(2)]
+
+
+if __name__ == "__main__":
+    service = Device()
+    Server(service).run()
+```
+
+![Nested Classes App](../images/Nested_Class_App.png)
+
+**Note** that defining classes within `DataService` classes is not supported (see [this issue](https://github.com/tiqi-group/pydase/issues/16)).
+
+## Custom Components (`pydase.components`)
+
+The custom components in `pydase` have two main parts:
+
+- A **Python Component Class** in the backend, implementing the logic needed to set, update, and manage the component's state and data.
+- A **Frontend React Component** that renders and manages user interaction in the browser.
+
+Below are the components available in the `pydase.components` module, accompanied by their Python usage:
+
+### `DeviceConnection`
+
+The `DeviceConnection` component acts as a base class within the `pydase` framework for managing device connections. It provides a structured approach to handle connections by offering a customizable `connect` method and a `connected` property. This setup facilitates the implementation of automatic reconnection logic, which periodically attempts reconnection whenever the connection is lost.
+
+In the frontend, this class abstracts away the direct interaction with the `connect` method and the `connected` property. Instead, it showcases user-defined attributes, methods, and properties. When the `connected` status is `False`, the frontend displays an overlay that prompts manual reconnection through the `connect()` method. Successful reconnection removes the overlay.
+
+```python
+import pydase.components
+import pydase.units as u
+
+
+class Device(pydase.components.DeviceConnection):
+    def __init__(self) -> None:
+        super().__init__()
+        self._voltage = 10 * u.units.V
+
+    def connect(self) -> None:
+        if not self._connected:
+            self._connected = True
+
+    @property
+    def voltage(self) -> float:
+        return self._voltage
+
+
+class MyService(pydase.DataService):
+    def __init__(self) -> None:
+        super().__init__()
+        self.device = Device()
+
+
+if __name__ == "__main__":
+    service_instance = MyService()
+    pydase.Server(service_instance).run()
+```
+
+![DeviceConnection Component](../images/DeviceConnection_component.png)
+
+#### Customizing Connection Logic
+
+Users are encouraged to primarily override the `connect` method to tailor the connection process to their specific device. This method should adjust the `self._connected` attribute based on the outcome of the connection attempt:
+
+```python
+import pydase.components
+
+
+class MyDeviceConnection(pydase.components.DeviceConnection):
+    def __init__(self) -> None:
+        super().__init__()
+        # Add any necessary initialization code here
+
+    def connect(self) -> None:
+        # Implement device-specific connection logic here
+        # Update self._connected to `True` if the connection is successful,
+        # or `False` if unsuccessful
+        ...
+```
+
+Moreover, if the connection status requires additional logic, users can override the `connected` property:
+
+```python
+import pydase.components
+
+class MyDeviceConnection(pydase.components.DeviceConnection):
+    def __init__(self) -> None:
+        super().__init__()
+        # Add any necessary initialization code here
+
+    def connect(self) -> None:
+        # Implement device-specific connection logic here
+        # Ensure self._connected reflects the connection status accurately
+        ...
+
+    @property
+    def connected(self) -> bool:
+        # Implement custom logic to accurately report connection status
+        return self._connected
+```
+
+#### Reconnection Interval
+
+The `DeviceConnection` component automatically executes a task that checks for device availability at a default interval of 10 seconds. This interval is adjustable by modifying the `_reconnection_wait_time` attribute on the class instance.
+
+### `Image`
+
+This component provides a versatile interface for displaying images within the application. Users can update and manage images from various sources, including local paths, URLs, and even matplotlib figures.
+
+The component offers methods to load images seamlessly, ensuring that visual content is easily integrated and displayed within the data service.
+
+```python
+import matplotlib.pyplot as plt
+import numpy as np
+import pydase
+from pydase.components.image import Image
+
+
+class MyDataService(pydase.DataService):
+    my_image = Image()
+
+
+if __name__ == "__main__":
+    service = MyDataService()
+    # loading from local path
+    service.my_image.load_from_path("/your/image/path/")
+
+    # loading from a URL
+    service.my_image.load_from_url("https://cataas.com/cat")
+
+    # loading a matplotlib figure
+    fig = plt.figure()
+    x = np.linspace(0, 2 * np.pi)
+    plt.plot(x, np.sin(x))
+    plt.grid()
+    service.my_image.load_from_matplotlib_figure(fig)
+
+    pydase.Server(service).run()
+```
+
+![Image Component](../images/Image_component.png)
+
+### `NumberSlider`
+
+The `NumberSlider` component in the `pydase` package provides an interactive slider interface for adjusting numerical values on the frontend. It is designed to support both numbers and quantities and ensures that values adjusted on the frontend are synchronized with the backend.
+
+To utilize the `NumberSlider`, users should implement a class that derives from `NumberSlider`. This class can then define the initial values, minimum and maximum limits, step sizes, and additional logic as needed.
+
+Here's an example of how to implement and use a custom slider:
+
+```python
+import pydase
+import pydase.components
+
+
+class MySlider(pydase.components.NumberSlider):
+    def __init__(
+        self,
+        value: float = 0.0,
+        min_: float = 0.0,
+        max_: float = 100.0,
+        step_size: float = 1.0,
+    ) -> None:
+        super().__init__(value, min_, max_, step_size)
+
+    @property
+    def min(self) -> float:
+        return self._min
+
+    @min.setter
+    def min(self, value: float) -> None:
+        self._min = value
+
+    @property
+    def max(self) -> float:
+        return self._max
+
+    @max.setter
+    def max(self, value: float) -> None:
+        self._max = value
+
+    @property
+    def step_size(self) -> float:
+        return self._step_size
+
+    @step_size.setter
+    def step_size(self, value: float) -> None:
+        self._step_size = value
+
+    @property
+    def value(self) -> float:
+        """Slider value."""
+        return self._value
+
+    @value.setter
+    def value(self, value: float) -> None:
+        if value < self._min or value > self._max:
+            raise ValueError("Value is either below allowed min or above max value.")
+
+        self._value = value
+
+
+class MyService(pydase.DataService):
+    def __init__(self) -> None:
+        super().__init__()
+        self.voltage = MySlider()
+
+
+if __name__ == "__main__":
+    service_instance = MyService()
+    service_instance.voltage.value = 5
+    print(service_instance.voltage.value)  # Output: 5
+    pydase.Server(service_instance).run()
+```
+
+In this example, `MySlider` overrides the `min`, `max`, `step_size`, and `value` properties. Users can make any of these properties read-only by omitting the corresponding setter method.
+
+![Slider Component](../images/Slider_component.png)
+
+- Accessing parent class resources in `NumberSlider`
+
+    In scenarios where you need the slider component to interact with or access resources from its parent class, you can achieve this by passing a callback function to it. This method avoids directly passing the entire parent class instance (`self`) and offers a more encapsulated approach. The callback function can be designed to utilize specific attributes or methods of the parent class, allowing the slider to perform actions or retrieve data in response to slider events.
+
+    Here's an illustrative example:
+
+    ```python
+    from collections.abc import Callable
+
+    import pydase
+    import pydase.components
+
+
+    class MySlider(pydase.components.NumberSlider):
+        def __init__(
+            self,
+            value: float,
+            on_change: Callable[[float], None],
+        ) -> None:
+            super().__init__(value=value)
+            self._on_change = on_change
+
+        # ... other properties ...
+
+        @property
+        def value(self) -> float:
+            return self._value
+
+        @value.setter
+        def value(self, new_value: float) -> None:
+            if new_value < self._min or new_value > self._max:
+                raise ValueError("Value is either below allowed min or above max value.")
+            self._value = new_value
+            self._on_change(new_value)
+
+
+    class MyService(pydase.DataService):
+        def __init__(self) -> None:
+            self.voltage = MySlider(
+                5,
+                on_change=self.handle_voltage_change,
+            )
+
+        def handle_voltage_change(self, new_voltage: float) -> None:
+            print(f"Voltage changed to: {new_voltage}")
+            # Additional logic here
+
+    if __name__ == "__main__":
+       service_instance = MyService()
+       my_service.voltage.value = 7  # Output: "Voltage changed to: 7"
+       pydase.Server(service_instance).run()
+    ```
+
+- Incorporating units in `NumberSlider`
+
+    The `NumberSlider` is capable of [displaying units](./Understanding-Units.md) alongside values, enhancing its usability in contexts where unit representation is crucial. When utilizing `pydase.units`, you can specify units for the slider's value, allowing the component to reflect these units in the frontend.
+
+    Here's how to implement a `NumberSlider` with unit display:
+
+    ```python
+    import pydase
+    import pydase.components
+    import pydase.units as u
+
+    class MySlider(pydase.components.NumberSlider):
+        def __init__(
+            self,
+            value: u.Quantity = 0.0 * u.units.V,
+        ) -> None:
+            super().__init__(value)
+
+        @property
+        def value(self) -> u.Quantity:
+            return self._value
+
+        @value.setter
+        def value(self, value: u.Quantity) -> None:
+            if value.m < self._min or value.m > self._max:
+                raise ValueError("Value is either below allowed min or above max value.")
+            self._value = value
+
+    class MyService(pydase.DataService):
+        def __init__(self) -> None:
+            super().__init__()
+            self.voltage = MySlider()
+
+    if __name__ == "__main__":
+        service_instance = MyService()
+        service_instance.voltage.value = 5 * u.units.V
+        print(service_instance.voltage.value)  # Output: 5 V
+        pydase.Server(service_instance).run()
+    ```
+
+### `ColouredEnum`
+
+This component provides a way to visually represent different states or categories in a data service using colour-coded options. It behaves similarly to a standard `Enum`, but the values encode colours in a format understood by CSS. The colours can be defined using various methods like Hexadecimal, RGB, HSL, and more.
+
+If the property associated with the `ColouredEnum` has a setter function, the keys of the enum will be rendered as a dropdown menu, allowing users to interact and select different options. Without a setter function, the selected key will simply be displayed as a coloured box with text inside, serving as a visual indicator.
+
+```python
+import pydase
+import pydase.components as pyc
+
+
+class MyStatus(pyc.ColouredEnum):
+    PENDING = "#FFA500"  # Hexadecimal colour (Orange)
+    RUNNING = "#0000FF80"  # Hexadecimal colour with transparency (Blue)
+    PAUSED = "rgb(169, 169, 169)"  # RGB colour (Dark Gray)
+    RETRYING = "rgba(255, 255, 0, 0.3)"  # RGB colour with transparency (Yellow)
+    COMPLETED = "hsl(120, 100%, 50%)"  # HSL colour (Green)
+    FAILED = "hsla(0, 100%, 50%, 0.7)"  # HSL colour with transparency (Red)
+    CANCELLED = "SlateGray"  # Cross-browser colour name (Slate Gray)
+
+
+class StatusTest(pydase.DataService):
+    _status = MyStatus.RUNNING
+
+    @property
+    def status(self) -> MyStatus:
+        return self._status
+
+    @status.setter
+    def status(self, value: MyStatus) -> None:
+        # do something ...
+        self._status = value
+
+# Modifying or accessing the status value:
+my_service = StatusExample()
+my_service.status = MyStatus.FAILED
+```
+
+![ColouredEnum Component](../images/ColouredEnum_component.png)
+
+**Note** that each enumeration name and value must be unique.
+This means that you should use different colour formats when you want to use a colour multiple times.
+
+### Extending with New Components
+
+Users can also extend the library by creating custom components. This involves defining the behavior on the Python backend and the visual representation on the frontend. For those looking to introduce new components, the [guide on adding components](https://pydase.readthedocs.io/en/latest/dev-guide/Adding_Components/) provides detailed steps on achieving this.
+

docs/user-guide/Service_Persistence.md

@@ -0,0 +1,49 @@
+# Understanding Service Persistence
+
+`pydase` allows you to easily persist the state of your service by saving it to a file. This is especially useful when you want to maintain the service's state across different runs.
+
+To save the state of your service, pass a `filename` keyword argument to the constructor of the `pydase.Server` class. If the file specified by `filename` does not exist, the state manager will create this file and store its state in it when the service is shut down. If the file already exists, the state manager will load the state from this file, setting the values of its attributes to the values stored in the file.
+
+Here's an example:
+
+```python
+import pydase
+
+class Device(pydase.DataService):
+    # ... defining the Device class ...
+
+
+if __name__ == "__main__":
+    service = Device()
+    pydase.Server(service=service, filename="device_state.json").run()
+```
+
+In this example, the state of the `Device` service will be saved to `device_state.json` when the service is shut down. If `device_state.json` exists when the server is started, the state manager will restore the state of the service from this file.
+
+## Controlling Property State Loading with `@load_state`
+
+By default, the state manager only restores values for public attributes of your service. If you have properties that you want to control the loading for, you can use the `@load_state` decorator on your property setters. This indicates to the state manager that the value of the property should be loaded from the state file.
+
+Here is how you can apply the `@load_state` decorator:
+
+```python
+import pydase
+from pydase.data_service.state_manager import load_state
+
+class Device(pydase.DataService):
+    _name = "Default Device Name"
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    @name.setter
+    @load_state
+    def name(self, value: str) -> None:
+        self._name = value
+```
+
+With the `@load_state` decorator applied to the `name` property setter, the state manager will load and apply the `name` property's value from the file storing the state upon server startup, assuming it exists.
+
+Note: If the service class structure has changed since the last time its state was saved, only the attributes and properties decorated with `@load_state` that have remained the same will be restored from the settings file.
+

docs/user-guide/Tasks.md

@@ -0,0 +1,38 @@
+# Understanding Tasks
+
+In `pydase`, a task is defined as an asynchronous function without arguments that is decorated with the `@task` decorator and contained in a class that inherits from `pydase.DataService`. These tasks usually contain a while loop and are designed to carry out periodic functions. For example, a task might be used to periodically read sensor data, update a database, or perform any other recurring job.
+
+`pydase` allows you to control task execution via both the frontend and Python clients and can automatically start tasks upon initialization of the service. By using the `@task` decorator with the `autostart=True` argument in your service class, `pydase` will automatically start these tasks when the server is started. Here's an example:
+
+```python
+import pydase
+from pydase.task.decorator import task
+
+
+class SensorService(pydase.DataService):
+    def __init__(self):
+        super().__init__()
+        self.readout_frequency = 1.0
+
+    def _process_data(self, data: ...) -> None:
+        ...
+
+    def _read_from_sensor(self) -> Any:
+        ...
+
+    @task(autostart=True)
+    async def read_sensor_data(self):
+        while True:
+            data = self._read_from_sensor()
+            self._process_data(data)  # Process the data as needed
+            await asyncio.sleep(self.readout_frequency)
+
+
+if __name__ == "__main__":
+    service = SensorService()
+    pydase.Server(service=service).run()
+```
+
+In this example, `read_sensor_data` is a task that continuously reads data from a sensor. By decorating it with `@task(autostart=True)`, it will automatically start running when `pydase.Server(service).run()` is executed.
+
+The `@task` decorator replaces the function with a task object that has `start()` and `stop()` methods. This means you can control the task execution directly using these methods. For instance, you can manually start or stop the task by calling `service.read_sensor_data.start()` and `service.read_sensor_data.stop()`, respectively.

docs/user-guide/Understanding-Units.md

@@ -0,0 +1,64 @@
+# Understanding Units
+
+`pydase` integrates with the [`pint`](https://pint.readthedocs.io/en/stable/) package to allow you to work with physical quantities within your service. This enables you to define attributes with units, making your service more expressive and ensuring consistency in the handling of physical quantities.
+
+You can define quantities in your `pydase.DataService` subclass using the `pydase.units` module.
+Here's an example:
+
+```python
+from typing import Any
+
+import pydase
+import pydase.units as u
+
+
+class ServiceClass(pydase.DataService):
+    voltage = 1.0 * u.units.V
+    _current: u.Quantity = 1.0 * u.units.mA
+
+    @property
+    def current(self) -> u.Quantity:
+        return self._current
+
+    @current.setter
+    def current(self, value: u.Quantity) -> None:
+        self._current = value
+
+
+if __name__ == "__main__":
+    service = ServiceClass()
+
+    service.voltage = 10.0 * u.units.V
+    service.current = 1.5 * u.units.mA
+
+    pydase.Server(service=service).run()
+```
+
+In the frontend, quantities are rendered as floats, with the unit displayed as additional text. This allows you to maintain a clear and consistent representation of physical quantities across both the backend and frontend of your service.
+![Web interface with rendered units](../images/Units_App.png)
+
+Should you need to access the magnitude or the unit of a quantity, you can use the `.m` attribute or the `.u` attribute of the variable, respectively. For example, this could be necessary to set the periodicity of a task:
+
+```python
+import asyncio
+import pydase
+import pydase.units as u
+
+
+class ServiceClass(pydase.DataService):
+    readout_wait_time = 1.0 * u.units.ms
+
+    async def read_sensor_data(self):
+        while True:
+            print("Reading out sensor ...")
+            await asyncio.sleep(self.readout_wait_time.to("s").m)
+
+
+if __name__ == "__main__":
+    service = ServiceClass()
+
+    pydase.Server(service=service).run()
+```
+
+For more information about what you can do with the units, please consult the documentation of [`pint`](https://pint.readthedocs.io/en/stable/).
+

docs/user-guide/Validating-Property-Setters.md

@@ -0,0 +1,38 @@
+# Using `validate_set` to Validate Property Setters
+
+The `validate_set` decorator ensures that a property setter reads back the set value using the property getter and checks it against the desired value.
+This decorator can be used to validate that a parameter has been correctly set on a device within a specified precision and timeout.
+
+The decorator takes two keyword arguments: `timeout` and `precision`. The `timeout` argument specifies the maximum time (in seconds) to wait for the value to be within the precision boundary.
+If the value is not within the precision boundary after this time, an exception is raised.
+The `precision` argument defines the acceptable deviation from the desired value.
+If `precision` is `None`, the value must be exact.
+For example, if `precision` is set to `1e-5`, the value read from the device must be within ±0.00001 of the desired value.
+
+Here’s how to use the `validate_set` decorator in a `DataService` class:
+
+```python
+import pydase
+from pydase.observer_pattern.observable.decorators import validate_set
+
+
+class Service(pydase.DataService):
+    def __init__(self) -> None:
+        super().__init__()
+        self._device = RemoteDevice()  # dummy class
+
+    @property
+    def value(self) -> float:
+        # Implement how to get the value from the remote device...
+        return self._device.value
+
+    @value.setter
+    @validate_set(timeout=1.0, precision=1e-5)
+    def value(self, value: float) -> None:
+        # Implement how to set the value on the remote device...
+        self._device.value = value
+
+
+if __name__ == "__main__":
+    pydase.Server(service=Service()).run()
+```

docs/user-guide/interaction/Auto-generated Frontend.md

@@ -0,0 +1,167 @@
+# Auto-generated Frontend
+
+`pydase` automatically generates a frontend interface based on your service definition, representing the current state and controls of the service.
+It simplifies the process of visualization and control of the data and devices managed by your `pydase` service, making it accessible to both developers and end-users.
+
+Through the integration of Socket.IO, the frontend provides real-time updates, reflecting changes as they occur and allowing for immediate interaction with the backend.
+
+
+## Accessing the Frontend
+
+You can access the auto-generated frontend by navigating to the hostname of the device the service is hosted on, followed by the exposed port:
+
+```
+http://<hostname>:<port>/
+```
+
+The frontend uses a component-based approach, representing various data types and control mechanisms as distinct UI components. For more information about this, please refer to [Components Guide](../Components.md).
+
+## Customization Options
+
+`pydase` allows you to enhance the user experience by customizing the web interface's appearance through
+
+1. a custom CSS file, and
+2. tailoring the frontend component layout and display style.
+
+For more advanced customization, you can provide a completely custom frontend source.
+
+### Custom CSS Styling
+
+You can apply your own styles globally across the web interface by passing a custom CSS file to the server during initialization.
+Here's how you can use this feature:
+
+1. Prepare your custom CSS file with the desired styles.
+
+2. When initializing your server, use the `css` parameter of the `Server` class to specify the path to your custom CSS file.
+
+```python
+from pydase import Server, DataService
+
+
+class MyService(DataService):
+    # ... your service definition ...
+
+
+if __name__ == "__main__":
+    service = MyService()
+    server = Server(service, css="path/to/your/custom.css").run()
+```
+
+This will apply the styles defined in `custom.css` to the web interface, allowing you to maintain branding consistency or improve visual accessibility.
+
+Please ensure that the CSS file path is accessible from the server's running location. Relative or absolute paths can be used depending on your setup.
+
+### Tailoring Frontend Component Layout
+
+You can customize the display names, visibility, and order of components via the `web_settings.json` file.
+Each key in the file corresponds to the full access path of public attributes, properties, and methods of the exposed service, using dot-notation.
+
+- **Custom Display Names**: Modify the `"displayName"` value in the file to change how each component appears in the frontend.
+- **Control Component Visibility**: Utilize the `"display"` key-value pair to control whether a component is rendered in the frontend. Set the value to `true` to make the component visible or `false` to hide it.
+- **Adjustable Component Order**: The `"displayOrder"` values determine the order of components. Alter these values to rearrange the components as desired. The value defaults to [`Number.MAX_SAFE_INTEGER`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Number/MAX_SAFE_INTEGER).
+
+The `web_settings.json` file will be stored in the directory specified by `SERVICE_CONFIG_DIR`. You can generate a `web_settings.json` file by setting the `GENERATE_WEB_SETTINGS` to `True`. For more information, see the [configuration section](#configuring-pydase-via-environment-variables).
+
+For example, styling the following service 
+
+```python
+import pydase
+
+
+class Device(pydase.DataService):
+    name = "My Device"
+    temperature = 1.0
+    power = 1
+
+
+class Service(pydase.DataService):
+    device = Device()
+    state = "RUNNING"
+
+
+if __name__ == "__main__":
+    pydase.Server(Service()).run()
+```
+
+with the following `web_settings.json`
+
+```json
+{
+    "device": {
+        "displayName": "My Device",
+        "displayOrder": 1
+    },
+    "device.name": {
+        "display": false
+    },
+    "device.power": {
+        "displayName": "Power",
+        "displayOrder": 1
+    },
+    "device.temperature": {
+      "displayName": "Temperature",
+      "displayOrder": 0
+    },
+    "state": {
+        "displayOrder": 0
+    }
+}
+```
+
+looks like this:
+
+![Tailoring frontend component layout](../../images/Tailoring_frontend_component_layout.png)
+
+### Specifying a Custom Frontend Source
+
+To further customize your web interface, you can provide a custom frontend source.
+By specifying the `frontend_src` parameter when initializing the server, you can host a tailored frontend application:
+
+```python
+from pathlib import Path
+
+import pydase
+
+
+class MyService(pydase.DataService):
+    # Service definition
+
+
+if __name__ == "__main__":
+    service = MyService()
+    pydase.Server(
+        service,
+        frontend_src=Path("path/to/your/frontend/directory"),
+    ).run()
+```
+
+`pydase` expects a directory structured as follows:
+
+```bash  title="Frontend directory structure"
+<your_frontend_directory>
+├── assets
+│   └── ...
+└── index.html
+```
+
+Any CSS, js, image or other files need to be put into the assets folder for the web server to be able to provide access to it.
+
+#### Example: Custom React Frontend
+
+You can use vite to generate a react app template:
+
+```bash
+npm create vite@latest my-react-app -- --template react
+```
+
+*TODO: Add some useful information here...*
+
+To deploy the custom react frontend, build it with
+
+```bash
+npm run build
+```
+
+and pass the relative path of the output directory to the `frontend_src` parameter of the `pydase.Server`.
+
+**Note** that you have to make sure that all the generated files (except the `index.html`) are in the `assets` folder. In the react app, you can achieve this by not using the `public` folder, but instead using e.g. `src/assets`.

docs/user-guide/interaction/Python Client.md

@@ -0,0 +1,60 @@
+# Python RPC Client
+
+You can connect to the service using the `pydase.Client`. Below is an example of how to establish a connection to a service and interact with it:
+
+```python
+import pydase
+
+# Replace the hostname and port with the IP address and the port of the machine where 
+# the service is running, respectively
+client_proxy = pydase.Client(url="ws://<ip_addr>:<service_port>").proxy
+# client_proxy = pydase.Client(url="wss://your-domain.ch").proxy  # if your service uses ssl-encryption
+
+# Interact with the service attributes as if they were local
+client_proxy.voltage = 5.0
+print(client_proxy.voltage)  # Expected output: 5.0
+```
+
+This example demonstrates setting and retrieving the `voltage` attribute through the client proxy.
+The proxy acts as a local representative of the remote service, enabling straightforward interaction.
+
+The proxy class dynamically synchronizes with the server's exposed attributes. This synchronization allows the proxy to be automatically updated with any attributes or methods that the server exposes, essentially mirroring the server's API. This dynamic updating enables users to interact with the remote service as if they were working with a local object.
+
+## Context Manager
+
+You can also use the client as a context manager which automatically opens and closes the connection again:
+
+```python
+import pydase
+
+
+with pydase.Client(url="ws://localhost:8001") as client:
+    client.proxy.<my_method>()
+```
+
+
+## Tab Completion Support
+
+In interactive environments such as Python interpreters and Jupyter notebooks, the proxy class supports tab completion, which allows users to explore available methods and attributes.
+
+## Integration within Other Services
+
+You can also integrate a client proxy within another service. Here's how you can set it up:
+
+```python
+import pydase
+
+class MyService(pydase.DataService):
+    # Initialize the client without blocking the constructor
+    proxy = pydase.Client(url="ws://<ip_addr>:<service_port>", block_until_connected=False).proxy
+    # proxy = pydase.Client(url="wss://your-domain.ch", block_until_connected=False).proxy  # communicating with ssl-encrypted service
+
+if __name__ == "__main__":
+    service = MyService()
+    # Create a server that exposes this service; adjust the web_port as needed
+    server = pydase.Server(service, web_port=8002). run()
+```
+
+In this setup, the `MyService` class has a `proxy` attribute that connects to a `pydase` service located at `<ip_addr>:8001`.
+The `block_until_connected=False` argument allows the service to start up even if the initial connection attempt fails.
+This configuration is particularly useful in distributed systems where services may start in any order.

docs/user-guide/interaction/README.md

@@ -0,0 +1,81 @@
+# Interacting with `pydase` Services
+
+`pydase` offers multiple ways for users to interact with the services they create, providing flexibility and convenience for different use cases. This section outlines the primary interaction methods available, including an auto-generated frontend, a RESTful API, and a Python client based on Socket.IO.
+
+{%
+   include-markdown "./Auto-generated Frontend.md"
+   heading-offset=1
+%}
+
+{%
+   include-markdown "./RESTful API.md"
+   heading-offset=1
+%}
+
+{%
+   include-markdown "./Python Client.md"
+   heading-offset=1
+%}
+
+<!-- ## 2. **Socket.IO for Real-Time Updates** -->
+<!-- For scenarios requiring real-time data updates, `pydase` includes a Socket.IO server. This feature is ideal for applications where live data tracking is crucial, such as monitoring systems or interactive dashboards. -->
+<!---->
+<!-- ### Key Features: -->
+<!-- - **Live Data Streams**: Receive real-time updates for data changes. -->
+<!-- - **Event-Driven Communication**: Utilize event-based messaging to push updates and handle client actions. -->
+<!---->
+<!-- ### Example Usage: -->
+<!-- Clients can connect to the Socket.IO server to receive updates: -->
+<!-- ```javascript -->
+<!-- var socket = io.connect('http://<hostname>:<port>'); -->
+<!-- socket.on('<event_name>', function(data) { -->
+<!--     console.log(data); -->
+<!-- }); -->
+<!-- ``` -->
+<!---->
+<!-- **Use Cases:** -->
+<!---->
+<!-- - Real-time monitoring and alerts -->
+<!-- - Live data visualization -->
+<!-- - Collaborative applications -->
+<!---->
+<!-- ## 3. **Auto-Generated Frontend** -->
+<!-- `pydase` automatically generates a web frontend based on the service definitions. This frontend is a convenient interface for interacting with the service, especially for users who prefer a graphical interface over command-line or code-based interactions. -->
+<!---->
+<!-- ### Key Features: -->
+<!-- - **User-Friendly Interface**: Intuitive and easy to use, with real-time interaction capabilities. -->
+<!-- - **Customizable**: Adjust the frontend's appearance and functionality to suit specific needs. -->
+<!---->
+<!-- ### Accessing the Frontend: -->
+<!-- Once the service is running, access the frontend via a web browser: -->
+<!-- ``` -->
+<!-- http://<hostname>:<port> -->
+<!-- ``` -->
+<!---->
+<!-- **Use Cases:** -->
+<!---->
+<!-- - End-user interfaces for data control and visualization -->
+<!-- - Rapid prototyping and testing -->
+<!-- - Demonstrations and training -->
+<!---->
+<!-- ## 4. **Python Client** -->
+<!-- `pydase` also provides a Python client for programmatic interactions. This client is particularly useful for developers who want to integrate `pydase` services into other Python applications or automate interactions. -->
+<!---->
+<!-- ### Key Features: -->
+<!-- - **Direct Interaction**: Call methods and access properties as if they were local. -->
+<!-- - **Tab Completion**: Supports tab completion in interactive environments like Jupyter notebooks. -->
+<!---->
+<!-- ### Example Usage: -->
+<!-- ```python -->
+<!-- import pydase -->
+<!---->
+<!-- client = pydase.Client(hostname="<ip_addr>", port=8001) -->
+<!-- service = client.proxy -->
+<!-- service.some_method() -->
+<!-- ``` -->
+<!---->
+<!-- **Use Cases:** -->
+<!---->
+<!-- - Integrating with other Python applications -->
+<!-- - Automation and scripting -->
+<!-- - Data analysis and manipulation -->

docs/user-guide/interaction/RESTful API.md

@@ -0,0 +1,22 @@
+# RESTful API
+
+The `pydase` RESTful API allows for standard HTTP-based interactions and provides access to various functionalities through specific routes. This is particularly useful for integrating `pydase` services with other applications or for scripting and automation.
+
+For example, you can get a value like this:
+
+```python
+import json
+
+import requests
+
+response = requests.get(
+    "http://<hostname>:<port>/api/v1/get_value?access_path=<full_access_path>"
+)
+serialized_value = json.loads(response.text)
+```
+
+To help developers understand and utilize the API, we provide an OpenAPI specification. This specification describes the available endpoints and corresponding request/response formats.
+
+## OpenAPI Specification
+
+<swagger-ui src="./openapi.yaml"/>

docs/user-guide/interaction/openapi.yaml

@@ -0,0 +1,326 @@
+openapi: 3.1.0
+info:
+  version: 1.0.0
+  title: pydase API
+tags:
+  - name: /api/v1
+    description: Version 1
+paths:
+  /api/v1/get_value:
+    get:
+      tags:
+        - /api/v1
+      summary: Get the value of an existing attribute.
+      description: Get the value of an existing attribute by full access path.
+      operationId: getValue
+      parameters:
+        - in: query
+          name: access_path
+          schema:
+            type: string
+          example:  device.channel[0].voltage
+          required: true
+          description: Full access path of the service attribute.
+      responses:
+        '200':
+          description: Successful Operation
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/SerializedAttribute'
+              examples:
+                Exists:
+                  summary: Attribute exists
+                  value:
+                    docs: My documentation string.
+                    full_access_path: device.channel[0].voltage
+                    readonly: false
+                    type: float
+                    value: 12.1
+        '400':
+          description: Could not get attribute
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/SerializedException'
+              examples:
+                Attribute:
+                  summary: Attribute does not exist
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: AttributeError
+                    readonly: true
+                    type: Exception
+                    value: "'MyService' object has no attribute 'invalid_attribute'"
+                List:
+                  summary: List index out of range
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: IndexError
+                    readonly: true
+                    type: Exception
+                    value: "list index out of range"
+  /api/v1/update_value:
+    put:
+      tags:
+        - /api/v1
+      summary: Update an existing attribute.
+      description: Update an existing attribute by full access path.
+      operationId: updateValue
+      requestBody:
+        description: Update an existent attribute in the service
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/UpdateValue'
+        required: true
+      responses:
+        '200':
+          description: Successful Operation
+        '400':
+          description: Could not Update Attribute
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/SerializedException'
+              examples:
+                Attribute:
+                  summary: Attribute does not exist
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: AttributeError
+                    readonly: true
+                    type: Exception
+                    value: "'MyService' object has no attribute 'invalid_attribute'"
+                ReadOnly:
+                  summary: Attribute is read-only
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: AttributeError
+                    readonly: true
+                    type: Exception
+                    value: "property 'readonly_property' of 'MyService' object has no setter"
+                List:
+                  summary: List index out of range
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: IndexError
+                    readonly: true
+                    type: Exception
+                    value: "list index out of range"
+  /api/v1/trigger_method:
+    put:
+      tags:
+        - /api/v1
+      summary: Trigger method.
+      description: Trigger method with by full access path with provided args and kwargs.
+      operationId: triggerMethod
+      requestBody:
+        description: Update an existent attribute in the service
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/TriggerMethod'
+        required: true
+      responses:
+        '200':
+          description: Successful Operation
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/SerializedAttribute'
+              examples:
+                NoneReturn:
+                  summary: Function returns None
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    readonly: false
+                    type: "NoneType"
+                    value: null
+                FloatReturn:
+                  summary: Function returns float
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    readonly: false
+                    type: "float"
+                    value: 23.2
+        '400':
+          description: Method does not exist
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/SerializedException'
+              examples:
+                Args:
+                  summary: Wrong number of arguments
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: TypeError
+                    readonly: true
+                    type: Exception
+                    value: "MyService.some_function() takes 1 positional argument but 2 were given"
+                Attribute:
+                  summary: Attribute does not exist
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: AttributeError
+                    readonly: true
+                    type: Exception
+                    value: "'MyService' object has no attribute 'invalid_method'"
+                List:
+                  summary: List index out of range
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: IndexError
+                    readonly: true
+                    type: Exception
+                    value: "list index out of range"
+                Dict:
+                  summary: Dictionary key does not exist
+                  value:
+                    docs: null
+                    full_access_path: ""
+                    name: KeyError
+                    readonly: true
+                    type: Exception
+                    value: "invalid_key"
+components:
+  schemas:
+    UpdateValue:
+      required:
+        - access_path
+        - value
+      type: object
+      properties:
+        access_path:
+          type: string
+          example: device.channel[0].voltage
+        value:
+          $ref: '#/components/schemas/SerializedValue'
+    TriggerMethod:
+      required:
+        - access_path
+      type: object
+      properties:
+        access_path:
+          type: string
+          example: device.channel[0].voltage
+        args:
+          type: object
+          required:
+            - type
+            - value
+            - full_access_path
+          properties:
+            full_access_path:
+              type: string
+              example: ""
+            type:
+              type: string
+              enum:
+                - list
+            value:
+              type: array
+              items:
+                $ref: '#/components/schemas/SerializedValue'
+        kwargs:
+          type: object
+          required:
+            - type
+            - value
+            - full_access_path
+          properties:
+            full_access_path:
+              type: string
+              example: ""
+            type:
+              type: string
+              enum:
+                - dict
+            value:
+              type: object
+              additionalProperties:
+                $ref: '#/components/schemas/SerializedValue'
+    SerializedValue:
+      required:
+        - full_access_path
+        - type
+        - value
+      type: object
+      properties:
+        docs:
+          type: string | null
+          example: null
+        full_access_path:
+          type: string
+          example: ""
+        readonly:
+          type: boolean
+          example: false
+        type:
+          type: string
+          example: float
+        value:
+          type: any
+          example: 22.0
+    SerializedAttribute:
+      required:
+        - full_access_path
+        - type
+        - value
+      type: object
+      properties:
+        docs:
+          type: string | null
+          example: My documentation string.
+        full_access_path:
+          type: string
+          example: device.channel[0].voltage
+        readonly:
+          type: boolean
+          example: false
+        type:
+          type: string
+          example: float
+        value:
+          type: any
+          example: 22.0
+    SerializedException:
+      required:
+        - full_access_path
+        - type
+        - value
+      type: object
+      properties:
+        docs:
+          type: string | null
+          example: Raised when the access path does not correspond to a valid attribute.
+        full_access_path:
+          type: string
+          example: ""
+        name:
+          type: string
+          example: SerializationPathError
+        readonly:
+          type: boolean
+          example: true
+        type:
+          type: string
+          example: Exception
+        value:
+          type: string
+          examples:
+            value:
+              "Index '2': list index out of range"
+            some:
+              "Index '2': list index out of range"

frontend/src/App.tsx

@@ -12,6 +12,7 @@ import { setNestedValueByPath, State } from "./utils/stateUtils";
 import { WebSettingsContext, WebSetting } from "./WebSettings";
 import { GenericComponent } from "./components/GenericComponent";
 import { SerializedObject } from "./types/SerializedObject";
+import useLocalStorage from "./hooks/useLocalStorage";
 
 type Action =
   | { type: "SET_DATA"; data: State }
@@ -53,15 +54,15 @@ const App = () => {
   const [state, dispatch] = useReducer(reducer, null);
   const [serviceName, setServiceName] = useState<string | null>(null);
   const [webSettings, setWebSettings] = useState<Record<string, WebSetting>>({});
-  const [isInstantUpdate, setIsInstantUpdate] = useState(() => {
-    const saved = localStorage.getItem("isInstantUpdate");
-    return saved !== null ? JSON.parse(saved) : false;
-  });
+  const [isInstantUpdate, setIsInstantUpdate] = useLocalStorage(
+    "isInstantUpdate",
+    false,
+  );
   const [showSettings, setShowSettings] = useState(false);
-  const [showNotification, setShowNotification] = useState(() => {
-    const saved = localStorage.getItem("showNotification");
-    return saved !== null ? JSON.parse(saved) : false;
-  });
+  const [showNotification, setShowNotification] = useLocalStorage(
+    "showNotification",
+    false,
+  );
   const [notifications, setNotifications] = useState<Notification[]>([]);
   const [connectionStatus, setConnectionStatus] = useState("connecting");
 
@@ -115,14 +116,6 @@ const App = () => {
     };
   }, []);
 
-  // Persist isInstantUpdate and showNotification state changes to localStorage
-  useEffect(() => {
-    localStorage.setItem("isInstantUpdate", JSON.stringify(isInstantUpdate));
-  }, [isInstantUpdate]);
-
-  useEffect(() => {
-    localStorage.setItem("showNotification", JSON.stringify(showNotification));
-  }, [showNotification]);
   // Adding useCallback to prevent notify to change causing a re-render of all
   // components
   const addNotification = useCallback(

frontend/src/WebSettings.tsx

@@ -5,5 +5,5 @@ export const WebSettingsContext = createContext<Record<string, WebSetting>>({});
 export interface WebSetting {
   displayName: string;
   display: boolean;
-  index: number;
+  displayOrder: number;
 }

frontend/src/components/ButtonComponent.tsx

@@ -3,7 +3,7 @@ import { ToggleButton } from "react-bootstrap";
 import { DocStringComponent } from "./DocStringComponent";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 interface ButtonComponentProps {
   fullAccessPath: string;

frontend/src/components/DataServiceComponent.tsx

@@ -1,10 +1,11 @@
-import { useEffect, useState } from "react";
 import React from "react";
 import { Card, Collapse } from "react-bootstrap";
 import { ChevronDown, ChevronRight } from "react-bootstrap-icons";
 import { GenericComponent } from "./GenericComponent";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
+import useLocalStorage from "../hooks/useLocalStorage";
+import useSortedEntries from "../hooks/useSortedEntries";
 
 interface DataServiceProps {
   props: DataServiceJSON;
@@ -19,15 +20,9 @@ export type DataServiceJSON = Record<string, SerializedObject>;
 export const DataServiceComponent = React.memo(
   ({ props, isInstantUpdate, addNotification, displayName, id }: DataServiceProps) => {
     // Retrieve the initial state from localStorage, default to true if not found
-    const [open, setOpen] = useState(() => {
-      const savedState = localStorage.getItem(`dataServiceComponent-${id}-open`);
-      return savedState !== null ? JSON.parse(savedState) : true;
-    });
+    const [open, setOpen] = useLocalStorage(`dataServiceComponent-${id}-open`, true);
 
-    // Update localStorage whenever the state changes
-    useEffect(() => {
-      localStorage.setItem(`dataServiceComponent-${id}-open`, JSON.stringify(open));
-    }, [open]);
+    const sortedEntries = useSortedEntries(props);
 
     if (displayName !== "") {
       return (
@@ -38,9 +33,9 @@ export const DataServiceComponent = React.memo(
             </Card.Header>
             <Collapse in={open}>
               <Card.Body>
-                {Object.entries(props).map(([key, value]) => (
+                {sortedEntries.map((value) => (
                   <GenericComponent
-                    key={key}
+                    key={value.full_access_path}
                     attribute={value}
                     isInstantUpdate={isInstantUpdate}
                     addNotification={addNotification}
@@ -54,9 +49,9 @@ export const DataServiceComponent = React.memo(
     } else {
       return (
         <div className="component dataServiceComponent" id={id}>
-          {Object.entries(props).map(([key, value]) => (
+          {sortedEntries.map((value) => (
             <GenericComponent
-              key={key}
+              key={value.full_access_path}
               attribute={value}
               isInstantUpdate={isInstantUpdate}
               addNotification={addNotification}

frontend/src/components/DictComponent.tsx

@@ -3,7 +3,8 @@ import { DocStringComponent } from "./DocStringComponent";
 import { GenericComponent } from "./GenericComponent";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
+import useSortedEntries from "../hooks/useSortedEntries";
 
 interface DictComponentProps {
   value: Record<string, SerializedObject>;
@@ -14,16 +15,16 @@ interface DictComponentProps {
 }
 
 export const DictComponent = React.memo((props: DictComponentProps) => {
-  const { value, docString, isInstantUpdate, addNotification, id } = props;
+  const { docString, isInstantUpdate, addNotification, id } = props;
 
+  const sortedEntries = useSortedEntries(props.value);
   const renderCount = useRenderCount();
-  const valueArray = Object.values(value);
 
   return (
     <div className={"listComponent"} id={id}>
       {process.env.NODE_ENV === "development" && <div>Render count: {renderCount}</div>}
       <DocStringComponent docString={docString} />
-      {valueArray.map((item) => {
+      {sortedEntries.map((item) => {
         return (
           <GenericComponent
             key={item.full_access_path}

frontend/src/components/EnumComponent.tsx

@@ -4,7 +4,7 @@ import { DocStringComponent } from "./DocStringComponent";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject, SerializedEnum } from "../types/SerializedObject";
 import { propsAreEqual } from "../utils/propsAreEqual";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 interface EnumComponentProps extends SerializedEnum {
   addNotification: (message: string, levelname?: LevelName) => void;

frontend/src/components/GenericComponent.tsx

@@ -4,7 +4,6 @@ import { NumberComponent, NumberObject } from "./NumberComponent";
 import { SliderComponent } from "./SliderComponent";
 import { EnumComponent } from "./EnumComponent";
 import { MethodComponent } from "./MethodComponent";
-import { AsyncMethodComponent } from "./AsyncMethodComponent";
 import { StringComponent } from "./StringComponent";
 import { ListComponent } from "./ListComponent";
 import { DataServiceComponent, DataServiceJSON } from "./DataServiceComponent";
@@ -17,6 +16,7 @@ import { updateValue } from "../socket";
 import { DictComponent } from "./DictComponent";
 import { parseFullAccessPath } from "../utils/stateUtils";
 import { SerializedEnum, SerializedObject } from "../types/SerializedObject";
+import { TaskComponent, TaskStatus } from "./TaskComponent";
 
 interface GenericComponentProps {
   attribute: SerializedObject;
@@ -144,30 +144,16 @@ export const GenericComponent = React.memo(
         />
       );
     } else if (attribute.type === "method") {
-      if (!attribute.async) {
-        return (
-          <MethodComponent
-            fullAccessPath={fullAccessPath}
-            docString={attribute.doc}
-            addNotification={addNotification}
-            displayName={displayName}
-            id={id}
-            render={attribute.frontend_render}
-          />
-        );
-      } else {
-        return (
-          <AsyncMethodComponent
-            fullAccessPath={fullAccessPath}
-            docString={attribute.doc}
-            value={attribute.value as "RUNNING" | null}
-            addNotification={addNotification}
-            displayName={displayName}
-            id={id}
-            render={attribute.frontend_render}
-          />
-        );
-      }
+      return (
+        <MethodComponent
+          fullAccessPath={fullAccessPath}
+          docString={attribute.doc}
+          addNotification={addNotification}
+          displayName={displayName}
+          id={id}
+          render={attribute.frontend_render}
+        />
+      );
     } else if (attribute.type === "str") {
       return (
         <StringComponent
@@ -182,6 +168,17 @@ export const GenericComponent = React.memo(
           id={id}
         />
       );
+    } else if (attribute.type == "Task") {
+      return (
+        <TaskComponent
+          fullAccessPath={fullAccessPath}
+          docString={attribute.doc}
+          status={attribute.value["status"].value as TaskStatus}
+          addNotification={addNotification}
+          displayName={displayName}
+          id={id}
+        />
+      );
     } else if (attribute.type === "DataService") {
       return (
         <DataServiceComponent

frontend/src/components/ImageComponent.tsx

@@ -3,7 +3,7 @@ import { Card, Collapse, Image } from "react-bootstrap";
 import { DocStringComponent } from "./DocStringComponent";
 import { ChevronDown, ChevronRight } from "react-bootstrap-icons";
 import { LevelName } from "./NotificationsComponent";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 interface ImageComponentProps {
   fullAccessPath: string;

frontend/src/components/ListComponent.tsx

@@ -3,7 +3,8 @@ import { DocStringComponent } from "./DocStringComponent";
 import { GenericComponent } from "./GenericComponent";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
+import useSortedEntries from "../hooks/useSortedEntries";
 
 interface ListComponentProps {
   value: SerializedObject[];
@@ -14,7 +15,9 @@ interface ListComponentProps {
 }
 
 export const ListComponent = React.memo((props: ListComponentProps) => {
-  const { value, docString, isInstantUpdate, addNotification, id } = props;
+  const { docString, isInstantUpdate, addNotification, id } = props;
+
+  const sortedEntries = useSortedEntries(props.value);
 
   const renderCount = useRenderCount();
 
@@ -22,7 +25,7 @@ export const ListComponent = React.memo((props: ListComponentProps) => {
     <div className={"listComponent"} id={id}>
       {process.env.NODE_ENV === "development" && <div>Render count: {renderCount}</div>}
       <DocStringComponent docString={docString} />
-      {value.map((item) => {
+      {sortedEntries.map((item) => {
         return (
           <GenericComponent
             key={item.full_access_path}

frontend/src/components/MethodComponent.tsx

@@ -3,7 +3,7 @@ import { runMethod } from "../socket";
 import { Button, Form } from "react-bootstrap";
 import { DocStringComponent } from "./DocStringComponent";
 import { LevelName } from "./NotificationsComponent";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 import { propsAreEqual } from "../utils/propsAreEqual";
 
 interface MethodProps {

frontend/src/components/NumberComponent.tsx

@@ -5,7 +5,7 @@ import "../App.css";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
 import { QuantityMap } from "../types/QuantityMap";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 // TODO: add button functionality
 
@@ -132,6 +132,8 @@ const handleNumericKey = (
   selectionStart: number,
   selectionEnd: number,
 ) => {
+  let newValue = value;
+
   // Check if a number key or a decimal point key is pressed
   if (key === "." && value.includes(".")) {
     // Check if value already contains a decimal. If so, ignore input.
@@ -139,14 +141,34 @@ const handleNumericKey = (
     return { value, selectionStart };
   }
 
-  let newValue = value;
+  // Handle minus sign input
+  if (key === "-") {
+    if (selectionStart === 0 && selectionEnd > selectionStart) {
+      // Replace selection with minus if selection starts at 0
+      newValue = "-" + value.slice(selectionEnd);
+      selectionStart = 1;
+    } else if (selectionStart === 0 && !value.startsWith("-")) {
+      // Add minus at the beginning if it doesn't exist
+      newValue = "-" + value;
+      selectionStart = 1;
+    } else if (
+      (selectionStart === 0 || selectionStart === 1) &&
+      value.startsWith("-")
+    ) {
+      // Remove minus if it exists
+      newValue = value.slice(1);
+      selectionStart = 0;
+    }
+
+    return { value: newValue, selectionStart };
+  }
 
   // Add the new key at the cursor's position
   if (selectionEnd > selectionStart) {
     // If there is a selection, replace it with the key
     newValue = value.slice(0, selectionStart) + key + value.slice(selectionEnd);
   } else {
-    // otherwise, append the key after the selection start
+    // Otherwise, insert the key at the cursor position
     newValue = value.slice(0, selectionStart) + key + value.slice(selectionStart);
   }
 
@@ -176,7 +198,6 @@ export const NumberComponent = React.memo((props: NumberComponentProps) => {
 
   const handleKeyDown = (event: React.KeyboardEvent<HTMLInputElement>) => {
     const { key, target } = event;
-    console.log(typeof key);
 
     // Typecast
     const inputTarget = target as HTMLInputElement;
@@ -202,17 +223,7 @@ export const NumberComponent = React.memo((props: NumberComponentProps) => {
       // Select everything when pressing Ctrl + a
       inputTarget.setSelectionRange(0, value.length);
       return;
-    } else if (key === "-") {
-      if (selectionStart === 0 && !value.startsWith("-")) {
-        newValue = "-" + value;
-        selectionStart++;
-      } else if (value.startsWith("-") && selectionStart === 1) {
-        newValue = value.substring(1); // remove minus sign
-        selectionStart--;
-      } else {
-        return; // Ignore "-" pressed in other positions
-      }
-    } else if (key >= "0" && key <= "9") {
+    } else if ((key >= "0" && key <= "9") || key === "-") {
       // Check if a number key or a decimal point key is pressed
       ({ value: newValue, selectionStart } = handleNumericKey(
         key,

frontend/src/components/SliderComponent.tsx

@@ -7,7 +7,7 @@ import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
 import { QuantityMap } from "../types/QuantityMap";
 import { propsAreEqual } from "../utils/propsAreEqual";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 interface SliderComponentProps {
   fullAccessPath: string;

frontend/src/components/StringComponent.tsx

@@ -4,7 +4,7 @@ import { DocStringComponent } from "./DocStringComponent";
 import "../App.css";
 import { LevelName } from "./NotificationsComponent";
 import { SerializedObject } from "../types/SerializedObject";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
 // TODO: add button functionality
 

frontend/src/components/TaskComponent.tsx

@@ -3,69 +3,53 @@ import { runMethod } from "../socket";
 import { Form, Button, InputGroup, Spinner } from "react-bootstrap";
 import { DocStringComponent } from "./DocStringComponent";
 import { LevelName } from "./NotificationsComponent";
-import { useRenderCount } from "../hooks/useRenderCount";
+import useRenderCount from "../hooks/useRenderCount";
 
-interface AsyncMethodProps {
+export type TaskStatus = "RUNNING" | "NOT_RUNNING";
+
+interface TaskProps {
   fullAccessPath: string;
-  value: "RUNNING" | null;
   docString: string | null;
-  hideOutput?: boolean;
+  status: TaskStatus;
   addNotification: (message: string, levelname?: LevelName) => void;
   displayName: string;
   id: string;
-  render: boolean;
 }
 
-export const AsyncMethodComponent = React.memo((props: AsyncMethodProps) => {
-  const {
-    fullAccessPath,
-    docString,
-    value: runningTask,
-    addNotification,
-    displayName,
-    id,
-  } = props;
-
-  // Conditional rendering based on the 'render' prop.
-  if (!props.render) {
-    return null;
-  }
+export const TaskComponent = React.memo((props: TaskProps) => {
+  const { fullAccessPath, docString, status, addNotification, displayName, id } = props;
 
   const renderCount = useRenderCount();
   const formRef = useRef(null);
   const [spinning, setSpinning] = useState(false);
-  const name = fullAccessPath.split(".").at(-1)!;
-  const parentPath = fullAccessPath.slice(0, -(name.length + 1));
 
   useEffect(() => {
     let message: string;
 
-    if (runningTask === null) {
-      message = `${fullAccessPath} task was stopped.`;
-    } else {
+    if (status === "RUNNING") {
       message = `${fullAccessPath} was started.`;
+    } else {
+      message = `${fullAccessPath} was stopped.`;
     }
+
     addNotification(message);
     setSpinning(false);
-  }, [props.value]);
+  }, [status]);
 
   const execute = async (event: React.FormEvent) => {
     event.preventDefault();
-    let method_name: string;
 
-    if (runningTask !== undefined && runningTask !== null) {
-      method_name = `stop_${name}`;
-    } else {
-      method_name = `start_${name}`;
-    }
+    const method_name = status == "RUNNING" ? "stop" : "start";
 
-    const accessPath = [parentPath, method_name].filter((element) => element).join(".");
+    const accessPath = [fullAccessPath, method_name]
+      .filter((element) => element)
+      .join(".");
     setSpinning(true);
     runMethod(accessPath);
   };
 
   return (
-    <div className="component asyncMethodComponent" id={id}>
+    <div className="component taskComponent" id={id}>
       {process.env.NODE_ENV === "development" && <div>Render count: {renderCount}</div>}
       <Form onSubmit={execute} ref={formRef}>
         <InputGroup>
@@ -76,7 +60,7 @@ export const AsyncMethodComponent = React.memo((props: AsyncMethodProps) => {
           <Button id={`button-${id}`} type="submit">
             {spinning ? (
               <Spinner size="sm" role="status" aria-hidden="true" />
-            ) : runningTask === "RUNNING" ? (
+            ) : status === "RUNNING" ? (
               "Stop "
             ) : (
               "Start "
@@ -88,4 +72,4 @@ export const AsyncMethodComponent = React.memo((props: AsyncMethodProps) => {
   );
 });
 
-AsyncMethodComponent.displayName = "AsyncMethodComponent";
+TaskComponent.displayName = "TaskComponent";

frontend/src/hooks/useLocalStorage.ts

@@ -0,0 +1,18 @@
+import { useState, useEffect } from "react";
+
+export default function useLocalStorage(key: string, defaultValue: unknown) {
+  const [value, setValue] = useState(() => {
+    const storedValue = localStorage.getItem(key);
+    if (storedValue) {
+      return JSON.parse(storedValue);
+    }
+    return defaultValue;
+  });
+
+  useEffect(() => {
+    if (value === undefined) return;
+    localStorage.setItem(key, JSON.stringify(value));
+  }, [value, key]);
+
+  return [value, setValue];
+}

frontend/src/hooks/useRenderCount.ts

@@ -1,6 +1,6 @@
 import { useRef, useEffect } from "react";
 
-export function useRenderCount() {
+export default function useRenderCount() {
   const count = useRef(0);
 
   useEffect(() => {

frontend/src/hooks/useSortedEntries.ts

@@ -0,0 +1,28 @@
+import { useContext } from "react";
+import { WebSettingsContext } from "../WebSettings";
+import { SerializedObject } from "../types/SerializedObject";
+
+export default function useSortedEntries(
+  props: Record<string, SerializedObject> | SerializedObject[],
+) {
+  const webSettings = useContext(WebSettingsContext);
+
+  // Get the order for sorting
+  const getOrder = (fullAccessPath: string) => {
+    return webSettings[fullAccessPath]?.displayOrder ?? Number.MAX_SAFE_INTEGER;
+  };
+
+  // Sort entries based on whether props is an array or an object
+  let sortedEntries;
+  if (Array.isArray(props)) {
+    // Need to make copy of array to leave the original array unmodified
+    sortedEntries = [...props].sort((objectA, objectB) => {
+      return getOrder(objectA.full_access_path) - getOrder(objectB.full_access_path);
+    });
+  } else {
+    sortedEntries = Object.values(props).sort((objectA, objectB) => {
+      return getOrder(objectA.full_access_path) - getOrder(objectB.full_access_path);
+    });
+  }
+  return sortedEntries;
+}

frontend/src/types/SerializedObject.ts

@@ -77,7 +77,12 @@ type SerializedException = SerializedObjectBase & {
   type: "Exception";
 };
 
-type DataServiceTypes = "DataService" | "Image" | "NumberSlider" | "DeviceConnection";
+type DataServiceTypes =
+  | "DataService"
+  | "Image"
+  | "NumberSlider"
+  | "DeviceConnection"
+  | "Task";
 
 type SerializedDataService = SerializedObjectBase & {
   name: string;

mkdocs.yml

@@ -4,8 +4,13 @@ edit_uri: blob/docs/docs/
 nav:
   - Home: index.md
   - Getting Started: getting-started.md
-  - User Guide: 
+  - User Guide:
     - Components Guide: user-guide/Components.md
+    - Interacting with pydase Services: user-guide/interaction/README.md
+    - Achieving Service Persistence: user-guide/Service_Persistence.md
+    - Understanding Tasks: user-guide/Tasks.md
+    - Understanding Units: user-guide/Understanding-Units.md
+    - Validating Property Setters: user-guide/Validating-Property-Setters.md
   - Developer Guide: 
     - Developer Guide: dev-guide/README.md
     - API Reference: dev-guide/api.md
@@ -16,7 +21,10 @@ nav:
     - Contributing: about/contributing.md
     - License: about/license.md
 
-theme: readthedocs
+theme: 
+  name: material
+  features:
+    - content.code.copy
 
 extra_css:
   - css/extra.css
@@ -26,17 +34,45 @@ markdown_extensions:
   - toc:
       permalink: true
   - pymdownx.highlight:
+      use_pygments: true
       anchor_linenums: true
+      line_spans: __span
+      pygments_lang_class: true
   - pymdownx.snippets
   - pymdownx.superfences
-  # - pymdownx.highlight:
-  # - pymdownx.inlinehilite
+  - pymdownx.inlinehilite
 
 
 plugins:
-  - include-markdown
-  - search
-  - mkdocstrings
+- include-markdown
+- search
+- mkdocstrings:
+    handlers:
+      python:
+        paths: [src]  # search packages in the src folder
+        import:
+          - https://docs.python.org/3/objects.inv
+          - https://docs.pydantic.dev/latest/objects.inv
+          - https://confz.readthedocs.io/en/latest/objects.inv
+        options:
+          show_source: true
+          inherited_members: true
+          merge_init_into_class: true
+          show_signature_annotations: true
+          signature_crossrefs: true
+          separate_signature: true
+          docstring_options:
+            ignore_init_summary: true
+          # docstring_section_style: list
+          heading_level: 2
+          parameter_headings: true
+          show_root_heading: true
+          show_root_full_path: true
+          show_symbol_type_heading: true
+          show_symbol_type_toc: true
+          # summary: true
+          unwrap_annotated: true
+- swagger-ui-tag
 
 watch:
   - src/pydase

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pydase"
-version = "0.8.4"
+version = "0.10.5"
 description = "A flexible and robust Python library for creating, managing, and interacting with data services, with built-in support for web and RPC servers, and customizable features for diverse use cases."
 authors = ["Mose Mueller <mosmuell@ethz.ch>"]
 readme = "README.md"
@@ -9,14 +9,14 @@ packages = [{ include = "pydase", from = "src" }]
 
 [tool.poetry.dependencies]
 python = "^3.10"
-fastapi = "^0.108.0"
-uvicorn = "^0.27.0"
 toml = "^0.10.2"
 python-socketio = "^5.8.0"
 confz = "^2.0.0"
 pint = "^0.24"
 websocket-client = "^1.7.0"
 aiohttp = "^3.9.3"
+click = "^8.1.7"
+aiohttp-middlewares = "^2.3.0"
 
 [tool.poetry.group.dev]
 optional = true
@@ -29,17 +29,18 @@ mypy = "^1.4.1"
 matplotlib = "^3.7.2"
 pyright = "^1.1.323"
 pytest-mock = "^3.11.1"
-ruff = "^0.2.0"
+ruff = "^0.5.0"
 pytest-asyncio = "^0.23.2"
 
 [tool.poetry.group.docs]
 optional = true
 
 [tool.poetry.group.docs.dependencies]
-mkdocs = "^1.5.2"
+mkdocs-material = "^9.5.30"
 mkdocs-include-markdown-plugin = "^3.9.1"
-mkdocstrings = "^0.22.0"
+mkdocstrings = {extras = ["python"], version = "^0.25.2"}
 pymdown-extensions = "^10.1"
+mkdocs-swagger-ui-tag = "^0.6.10"
 
 [build-system]
 requires = ["poetry-core"]

src/pydase/client/client.py

@@ -1,5 +1,6 @@
 import asyncio
 import logging
+import sys
 import threading
 from typing import TypedDict, cast
 
@@ -10,6 +11,12 @@ from pydase.client.proxy_loader import ProxyClassMixin, ProxyLoader
 from pydase.utils.serialization.deserializer import loads
 from pydase.utils.serialization.types import SerializedDataService, SerializedObject
 
+if sys.version_info < (3, 11):
+    from typing_extensions import Self
+else:
+    from typing import Self
+
+
 logger = logging.getLogger(__name__)
 
 
@@ -33,10 +40,10 @@ class ProxyClass(ProxyClassMixin, pydase.components.DeviceConnection):
     via a socket.io client in an asyncio environment.
 
     Args:
-        sio_client (socketio.AsyncClient):
+        sio_client:
             The socket.io client instance used for asynchronous communication with the
             pydase service server.
-        loop (asyncio.AbstractEventLoop):
+        loop:
             The event loop in which the client operations are managed and executed.
 
     This class is used to create a proxy object that behaves like a local representation
@@ -44,26 +51,27 @@ class ProxyClass(ProxyClassMixin, pydase.components.DeviceConnection):
     while actually communicating over network protocols.
     It can also be used as an attribute of a pydase service itself, e.g.
 
-        ```python
-        import pydase
+    ```python
+    import pydase
 
 
-        class MyService(pydase.DataService):
-            proxy = pydase.Client(
-                hostname="...", port=8001, block_until_connected=False
-            ).proxy
+    class MyService(pydase.DataService):
+        proxy = pydase.Client(
+            hostname="...", port=8001, block_until_connected=False
+        ).proxy
 
 
-        if __name__ == "__main__":
-            service = MyService()
-            server = pydase.Server(service, web_port=8002).run()
-        ```
+    if __name__ == "__main__":
+        service = MyService()
+        server = pydase.Server(service, web_port=8002).run()
+    ```
     """
 
     def __init__(
         self, sio_client: socketio.AsyncClient, loop: asyncio.AbstractEventLoop
     ) -> None:
         super().__init__()
+        pydase.components.DeviceConnection.__init__(self)
         self._initialise(sio_client=sio_client, loop=loop)
 
 
@@ -74,19 +82,16 @@ class Client:
     connection, disconnection, and updates, and ensures that the proxy object is
     up-to-date with the server state.
 
-    Attributes:
-        proxy (ProxyClass):
-            A proxy object representing the remote service, facilitating interaction as
-            if it were local.
-
     Args:
-        hostname (str):
-            Hostname of the exposed service this client attempts to connect to.
-            Default is "localhost".
-        port (int):
-            Port of the exposed service this client attempts to connect on.
-            Default is 8001.
-        block_until_connected (bool):
+        url:
+            The URL of the pydase Socket.IO server. This should always contain the
+            protocol and the hostname.
+
+            Examples:
+
+            - `wss://my-service.example.com`  # for secure connections, use wss
+            - `ws://localhost:8001`
+        block_until_connected:
             If set to True, the constructor will block until the connection to the
             service has been established. This is useful for ensuring the client is
             ready to use immediately after instantiation. Default is True.
@@ -94,42 +99,62 @@ class Client:
 
     def __init__(
         self,
-        hostname: str,
-        port: int,
+        *,
+        url: str,
         block_until_connected: bool = True,
     ):
-        self._hostname = hostname
-        self._port = port
+        self._url = url
         self._sio = socketio.AsyncClient()
         self._loop = asyncio.new_event_loop()
         self.proxy = ProxyClass(sio_client=self._sio, loop=self._loop)
+        """A proxy object representing the remote service, facilitating interaction as
+        if it were local."""
         self._thread = threading.Thread(
             target=asyncio_loop_thread, args=(self._loop,), daemon=True
         )
         self._thread.start()
+        self.connect(block_until_connected=block_until_connected)
+
+    def __enter__(self) -> Self:
+        self.connect(block_until_connected=True)
+        return self
+
+    def __del__(self) -> None:
+        self.disconnect()
+
+    def connect(self, block_until_connected: bool = True) -> None:
         connection_future = asyncio.run_coroutine_threadsafe(
             self._connect(), self._loop
         )
         if block_until_connected:
             connection_future.result()
 
+    def disconnect(self) -> None:
+        connection_future = asyncio.run_coroutine_threadsafe(
+            self._disconnect(), self._loop
+        )
+        connection_future.result()
+
     async def _connect(self) -> None:
-        logger.debug("Connecting to server '%s:%s' ...", self._hostname, self._port)
+        logger.debug("Connecting to server '%s' ...", self._url)
         await self._setup_events()
         await self._sio.connect(
-            f"ws://{self._hostname}:{self._port}",
+            self._url,
             socketio_path="/ws/socket.io",
             transports=["websocket"],
             retry=True,
         )
 
+    async def _disconnect(self) -> None:
+        await self._sio.disconnect()
+
     async def _setup_events(self) -> None:
         self._sio.on("connect", self._handle_connect)
         self._sio.on("disconnect", self._handle_disconnect)
         self._sio.on("notify", self._handle_update)
 
     async def _handle_connect(self) -> None:
-        logger.debug("Connected to '%s:%s' ...", self._hostname, self._port)
+        logger.debug("Connected to '%s' ...", self._url)
         serialized_object = cast(
             SerializedDataService, await self._sio.call("service_serialization")
         )
@@ -141,7 +166,7 @@ class Client:
         self.proxy._connected = True
 
     async def _handle_disconnect(self) -> None:
-        logger.debug("Disconnected from '%s:%s' ...", self._hostname, self._port)
+        logger.debug("Disconnected from '%s' ...", self._url)
         self.proxy._connected = False
 
     async def _handle_update(self, data: NotifyDict) -> None:

src/pydase/client/proxy_loader.py

@@ -351,7 +351,7 @@ class ProxyLoader:
     ) -> Any:
         # Custom types like Components or DataService classes
         component_class = cast(
-            type, Deserializer.get_component_class(serialized_object["type"])
+            type, Deserializer.get_service_base_class(serialized_object["type"])
         )
         class_bases = (
             ProxyClassMixin,

src/pydase/components/coloured_enum.py

@@ -7,58 +7,59 @@ class ColouredEnum(Enum):
 
     This class extends the standard Enum but requires its values to be valid CSS
     colour codes. Supported colour formats include:
-        - Hexadecimal colours
-        - Hexadecimal colours with transparency
-        - RGB colours
-        - RGBA colours
-        - HSL colours
-        - HSLA colours
-        - Predefined/Cross-browser colour names
+
+    - Hexadecimal colours
+    - Hexadecimal colours with transparency
+    - RGB colours
+    - RGBA colours
+    - HSL colours
+    - HSLA colours
+    - Predefined/Cross-browser colour names
+
     Refer to the this website for more details on colour formats:
     (https://www.w3schools.com/cssref/css_colours_legal.php)
 
     The behavior of this component in the UI depends on how it's defined in the data
     service:
-        - As property with a setter or as attribute: Renders as a dropdown menu,
-            allowing users to select and change its value from the frontend.
-        - As property without a setter: Displays as a coloured box with the key of the
-            `ColouredEnum` as text inside, serving as a visual indicator without user
-            interaction.
+
+    - As property with a setter or as attribute: Renders as a dropdown menu, allowing
+    users to select and change its value from the frontend.
+    - As property without a setter: Displays as a coloured box with the key of the
+    `ColouredEnum` as text inside, serving as a visual indicator without user
+    interaction.
 
     Example:
-    --------
-    ```python
-    import pydase.components as pyc
-    import pydase
+        ```python
+        import pydase.components as pyc
+        import pydase
 
-    class MyStatus(pyc.ColouredEnum):
-        PENDING = "#FFA500"  # Orange
-        RUNNING = "#0000FF80"  # Transparent Blue
-        PAUSED = "rgb(169, 169, 169)"  # Dark Gray
-        RETRYING = "rgba(255, 255, 0, 0.3)"  # Transparent Yellow
-        COMPLETED = "hsl(120, 100%, 50%)"  # Green
-        FAILED = "hsla(0, 100%, 50%, 0.7)"  # Transparent Red
-        CANCELLED = "SlateGray"  # Slate Gray
+        class MyStatus(pyc.ColouredEnum):
+            PENDING = "#FFA500"  # Orange
+            RUNNING = "#0000FF80"  # Transparent Blue
+            PAUSED = "rgb(169, 169, 169)"  # Dark Gray
+            RETRYING = "rgba(255, 255, 0, 0.3)"  # Transparent Yellow
+            COMPLETED = "hsl(120, 100%, 50%)"  # Green
+            FAILED = "hsla(0, 100%, 50%, 0.7)"  # Transparent Red
+            CANCELLED = "SlateGray"  # Slate Gray
 
-    class StatusExample(pydase.DataService):
-        _status = MyStatus.RUNNING
+        class StatusExample(pydase.DataService):
+            _status = MyStatus.RUNNING
 
-        @property
-        def status(self) -> MyStatus:
-            return self._status
+            @property
+            def status(self) -> MyStatus:
+                return self._status
 
-        @status.setter
-        def status(self, value: MyStatus) -> None:
-            # Custom logic here...
-            self._status = value
+            @status.setter
+            def status(self, value: MyStatus) -> None:
+                # Custom logic here...
+                self._status = value
 
-    # Example usage:
-    my_service = StatusExample()
-    my_service.status = MyStatus.FAILED
-    ```
+        # Example usage:
+        my_service = StatusExample()
+        my_service.status = MyStatus.FAILED
+        ```
 
-    Note
-    ----
-    Each enumeration name and value must be unique. This means that you should use
-    different colour formats when you want to use a colour multiple times.
+    Note:
+        Each enumeration name and value must be unique. This means that you should use
+        different colour formats when you want to use a colour multiple times.
     """

src/pydase/components/device_connection.py

@@ -1,6 +1,7 @@
 import asyncio
 
 import pydase.data_service
+import pydase.task.decorator
 
 
 class DeviceConnection(pydase.data_service.DataService):
@@ -19,22 +20,26 @@ class DeviceConnection(pydase.data_service.DataService):
     to the device. This method should update the `self._connected` attribute to reflect
     the connection status:
 
-    >>> class MyDeviceConnection(DeviceConnection):
-    ...     def connect(self) -> None:
-    ...         # Implementation to connect to the device
-    ...         # Update self._connected to `True` if connection is successful,
-    ...         # `False` otherwise
-    ...         ...
+    ```python
+    class MyDeviceConnection(DeviceConnection):
+        def connect(self) -> None:
+            # Implementation to connect to the device
+            # Update self._connected to `True` if connection is successful,
+            # `False` otherwise
+            ...
+    ```
 
     Optionally, if additional logic is needed to determine the connection status,
     the `connected` property can also be overridden:
 
-    >>> class MyDeviceConnection(DeviceConnection):
-    ...     @property
-    ...     def connected(self) -> bool:
-    ...         # Custom logic to determine connection status
-    ...         return some_custom_condition
-    ...
+    ```python
+    class MyDeviceConnection(DeviceConnection):
+        @property
+        def connected(self) -> bool:
+            # Custom logic to determine connection status
+            return some_custom_condition
+
+    ```
 
     Frontend Representation
     -----------------------
@@ -48,7 +53,6 @@ class DeviceConnection(pydase.data_service.DataService):
     def __init__(self) -> None:
         super().__init__()
         self._connected = False
-        self._autostart_tasks["_handle_connection"] = ()  # type: ignore
         self._reconnection_wait_time = 10.0
 
     def connect(self) -> None:
@@ -66,6 +70,7 @@ class DeviceConnection(pydase.data_service.DataService):
         """
         return self._connected
 
+    @pydase.task.decorator.task(autostart=True)
     async def _handle_connection(self) -> None:
         """Automatically tries reconnecting to the device if it is not connected.
         This method leverages the `connect` method and the `connected` property to

src/pydase/components/number_slider.py

@@ -11,76 +11,74 @@ class NumberSlider(DataService):
     This class models a UI slider for a data service, allowing for adjustments of a
     parameter within a specified range and increments.
 
-    Parameters:
-    -----------
-    value (float, optional):
-        The initial value of the slider. Defaults to 0.
-    min (float, optional):
-        The minimum value of the slider. Defaults to 0.
-    max (float, optional):
-        The maximum value of the slider. Defaults to 100.
-    step_size (float, optional):
-        The increment/decrement step size of the slider. Defaults to 1.0.
+    Args:
+        value:
+            The initial value of the slider. Defaults to 0.
+        min_:
+            The minimum value of the slider. Defaults to 0.
+        max_:
+            The maximum value of the slider. Defaults to 100.
+        step_size:
+            The increment/decrement step size of the slider. Defaults to 1.0.
 
     Example:
-    --------
-    ```python
-    class MySlider(pydase.components.NumberSlider):
-        def __init__(
-            self,
-            value: float = 0.0,
-            min_: float = 0.0,
-            max_: float = 100.0,
-            step_size: float = 1.0,
-        ) -> None:
-            super().__init__(value, min_, max_, step_size)
+        ```python
+        class MySlider(pydase.components.NumberSlider):
+            def __init__(
+                self,
+                value: float = 0.0,
+                min_: float = 0.0,
+                max_: float = 100.0,
+                step_size: float = 1.0,
+            ) -> None:
+                super().__init__(value, min_, max_, step_size)
 
-        @property
-        def min(self) -> float:
-            return self._min
+            @property
+            def min(self) -> float:
+                return self._min
 
-        @min.setter
-        def min(self, value: float) -> None:
-            self._min = value
+            @min.setter
+            def min(self, value: float) -> None:
+                self._min = value
 
-        @property
-        def max(self) -> float:
-            return self._max
+            @property
+            def max(self) -> float:
+                return self._max
 
-        @max.setter
-        def max(self, value: float) -> None:
-            self._max = value
+            @max.setter
+            def max(self, value: float) -> None:
+                self._max = value
 
-        @property
-        def step_size(self) -> float:
-            return self._step_size
+            @property
+            def step_size(self) -> float:
+                return self._step_size
 
-        @step_size.setter
-        def step_size(self, value: float) -> None:
-            self._step_size = value
+            @step_size.setter
+            def step_size(self, value: float) -> None:
+                self._step_size = value
 
-        @property
-        def value(self) -> float:
-            return self._value
+            @property
+            def value(self) -> float:
+                return self._value
 
-        @value.setter
-        def value(self, value: float) -> None:
-            if value < self._min or value > self._max:
-                raise ValueError(
-                    "Value is either below allowed min or above max value."
-                )
+            @value.setter
+            def value(self, value: float) -> None:
+                if value < self._min or value > self._max:
+                    raise ValueError(
+                        "Value is either below allowed min or above max value."
+                    )
 
-            self._value = value
+                self._value = value
 
-    class MyService(pydase.DataService):
-        def __init__(self) -> None:
-            self.voltage = MyService()
+        class MyService(pydase.DataService):
+            def __init__(self) -> None:
+                self.voltage = MyService()
 
-    # Modifying or accessing the voltage value:
-    my_service = MyService()
-    my_service.voltage.value = 5
-    print(my_service.voltage.value)  # Output: 5
-    ```
+        # Modifying or accessing the voltage value:
+        my_service = MyService()
+        my_service.voltage.value = 5
+        print(my_service.voltage.value)  # Output: 5
+        ```
     """
 
     def __init__(

src/pydase/config.py

@@ -5,19 +5,31 @@ from confz import BaseConfig, EnvSource
 
 
 class OperationMode(BaseConfig):  # type: ignore[misc]
-    environment: Literal["development", "production"] = "development"
+    environment: Literal["testing", "development", "production"] = "development"
+    """The service's operation mode."""
 
     CONFIG_SOURCES = EnvSource(allow=["ENVIRONMENT"])
 
 
 class ServiceConfig(BaseConfig):  # type: ignore[misc]
+    """Service configuration.
+
+    Variables can be set through environment variables prefixed with `SERVICE_` or an
+    `.env` file containing those variables.
+    """
+
     config_dir: Path = Path("config")
+    """Configuration directory"""
     web_port: int = 8001
+    """Web server port"""
 
     CONFIG_SOURCES = EnvSource(allow_all=True, prefix="SERVICE_", file=".env")
 
 
 class WebServerConfig(BaseConfig):  # type: ignore[misc]
+    """The service's web server configuration."""
+
     generate_web_settings: bool = False
+    """Should generate web_settings.json file"""
 
     CONFIG_SOURCES = EnvSource(allow=["GENERATE_WEB_SETTINGS"])

src/pydase/data_service/abstract_data_service.py

@@ -1,15 +1,7 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any
-
 from pydase.observer_pattern.observable.observable import Observable
 
-if TYPE_CHECKING:
-    from pydase.data_service.data_service import DataService
-    from pydase.data_service.task_manager import TaskManager
-
 
 class AbstractDataService(Observable):
-    __root__: DataService
-    _task_manager: TaskManager
-    _autostart_tasks: dict[str, tuple[Any]]
+    pass

src/pydase/data_service/data_service.py

@@ -5,12 +5,12 @@ from typing import Any
 
 import pydase.units as u
 from pydase.data_service.abstract_data_service import AbstractDataService
-from pydase.data_service.task_manager import TaskManager
 from pydase.observer_pattern.observable.observable import (
     Observable,
 )
 from pydase.utils.helpers import (
     get_class_and_instance_attributes,
+    is_descriptor,
     is_property_attribute,
 )
 from pydase.utils.serialization.serializer import (
@@ -24,11 +24,6 @@ logger = logging.getLogger(__name__)
 class DataService(AbstractDataService):
     def __init__(self) -> None:
         super().__init__()
-        self._task_manager = TaskManager(self)
-
-        if not hasattr(self, "_autostart_tasks"):
-            self._autostart_tasks = {}
-
         self.__check_instance_classes()
 
     def __setattr__(self, __name: str, __value: Any) -> None:
@@ -74,7 +69,7 @@ class DataService(AbstractDataService):
         if not issubclass(
             value_class,
             (int | float | bool | str | list | dict | Enum | u.Quantity | Observable),
-        ):
+        ) and not is_descriptor(__value):
             logger.warning(
                 "Class '%s' does not inherit from DataService. This may lead to"
                 " unexpected behaviour!",

src/pydase/data_service/data_service_cache.py

@@ -2,8 +2,6 @@ import logging
 from typing import TYPE_CHECKING, Any, cast
 
 from pydase.utils.serialization.serializer import (
-    SerializationPathError,
-    SerializationValueError,
     SerializedObject,
     get_nested_dict_by_path,
     set_nested_value_by_path,
@@ -38,16 +36,7 @@ class DataServiceCache:
         )
 
     def get_value_dict_from_cache(self, full_access_path: str) -> SerializedObject:
-        try:
-            return get_nested_dict_by_path(
-                cast(dict[str, SerializedObject], self._cache["value"]),
-                full_access_path,
-            )
-        except (SerializationPathError, SerializationValueError, KeyError):
-            return {
-                "full_access_path": full_access_path,
-                "value": None,
-                "type": "None",
-                "doc": None,
-                "readonly": False,
-            }
+        return get_nested_dict_by_path(
+            cast(dict[str, SerializedObject], self._cache["value"]),
+            full_access_path,
+        )

src/pydase/data_service/data_service_observer.py

@@ -8,8 +8,15 @@ from pydase.observer_pattern.observable.observable_object import ObservableObjec
 from pydase.observer_pattern.observer.property_observer import (
     PropertyObserver,
 )
-from pydase.utils.helpers import get_object_attr_from_path
-from pydase.utils.serialization.serializer import SerializedObject, dump
+from pydase.utils.helpers import (
+    get_object_attr_from_path,
+    normalize_full_access_path_string,
+)
+from pydase.utils.serialization.serializer import (
+    SerializationPathError,
+    SerializedObject,
+    dump,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -29,12 +36,22 @@ class DataServiceObserver(PropertyObserver):
             for changing_attribute in self.changing_attributes
         ):
             return
+        cached_value_dict: SerializedObject
 
-        cached_value_dict = deepcopy(
-            self.state_manager._data_service_cache.get_value_dict_from_cache(
-                full_access_path
+        try:
+            cached_value_dict = deepcopy(
+                self.state_manager.cache_manager.get_value_dict_from_cache(
+                    full_access_path
+                )
             )
-        )
+        except (SerializationPathError, KeyError):
+            cached_value_dict = {
+                "full_access_path": full_access_path,
+                "value": None,
+                "type": "None",
+                "doc": None,
+                "readonly": False,
+            }
 
         cached_value = cached_value_dict.get("value")
         if (
@@ -46,7 +63,7 @@ class DataServiceObserver(PropertyObserver):
             self._update_cache_value(full_access_path, value, cached_value_dict)
 
             cached_value_dict = deepcopy(
-                self.state_manager._data_service_cache.get_value_dict_from_cache(
+                self.state_manager.cache_manager.get_value_dict_from_cache(
                     full_access_path
                 )
             )
@@ -79,13 +96,14 @@ class DataServiceObserver(PropertyObserver):
                 value_dict["type"],
                 cached_value_dict["type"],
             )
-        self.state_manager._data_service_cache.update_cache(
+        self.state_manager.cache_manager.update_cache(
             full_access_path,
             value,
         )
 
     def _notify_dependent_property_changes(self, changed_attr_path: str) -> None:
-        changed_props = self.property_deps_dict.get(changed_attr_path, [])
+        normalized_attr_path = normalize_full_access_path_string(changed_attr_path)
+        changed_props = self.property_deps_dict.get(normalized_attr_path, [])
         for prop in changed_props:
             # only notify about changing attribute if it is not currently being
             # "changed" e.g. when calling the getter of a property within another
@@ -110,8 +128,10 @@ class DataServiceObserver(PropertyObserver):
         object.
 
         Args:
-            callback (Callable[[str, Any, dict[str, Any]]): The callback function to be
-            registered. The function should have the following signature:
+            callback:
+                The callback function to be registered. The function should have the
+                following signature:
+
                 - full_access_path (str): The full dot-notation access path of the
                   changed attribute. This path indicates the location of the changed
                   attribute within the observable object's structure.

src/pydase/data_service/state_manager.py

@@ -1,3 +1,4 @@
+import contextlib
 import json
 import logging
 import os
@@ -32,17 +33,19 @@ def load_state(func: Callable[..., Any]) -> Callable[..., Any]:
     the value should be loaded from the JSON file.
 
     Example:
-    >>>     class Service(pydase.DataService):
-    ...         _name = "Service"
-    ...
-    ...         @property
-    ...         def name(self) -> str:
-    ...             return self._name
-    ...
-    ...         @name.setter
-    ...         @load_state
-    ...         def name(self, value: str) -> None:
-    ...             self._name = value
+        ```python
+        class Service(pydase.DataService):
+            _name = "Service"
+
+            @property
+            def name(self) -> str:
+                return self._name
+
+            @name.setter
+            @load_state
+            def name(self, value: str) -> None:
+                self._name = value
+        ```
     """
 
     func._load_state = True  # type: ignore[attr-defined]
@@ -84,13 +87,11 @@ class StateManager:
     StateManager provides a snapshot of the DataService's state that is sufficiently
     accurate for initial rendering and interaction.
 
-    Attributes:
-        cache (dict[str, Any]):
-            A dictionary cache of the DataService's state.
-        filename (str):
-            The file name used for storing the DataService's state.
-        service (DataService):
+    Args:
+        service:
             The DataService instance whose state is being managed.
+        filename:
+            The file name used for storing the DataService's state.
 
     Note:
         The StateManager's cache updates are triggered by notifications and do not
@@ -113,19 +114,12 @@ class StateManager:
             self.filename = filename
 
         self.service = service
-        self._data_service_cache = DataServiceCache(self.service)
-
-    @property
-    def cache(self) -> SerializedObject:
-        """Returns the cached DataService state."""
-        return self._data_service_cache.cache
+        self.cache_manager = DataServiceCache(self.service)
 
     @property
     def cache_value(self) -> dict[str, SerializedObject]:
         """Returns the "value" value of the DataService serialization."""
-        return cast(
-            dict[str, SerializedObject], self._data_service_cache.cache["value"]
-        )
+        return cast(dict[str, SerializedObject], self.cache_manager.cache["value"])
 
     def save_state(self) -> None:
         """
@@ -157,9 +151,18 @@ class StateManager:
         for path in generate_serialized_data_paths(json_dict):
             if self.__is_loadable_state_attribute(path):
                 nested_json_dict = get_nested_dict_by_path(json_dict, path)
-                nested_class_dict = self._data_service_cache.get_value_dict_from_cache(
-                    path
-                )
+                try:
+                    nested_class_dict = self.cache_manager.get_value_dict_from_cache(
+                        path
+                    )
+                except (SerializationPathError, KeyError):
+                    nested_class_dict = {
+                        "full_access_path": path,
+                        "value": None,
+                        "type": "None",
+                        "doc": None,
+                        "readonly": False,
+                    }
 
                 value_type = nested_json_dict["type"]
                 class_attr_value_type = nested_class_dict.get("type", None)
@@ -197,17 +200,23 @@ class StateManager:
         It also handles type-specific conversions for the new value before setting it.
 
         Args:
-            path: A dot-separated string indicating the hierarchical path to the
+            path:
+                A dot-separated string indicating the hierarchical path to the
                 attribute.
-            value: The new value to set for the attribute.
+            serialized_value:
+                The serialized representation of the new value to set for the attribute.
         """
 
-        current_value_dict = get_nested_dict_by_path(self.cache_value, path)
-
-        # This will also filter out methods as they are 'read-only'
-        if current_value_dict["readonly"]:
-            logger.debug("Attribute '%s' is read-only. Ignoring new value...", path)
-            return
+        try:
+            current_value_dict = self.cache_manager.get_value_dict_from_cache(path)
+        except (SerializationPathError, KeyError):
+            current_value_dict = {
+                "full_access_path": path,
+                "value": None,
+                "type": "None",
+                "doc": None,
+                "readonly": False,
+            }
 
         if "full_access_path" not in serialized_value:
             # Backwards compatibility for JSON files not containing the
@@ -237,24 +246,21 @@ class StateManager:
     def __update_attribute_by_path(
         self, path: str, serialized_value: SerializedObject
     ) -> None:
+        is_value_set = False
         path_parts = parse_full_access_path(path)
         target_obj = get_object_by_path_parts(self.service, path_parts[:-1])
 
-        attr_cache_type = get_nested_dict_by_path(self.cache_value, path)["type"]
-
-        # De-serialize the value
-        if attr_cache_type in ("ColouredEnum", "Enum"):
+        if self.__cached_value_is_enum(path):
             enum_attr = get_object_by_path_parts(target_obj, [path_parts[-1]])
             # take the value of the existing enum class
             if serialized_value["type"] in ("ColouredEnum", "Enum"):
-                try:
+                # This error will arise when setting an enum from another enum class.
+                # In this case, we resort to loading the enum and setting it directly.
+                with contextlib.suppress(KeyError):
                     value = enum_attr.__class__[serialized_value["value"]]
-                except KeyError:
-                    # This error will arise when setting an enum from another enum class
-                    # In this case, we resort to loading the enum and setting it
-                    # directly
-                    value = loads(serialized_value)
-        else:
+                    is_value_set = True
+
+        if not is_value_set:
             value = loads(serialized_value)
 
         # set the value
@@ -262,6 +268,15 @@ class StateManager:
             processed_key = parse_serialized_key(path_parts[-1])
             target_obj[processed_key] = value  # type: ignore
         else:
+            # Don't allow adding attributes to objects through state manager
+            if self.__attr_exists_on_target_obj(
+                target_obj=target_obj, name=path_parts[-1]
+            ):
+                raise AttributeError(
+                    f"{target_obj.__class__.__name__!r} object has no attribute "
+                    f"{path_parts[-1]!r}"
+                )
+
             setattr(target_obj, path_parts[-1], value)
 
     def __is_loadable_state_attribute(self, full_access_path: str) -> bool:
@@ -287,8 +302,8 @@ class StateManager:
             return has_decorator
 
         try:
-            cached_serialization_dict = get_nested_dict_by_path(
-                self.cache_value, full_access_path
+            cached_serialization_dict = self.cache_manager.get_value_dict_from_cache(
+                full_access_path
             )
 
             if cached_serialization_dict["value"] == "method":
@@ -303,3 +318,16 @@ class StateManager:
                 path_parts[-1],
             )
             return False
+
+    def __cached_value_is_enum(self, path: str) -> bool:
+        try:
+            attr_cache_type = self.cache_manager.get_value_dict_from_cache(path)["type"]
+
+            return attr_cache_type in ("ColouredEnum", "Enum")
+        except Exception:
+            return False
+
+    def __attr_exists_on_target_obj(self, target_obj: Any, name: str) -> bool:
+        return not is_property_attribute(target_obj, name) and not hasattr(
+            target_obj, name
+        )

src/pydase/data_service/task_manager.py

@@ -1,225 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import inspect
-import logging
-from enum import Enum
-from typing import TYPE_CHECKING, Any
-
-from pydase.data_service.abstract_data_service import AbstractDataService
-from pydase.utils.helpers import (
-    function_has_arguments,
-    get_class_and_instance_attributes,
-    is_property_attribute,
-)
-
-if TYPE_CHECKING:
-    from collections.abc import Callable
-
-    from .data_service import DataService
-
-logger = logging.getLogger(__name__)
-
-
-class TaskStatus(Enum):
-    RUNNING = "running"
-
-
-class TaskManager:
-    """
-    The TaskManager class is a utility designed to manage asynchronous tasks. It
-    provides functionality for starting, stopping, and tracking these tasks. The class
-    is primarily used by the DataService class to manage its tasks.
-
-    A task in TaskManager is any asynchronous function. To add a task, you simply need
-    to define an async function within your class that extends TaskManager. For example:
-
-    ```python
-    class MyService(DataService):
-        async def my_task(self):
-            # Your task implementation here
-            pass
-    ```
-
-    With the above definition, TaskManager automatically creates `start_my_task` and
-    `stop_my_task` methods that can be used to control the task.
-
-    TaskManager also supports auto-starting tasks. If there are tasks that should start
-    running as soon as an instance of your class is created, you can define them in
-    `self._autostart_tasks` in your class constructor (__init__ method). Here's how:
-
-    ```python
-    class MyService(DataService):
-        def __init__(self):
-            self._autostart_tasks = {
-                "my_task": (*args)  # Replace with actual arguments
-            }
-            self.wait_time = 1
-            super().__init__()
-
-        async def my_task(self, *args):
-            while True:
-                # Your task implementation here
-                await asyncio.sleep(self.wait_time)
-    ```
-
-    In the above example, `my_task` will start running as soon as
-    `_start_autostart_tasks` is called which is done when the DataService instance is
-    passed to the `pydase.Server` class.
-
-    The responsibilities of the TaskManager class are:
-
-    - Track all running tasks: Keeps track of all the tasks that are currently running.
-    This allows for monitoring of task statuses and for making sure tasks do not
-    overlap.
-    - Provide the ability to start and stop tasks: Automatically creates methods to
-    start and stop each task.
-    - Emit notifications when the status of a task changes: Has a built-in mechanism for
-    emitting notifications when a task starts or stops. This is used to update the user
-    interfaces, but can also be used to write logs, etc.
-    """
-
-    def __init__(self, service: DataService) -> None:
-        self.service = service
-
-        self.tasks: dict[str, asyncio.Task[None]] = {}
-        """A dictionary to keep track of running tasks. The keys are the names of the
-        tasks and the values are TaskDict instances which include the task itself and
-        its kwargs.
-        """
-
-        self._set_start_and_stop_for_async_methods()
-
-    @property
-    def _loop(self) -> asyncio.AbstractEventLoop:
-        return asyncio.get_running_loop()
-
-    def _set_start_and_stop_for_async_methods(self) -> None:
-        for name in dir(self.service):
-            # circumvents calling properties
-            if is_property_attribute(self.service, name):
-                continue
-
-            method = getattr(self.service, name)
-            if inspect.iscoroutinefunction(method):
-                if function_has_arguments(method):
-                    logger.info(
-                        "Async function %a is defined with at least one argument. If "
-                        "you want to use it as a task, remove the argument(s) from the "
-                        "function definition.",
-                        method.__name__,
-                    )
-                    continue
-
-                # create start and stop methods for each coroutine
-                setattr(
-                    self.service, f"start_{name}", self._make_start_task(name, method)
-                )
-                setattr(self.service, f"stop_{name}", self._make_stop_task(name))
-
-    def _initiate_task_startup(self) -> None:
-        if self.service._autostart_tasks is not None:
-            for service_name, args in self.service._autostart_tasks.items():
-                start_method = getattr(self.service, f"start_{service_name}", None)
-                if start_method is not None and callable(start_method):
-                    start_method(*args)
-                else:
-                    logger.warning(
-                        "No start method found for service '%s'", service_name
-                    )
-
-    def start_autostart_tasks(self) -> None:
-        self._initiate_task_startup()
-        attrs = get_class_and_instance_attributes(self.service)
-
-        for attr_value in attrs.values():
-            if isinstance(attr_value, AbstractDataService):
-                attr_value._task_manager.start_autostart_tasks()
-            elif isinstance(attr_value, list):
-                for item in attr_value:
-                    if isinstance(item, AbstractDataService):
-                        item._task_manager.start_autostart_tasks()
-
-    def _make_stop_task(self, name: str) -> Callable[..., Any]:
-        """
-        Factory function to create a 'stop_task' function for a running task.
-
-        The generated function cancels the associated asyncio task using 'name' for
-        identification, ensuring proper cleanup. Avoids closure and late binding issues.
-
-        Args:
-            name (str): The name of the coroutine task, used for its identification.
-        """
-
-        def stop_task() -> None:
-            # cancel the task
-            task = self.tasks.get(name, None)
-            if task is not None:
-                self._loop.call_soon_threadsafe(task.cancel)
-
-        return stop_task
-
-    def _make_start_task(
-        self, name: str, method: Callable[..., Any]
-    ) -> Callable[..., Any]:
-        """
-        Factory function to create a 'start_task' function for a coroutine.
-
-        The generated function starts the coroutine as an asyncio task, handling
-        registration and monitoring.
-        It uses 'name' and 'method' to avoid the closure and late binding issue.
-
-        Args:
-            name (str): The name of the coroutine, used for task management.
-            method (callable): The coroutine to be turned into an asyncio task.
-        """
-
-        def start_task() -> None:
-            def task_done_callback(task: asyncio.Task[None], name: str) -> None:
-                """Handles tasks that have finished.
-
-                Removes a task from the tasks dictionary, calls the defined
-                callbacks, and logs and re-raises exceptions."""
-
-                # removing the finished task from the tasks i
-                self.tasks.pop(name, None)
-
-                # emit the notification that the task was stopped
-                self.service._notify_changed(name, None)
-
-                exception = task.exception()
-                if exception is not None:
-                    # Handle the exception, or you can re-raise it.
-                    logger.error(
-                        "Task '%s' encountered an exception: %s: %s",
-                        name,
-                        type(exception).__name__,
-                        exception,
-                    )
-                    raise exception
-
-            async def task() -> None:
-                try:
-                    await method()
-                except asyncio.CancelledError:
-                    logger.info("Task '%s' was cancelled", name)
-
-            if not self.tasks.get(name):
-                # creating the task and adding the task_done_callback which checks
-                # if an exception has occured during the task execution
-                task_object = self._loop.create_task(task())
-                task_object.add_done_callback(
-                    lambda task: task_done_callback(task, name)
-                )
-
-                # Store the task and its arguments in the '__tasks' dictionary. The
-                # key is the name of the method, and the value is a dictionary
-                # containing the task object and the updated keyword arguments.
-                self.tasks[name] = task_object
-
-                # emit the notification that the task was started
-                self.service._notify_changed(name, TaskStatus.RUNNING)
-            else:
-                logger.error("Task '%s' is already running!", name)
-
-        return start_task

src/pydase/frontend/index.html

@@ -6,7 +6,7 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <meta name="theme-color" content="#000000" />
     <meta name="description" content="Web site displaying a pydase UI." />
-  <script type="module" crossorigin src="/assets/index-C12UM6g5.js"></script>
+  <script type="module" crossorigin src="/assets/index-BjsjosWf.js"></script>
   <link rel="stylesheet" crossorigin href="/assets/index-D2aktF3W.css">
 </head>
 

src/pydase/observer_pattern/observable/decorators.py

@@ -17,10 +17,10 @@ def validate_set(
     getter and check against the desired value.
 
     Args:
-        timeout (float):
+        timeout:
             The maximum time (in seconds) to wait for the value to be within the
             precision boundary.
-        precision (float | None):
+        precision:
             The acceptable deviation from the desired value. If None, the value must be
             exact.
     """
@@ -44,13 +44,11 @@ def has_validate_set_decorator(prop: property) -> bool:
     Checks if a property setter has been decorated with the `validate_set` decorator.
 
     Args:
-        prop (property):
+        prop:
             The property to check.
 
     Returns:
-        bool:
-            True if the property setter has the `validate_set` decorator, False
-            otherwise.
+        True if the property setter has the `validate_set` decorator, False otherwise.
     """
 
     property_setter = prop.fset
@@ -68,11 +66,11 @@ def _validate_value_was_correctly_set(
     specified `precision` and time `timeout`.
 
     Args:
-        obj (Observable):
+        obj:
             The instance of the class containing the property.
-        name (str):
+        name:
             The name of the property to validate.
-        value (Any):
+        value:
             The desired value to check against.
 
     Raises:

src/pydase/observer_pattern/observable/observable.py

@@ -6,7 +6,7 @@ from pydase.observer_pattern.observable.decorators import (
     has_validate_set_decorator,
 )
 from pydase.observer_pattern.observable.observable_object import ObservableObject
-from pydase.utils.helpers import is_property_attribute
+from pydase.utils.helpers import is_descriptor, is_property_attribute
 
 logger = logging.getLogger(__name__)
 
@@ -22,7 +22,9 @@ class Observable(ObservableObject):
             - {"__annotations__"}
         }
         for name, value in class_attrs.items():
-            if isinstance(value, property) or callable(value):
+            if isinstance(value, property) or callable(value) or is_descriptor(value):
+                # Properties, methods and descriptors have to be stored as class
+                # attributes to work properly. So don't make it an instance attribute.
                 continue
             self.__dict__[name] = self._initialise_new_objects(name, value)
 

src/pydase/observer_pattern/observer/observer.py

@@ -24,8 +24,7 @@ class Observer(ABC):
         self.on_change_start(changing_attribute)
 
     @abstractmethod
-    def on_change(self, full_access_path: str, value: Any) -> None:
-        ...
+    def on_change(self, full_access_path: str, value: Any) -> None: ...
 
     def on_change_start(self, full_access_path: str) -> None:
         return

src/pydase/observer_pattern/observer/property_observer.py

@@ -5,6 +5,7 @@ from typing import Any
 
 from pydase.observer_pattern.observable.observable import Observable
 from pydase.observer_pattern.observer.observer import Observer
+from pydase.utils.helpers import is_descriptor
 
 logger = logging.getLogger(__name__)
 
@@ -60,18 +61,28 @@ class PropertyObserver(Observer):
     def _process_nested_observables_properties(
         self, obj: Observable, deps: dict[str, Any], prefix: str
     ) -> None:
-        for k, value in vars(obj).items():
+        for k, value in {**vars(type(obj)), **vars(obj)}.items():
+            actual_value = value
             prefix = (
                 f"{prefix}." if prefix != "" and not prefix.endswith(".") else prefix
             )
             parent_path = f"{prefix}{k}"
-            if isinstance(value, Observable):
+
+            # Get value from descriptor
+            if not isinstance(value, property) and is_descriptor(value):
+                actual_value = getattr(obj, k)
+
+            if isinstance(actual_value, Observable):
                 new_prefix = f"{parent_path}."
                 deps.update(
-                    self._get_properties_and_their_dependencies(value, new_prefix)
+                    self._get_properties_and_their_dependencies(
+                        actual_value, new_prefix
+                    )
                 )
             elif isinstance(value, list | dict):
-                self._process_collection_item_properties(value, deps, parent_path)
+                self._process_collection_item_properties(
+                    actual_value, deps, parent_path
+                )
 
     def _process_collection_item_properties(
         self,

src/pydase/server/server.py

@@ -2,18 +2,26 @@ import asyncio
 import logging
 import os
 import signal
+import sys
 import threading
 from pathlib import Path
 from types import FrameType
 from typing import Any, Protocol, TypedDict
 
-from uvicorn.server import HANDLED_SIGNALS
-
 from pydase import DataService
 from pydase.config import ServiceConfig
 from pydase.data_service.data_service_observer import DataServiceObserver
 from pydase.data_service.state_manager import StateManager
 from pydase.server.web_server import WebServer
+from pydase.task.autostart import autostart_service_tasks
+from pydase.utils.helpers import current_event_loop_exists
+
+HANDLED_SIGNALS = (
+    signal.SIGINT,  # Unix signal 2. Sent by Ctrl+C.
+    signal.SIGTERM,  # Unix signal 15. Sent by `kill <pid>`.
+)
+if sys.platform == "win32":  # pragma: py-not-win32
+    HANDLED_SIGNALS += (signal.SIGBREAK,)  # Windows signal 21. Sent by Ctrl+Break.
 
 logger = logging.getLogger(__name__)
 
@@ -29,18 +37,18 @@ class AdditionalServerProtocol(Protocol):
 
     Args:
         data_service_observer:
-          Observer for the DataService, handling state updates and communication to
-          connected clients through injected callbacks. Can be utilized to access the
-          service and state manager, and to add custom state-update callbacks.
+            Observer for the DataService, handling state updates and communication to
+            connected clients through injected callbacks. Can be utilized to access the
+            service and state manager, and to add custom state-update callbacks.
         host:
-          Hostname or IP address where the server is accessible. Commonly '0.0.0.0' to
-          bind to all network interfaces.
+            Hostname or IP address where the server is accessible. Commonly '0.0.0.0' to
+            bind to all network interfaces.
         port:
-          Port number on which the server listens. Typically in the range 1024-65535
-          (non-standard ports).
+            Port number on which the server listens. Typically in the range 1024-65535
+            (non-standard ports).
         **kwargs:
-          Any additional parameters required for initializing the server. These
-          parameters are specific to the server's implementation.
+            Any additional parameters required for initializing the server. These
+            parameters are specific to the server's implementation.
     """
 
     def __init__(
@@ -58,18 +66,17 @@ class AdditionalServerProtocol(Protocol):
 
 
 class AdditionalServer(TypedDict):
-    """
-    A TypedDict that represents the configuration for an additional server to be run
+    """A TypedDict that represents the configuration for an additional server to be run
     alongside the main server.
-
-    This class is used to specify the server type, the port on which the server should
-    run, and any additional keyword arguments that should be passed to the server when
-    it's instantiated.
     """
 
     server: type[AdditionalServerProtocol]
+    """Server adhering to the
+    [`AdditionalServerProtocol`][pydase.server.server.AdditionalServerProtocol]."""
     port: int
+    """Port on which the server should run."""
     kwargs: dict[str, Any]
+    """Additional keyword arguments that will be passed to the server's constructor """
 
 
 class Server:
@@ -77,29 +84,20 @@ class Server:
     The `Server` class provides a flexible server implementation for the `DataService`.
 
     Args:
-        service: DataService
+        service:
             The DataService instance that this server will manage.
-        host: str
-            The host address for the server. Default is '0.0.0.0', which means all
+        host:
+            The host address for the server. Defaults to `'0.0.0.0'`, which means all
             available network interfaces.
-        web_port: int
-            The port number for the web server. Default is
-            `pydase.config.ServiceConfig().web_port`.
-        enable_web: bool
-            Whether to enable the web server. Default is True.
-        filename: str | Path | None
+        web_port:
+            The port number for the web server. Defaults to
+            [`ServiceConfig().web_port`][pydase.config.ServiceConfig.web_port].
+        enable_web:
+            Whether to enable the web server.
+        filename:
             Filename of the file managing the service state persistence.
-            Defaults to None.
-        additional_servers : list[AdditionalServer]
-            A list of additional servers to run alongside the main server. Each entry in
-            the list should be a dictionary with the following structure:
-                - server: A class that adheres to the AdditionalServerProtocol. This
-                    class should have an `__init__` method that accepts the DataService
-                    instance, port, host, and optional keyword arguments, and a `serve`
-                    method that is a coroutine responsible for starting the server.
-                - port: The port on which the additional server will be running.
-                - kwargs: A dictionary containing additional keyword arguments that will
-                    be passed to the server's `__init__` method.
+        additional_servers:
+            A list of additional servers to run alongside the main server.
 
             Here's an example of how you might define an additional server:
 
@@ -139,8 +137,8 @@ class Server:
             )
             server.run()
             ```
-        **kwargs: Any
-          Additional keyword arguments.
+        **kwargs:
+            Additional keyword arguments.
     """
 
     def __init__(  # noqa: PLR0913
@@ -160,13 +158,18 @@ class Server:
         self._web_port = web_port
         self._enable_web = enable_web
         self._kwargs = kwargs
-        self._loop: asyncio.AbstractEventLoop
         self._additional_servers = additional_servers
         self.should_exit = False
         self.servers: dict[str, asyncio.Future[Any]] = {}
         self._state_manager = StateManager(self._service, filename)
         self._observer = DataServiceObserver(self._state_manager)
         self._state_manager.load_state()
+        autostart_service_tasks(self._service)
+        if not current_event_loop_exists():
+            self._loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(self._loop)
+        else:
+            self._loop = asyncio.get_event_loop()
 
     def run(self) -> None:
         """
@@ -174,7 +177,7 @@ class Server:
 
         This method should be called to start the server after it's been instantiated.
         """
-        asyncio.run(self.serve())
+        self._loop.run_until_complete(self.serve())
 
     async def serve(self) -> None:
         process_id = os.getpid()
@@ -190,10 +193,8 @@ class Server:
         logger.info("Finished server process [%s]", process_id)
 
     async def startup(self) -> None:
-        self._loop = asyncio.get_running_loop()
         self._loop.set_exception_handler(self.custom_exception_handler)
         self.install_signal_handlers()
-        self._service._task_manager.start_autostart_tasks()
 
         for server in self._additional_servers:
             addin_server = server["server"](
@@ -207,8 +208,9 @@ class Server:
                 addin_server.__module__ + "." + addin_server.__class__.__name__
             )
 
-            future_or_task = self._loop.create_task(addin_server.serve())
-            self.servers[server_name] = future_or_task
+            server_task = self._loop.create_task(addin_server.serve())
+            server_task.add_done_callback(self._handle_server_shutdown)
+            self.servers[server_name] = server_task
         if self._enable_web:
             self._web_server = WebServer(
                 data_service_observer=self._observer,
@@ -216,8 +218,22 @@ class Server:
                 port=self._web_port,
                 **self._kwargs,
             )
-            future_or_task = self._loop.create_task(self._web_server.serve())
-            self.servers["web"] = future_or_task
+            server_task = self._loop.create_task(self._web_server.serve())
+
+            server_task.add_done_callback(self._handle_server_shutdown)
+            self.servers["web"] = server_task
+
+    def _handle_server_shutdown(self, task: asyncio.Task[Any]) -> None:
+        """Handle server shutdown. If the service should exit, do nothing. Else, make
+        the service exit."""
+
+        if self.should_exit:
+            return
+
+        try:
+            task.result()
+        except Exception:
+            self.should_exit = True
 
     async def main_loop(self) -> None:
         while not self.should_exit:
@@ -229,7 +245,9 @@ class Server:
         logger.info("Saving data to %s.", self._state_manager.filename)
         self._state_manager.save_state()
 
+        logger.debug("Cancelling servers")
         await self.__cancel_servers()
+        logger.debug("Cancelling tasks")
         await self.__cancel_tasks()
 
     async def __cancel_servers(self) -> None:
@@ -240,7 +258,7 @@ class Server:
             except asyncio.CancelledError:
                 logger.debug("Cancelled '%s' server.", server_name)
             except Exception as e:
-                logger.warning("Unexpected exception: %s", e)
+                logger.error("Unexpected exception: %s", e)
 
     async def __cancel_tasks(self) -> None:
         for task in asyncio.all_tasks(self._loop):

src/pydase/server/web_server/api/__init__.py

@@ -0,0 +1,24 @@
+import logging
+
+import aiohttp.web
+import aiohttp_middlewares.error
+
+import pydase.server.web_server.api.v1.application
+from pydase.data_service.state_manager import StateManager
+
+logger = logging.getLogger(__name__)
+
+
+def create_api_application(state_manager: StateManager) -> aiohttp.web.Application:
+    api_application = aiohttp.web.Application(
+        middlewares=(aiohttp_middlewares.error.error_middleware(),)
+    )
+
+    api_application.add_subapp(
+        "/v1/",
+        pydase.server.web_server.api.v1.application.create_api_application(
+            state_manager
+        ),
+    )
+
+    return api_application

src/pydase/server/web_server/api/v1/application.py

@@ -0,0 +1,70 @@
+import logging
+from typing import TYPE_CHECKING
+
+import aiohttp.web
+import aiohttp_middlewares.error
+
+from pydase.data_service.state_manager import StateManager
+from pydase.server.web_server.api.v1.endpoints import (
+    get_value,
+    trigger_method,
+    update_value,
+)
+from pydase.utils.serialization.serializer import dump
+
+if TYPE_CHECKING:
+    from pydase.server.web_server.sio_setup import TriggerMethodDict, UpdateDict
+
+logger = logging.getLogger(__name__)
+
+API_VERSION = "v1"
+
+STATUS_OK = 200
+STATUS_FAILED = 400
+
+
+def create_api_application(state_manager: StateManager) -> aiohttp.web.Application:
+    api_application = aiohttp.web.Application(
+        middlewares=(aiohttp_middlewares.error.error_middleware(),)
+    )
+
+    async def _get_value(request: aiohttp.web.Request) -> aiohttp.web.Response:
+        logger.info("Handle api request: %s", request)
+
+        access_path = request.rel_url.query["access_path"]
+
+        status = STATUS_OK
+        try:
+            result = get_value(state_manager, access_path)
+        except Exception as e:
+            logger.exception(e)
+            result = dump(e)
+            status = STATUS_FAILED
+        return aiohttp.web.json_response(result, status=status)
+
+    async def _update_value(request: aiohttp.web.Request) -> aiohttp.web.Response:
+        data: UpdateDict = await request.json()
+
+        try:
+            update_value(state_manager, data)
+
+            return aiohttp.web.json_response()
+        except Exception as e:
+            logger.exception(e)
+            return aiohttp.web.json_response(dump(e), status=STATUS_FAILED)
+
+    async def _trigger_method(request: aiohttp.web.Request) -> aiohttp.web.Response:
+        data: TriggerMethodDict = await request.json()
+
+        try:
+            return aiohttp.web.json_response(trigger_method(state_manager, data))
+
+        except Exception as e:
+            logger.exception(e)
+            return aiohttp.web.json_response(dump(e), status=STATUS_FAILED)
+
+    api_application.router.add_get("/get_value", _get_value)
+    api_application.router.add_put("/update_value", _update_value)
+    api_application.router.add_put("/trigger_method", _trigger_method)
+
+    return api_application

src/pydase/server/web_server/api/v1/endpoints.py

@@ -0,0 +1,38 @@
+from typing import Any
+
+import pydase.utils.serialization.deserializer
+import pydase.utils.serialization.serializer
+from pydase.data_service.state_manager import StateManager
+from pydase.server.web_server.sio_setup import TriggerMethodDict, UpdateDict
+from pydase.utils.helpers import get_object_attr_from_path
+from pydase.utils.serialization.types import SerializedObject
+
+loads = pydase.utils.serialization.deserializer.loads
+Serializer = pydase.utils.serialization.serializer.Serializer
+
+
+def update_value(state_manager: StateManager, data: UpdateDict) -> None:
+    path = data["access_path"]
+
+    state_manager.set_service_attribute_value_by_path(
+        path=path, serialized_value=data["value"]
+    )
+
+
+def get_value(state_manager: StateManager, access_path: str) -> SerializedObject:
+    return Serializer.serialize_object(
+        get_object_attr_from_path(state_manager.service, access_path),
+        access_path=access_path,
+    )
+
+
+def trigger_method(state_manager: StateManager, data: TriggerMethodDict) -> Any:
+    method = get_object_attr_from_path(state_manager.service, data["access_path"])
+
+    serialized_args = data.get("args", None)
+    args = loads(serialized_args) if serialized_args else []
+
+    serialized_kwargs = data.get("kwargs", None)
+    kwargs: dict[str, Any] = loads(serialized_kwargs) if serialized_kwargs else {}
+
+    return Serializer.serialize_object(method(*args, **kwargs))

src/pydase/server/web_server/sio_setup.py

@@ -1,19 +1,30 @@
 import asyncio
 import logging
+import sys
 from typing import Any, TypedDict
 
+if sys.version_info < (3, 11):
+    from typing_extensions import NotRequired
+else:
+    from typing import NotRequired
+
 import click
 import socketio  # type: ignore[import-untyped]
 
+import pydase.server.web_server.api.v1.endpoints
+import pydase.utils.serialization.deserializer
+import pydase.utils.serialization.serializer
 from pydase.data_service.data_service_observer import DataServiceObserver
 from pydase.data_service.state_manager import StateManager
-from pydase.utils.helpers import get_object_attr_from_path
 from pydase.utils.logging import SocketIOHandler
-from pydase.utils.serialization.deserializer import Deserializer
-from pydase.utils.serialization.serializer import SerializedObject, dump
+from pydase.utils.serialization.serializer import SerializedObject
 
 logger = logging.getLogger(__name__)
 
+# These functions can be monkey-patched by other libraries at runtime
+dump = pydase.utils.serialization.serializer.dump
+sio_client_manager = None
+
 
 class UpdateDict(TypedDict):
     """
@@ -34,8 +45,8 @@ class UpdateDict(TypedDict):
 
 class TriggerMethodDict(TypedDict):
     access_path: str
-    args: SerializedObject
-    kwargs: SerializedObject
+    args: NotRequired[SerializedObject]
+    kwargs: NotRequired[SerializedObject]
 
 
 class RunMethodDict(TypedDict):
@@ -44,12 +55,15 @@ class RunMethodDict(TypedDict):
     exposed DataService.
 
     Attributes:
-        name (str): The name of the method to be run.
-        parent_path (str): The access path for the parent object of the method to be
-            run. This is used to construct the full access path for the method. For
-            example, for an method with access path 'attr1.list_attr[0].method_name',
-            'attr1.list_attr[0]' would be the parent_path.
-        kwargs (dict[str, Any]): The arguments passed to the method.
+        name:
+            The name of the method to be run.
+        parent_path:
+            The access path for the parent object of the method to be run. This is used
+            to construct the full access path for the method. For example, for an method
+            with access path 'attr1.list_attr[0].method_name', 'attr1.list_attr[0]'
+            would be the parent_path.
+        kwargs:
+            The arguments passed to the method.
     """
 
     name: str
@@ -66,23 +80,30 @@ def setup_sio_server(
     Sets up and configures a Socket.IO asynchronous server.
 
     Args:
-        observer (DataServiceObserver):
-          The observer managing state updates and communication.
-        enable_cors (bool):
-          Flag indicating whether CORS should be enabled for the server.
-        loop (asyncio.AbstractEventLoop):
-          The event loop in which the server will run.
+        observer:
+            The observer managing state updates and communication.
+        enable_cors:
+            Flag indicating whether CORS should be enabled for the server.
+        loop:
+            The event loop in which the server will run.
 
     Returns:
-        socketio.AsyncServer: The configured Socket.IO asynchronous server.
+        The configured Socket.IO asynchronous server.
     """
 
     state_manager = observer.state_manager
 
     if enable_cors:
-        sio = socketio.AsyncServer(async_mode="asgi", cors_allowed_origins="*")
+        sio = socketio.AsyncServer(
+            async_mode="aiohttp",
+            cors_allowed_origins="*",
+            client_manager=sio_client_manager,
+        )
     else:
-        sio = socketio.AsyncServer(async_mode="asgi")
+        sio = socketio.AsyncServer(
+            async_mode="aiohttp",
+            client_manager=sio_client_manager,
+        )
 
     setup_sio_events(sio, state_manager)
     setup_logging_handler(sio)
@@ -117,37 +138,36 @@ def setup_sio_server(
 def setup_sio_events(sio: socketio.AsyncServer, state_manager: StateManager) -> None:  # noqa: C901
     @sio.event  # type: ignore
     async def connect(sid: str, environ: Any) -> None:
-        logging.debug("Client [%s] connected", click.style(str(sid), fg="cyan"))
+        logger.debug("Client [%s] connected", click.style(str(sid), fg="cyan"))
 
     @sio.event  # type: ignore
     async def disconnect(sid: str) -> None:
-        logging.debug("Client [%s] disconnected", click.style(str(sid), fg="cyan"))
+        logger.debug("Client [%s] disconnected", click.style(str(sid), fg="cyan"))
 
     @sio.event  # type: ignore
     async def service_serialization(sid: str) -> SerializedObject:
-        logging.debug(
+        logger.debug(
             "Client [%s] requested service serialization",
             click.style(str(sid), fg="cyan"),
         )
-        return state_manager.cache
+        return state_manager.cache_manager.cache
 
     @sio.event
-    async def update_value(sid: str, data: UpdateDict) -> SerializedObject | None:  # type: ignore
-        path = data["access_path"]
-
+    async def update_value(sid: str, data: UpdateDict) -> SerializedObject | None:
         try:
-            state_manager.set_service_attribute_value_by_path(
-                path=path, serialized_value=data["value"]
+            pydase.server.web_server.api.v1.endpoints.update_value(
+                state_manager=state_manager, data=data
             )
         except Exception as e:
             logger.exception(e)
             return dump(e)
+        return None
 
     @sio.event
     async def get_value(sid: str, access_path: str) -> SerializedObject:
         try:
-            return state_manager._data_service_cache.get_value_dict_from_cache(
-                access_path
+            return pydase.server.web_server.api.v1.endpoints.get_value(
+                state_manager=state_manager, access_path=access_path
             )
         except Exception as e:
             logger.exception(e)
@@ -156,17 +176,14 @@ def setup_sio_events(sio: socketio.AsyncServer, state_manager: StateManager) ->
     @sio.event
     async def trigger_method(sid: str, data: TriggerMethodDict) -> Any:
         try:
-            method = get_object_attr_from_path(
-                state_manager.service, data["access_path"]
+            return pydase.server.web_server.api.v1.endpoints.trigger_method(
+                state_manager=state_manager, data=data
             )
-            args = Deserializer.deserialize(data["args"])
-            kwargs: dict[str, Any] = Deserializer.deserialize(data["kwargs"])
-            return dump(method(*args, **kwargs))
         except Exception as e:
             logger.error(e)
             return dump(e)
 
 
 def setup_logging_handler(sio: socketio.AsyncServer) -> None:
-    logger = logging.getLogger()
-    logger.addHandler(SocketIOHandler(sio))
+    logging.getLogger().addHandler(SocketIOHandler(sio))
+    logging.getLogger("pydase").addHandler(SocketIOHandler(sio))

src/pydase/server/web_server/web_server.py

@@ -4,62 +4,72 @@ import logging
 from pathlib import Path
 from typing import Any
 
-import socketio  # type: ignore[import-untyped]
-import uvicorn
-from fastapi import FastAPI, Response
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import FileResponse
-from fastapi.staticfiles import StaticFiles
+import aiohttp.web
+import aiohttp_middlewares.cors
 
 from pydase.config import ServiceConfig, WebServerConfig
 from pydase.data_service.data_service_observer import DataServiceObserver
+from pydase.server.web_server.api import create_api_application
 from pydase.server.web_server.sio_setup import (
     setup_sio_server,
 )
-from pydase.utils.helpers import get_path_from_path_parts, parse_full_access_path
+from pydase.utils.helpers import (
+    get_path_from_path_parts,
+    parse_full_access_path,
+)
 from pydase.utils.serialization.serializer import generate_serialized_data_paths
-from pydase.version import __version__
 
 logger = logging.getLogger(__name__)
+API_VERSION = "v1"
 
 
 class WebServer:
     """
-    Represents a web server that adheres to the AdditionalServerProtocol, designed to
-    work with a DataService instance. This server facilitates client-server
-    communication and state management through web protocols and socket connections.
+    Represents a web server that adheres to the
+    [`AdditionalServerProtocol`][pydase.server.server.AdditionalServerProtocol],
+    designed to work with a [`DataService`][pydase.DataService] instance. This server
+    facilitates client-server communication and state management through web protocols
+    and socket connections.
 
-    The WebServer class initializes and manages a web server environment using FastAPI
-    and Socket.IO, allowing for HTTP and WebSocket communications. It incorporates CORS
-    (Cross-Origin Resource Sharing) support, custom CSS, and serves a frontend static
-    files directory. It also initializes web server settings based on configuration
-    files or generates default settings if necessary.
+    The WebServer class initializes and manages a web server environment aiohttp and
+    Socket.IO, allowing for HTTP and Socket.IO communications. It incorporates CORS
+    (Cross-Origin Resource Sharing) support, custom CSS, and serves a static files
+    directory. It also initializes web server settings based on configuration files or
+    generates default settings if necessary.
 
     Configuration for the web server (like service configuration directory and whether
     to generate new web settings) is determined in the following order of precedence:
+
     1. Values provided directly to the constructor.
     2. Environment variable settings (via configuration classes like
-      `pydase.config.ServiceConfig` and `pydase.config.WebServerConfig`).
+      [`ServiceConfig`][pydase.config.ServiceConfig] and
+      [`WebServerConfig`][pydase.config.WebServerConfig]).
     3. Default values defined in the configuration classes.
 
     Args:
-        data_service_observer (DataServiceObserver): Observer for the DataService,
-          handling state updates and communication to connected clients.
-        host (str): Hostname or IP address where the server is accessible. Commonly
-          '0.0.0.0' to bind to all network interfaces.
-        port (int): Port number on which the server listens. Typically in the range
-          1024-65535 (non-standard ports).
-        css (str | Path | None, optional): Path to a custom CSS file for styling the
-          frontend. If None, no custom styles are applied. Defaults to None.
-        enable_cors (bool, optional): Flag to enable or disable CORS policy. When True,
-          CORS is enabled, allowing cross-origin requests. Defaults to True.
-        config_dir (Path | None, optional): Path to the configuration
-          directory where the web settings will be stored. Defaults to
-          `pydase.config.ServiceConfig().config_dir`.
-        generate_new_web_settings (bool | None, optional): Flag to enable or disable
-          generation of new web settings if the configuration file is missing. Defaults
-          to `pydase.config.WebServerConfig().generate_new_web_settings`.
-        **kwargs (Any): Additional unused keyword arguments.
+        data_service_observer:
+            Observer for the [`DataService`][pydase.DataService], handling state updates
+            and communication to connected clients.
+        host:
+            Hostname or IP address where the server is accessible. Commonly '0.0.0.0'
+            to bind to all network interfaces.
+        port:
+            Port number on which the server listens. Typically in the range 1024-65535
+            (non-standard ports).
+        css:
+            Path to a custom CSS file for styling the frontend. If None, no custom
+            styles are applied. Defaults to None.
+        enable_cors:
+            Flag to enable or disable CORS policy. When True, CORS is enabled, allowing
+            cross-origin requests. Defaults to True.
+        config_dir:
+            Path to the configuration directory where the web settings will be stored.
+            Defaults to
+            [`ServiceConfig().config_dir`][pydase.config.ServiceConfig.config_dir].
+        generate_web_settings:
+            Flag to enable or disable generation of new web settings if the
+            configuration file is missing. Defaults to
+            [`WebServerConfig().generate_web_settings`][pydase.config.WebServerConfig.generate_web_settings].
     """
 
     def __init__(  # noqa: PLR0913
@@ -88,24 +98,68 @@ class WebServer:
 
     async def serve(self) -> None:
         self._loop = asyncio.get_running_loop()
-        self._setup_socketio()
-        self._setup_fastapi_app()
-        self.web_server = uvicorn.Server(
-            uvicorn.Config(self.__fastapi_app, host=self.host, port=self.port)
+        self._sio = setup_sio_server(self.observer, self.enable_cors, self._loop)
+
+        async def index(request: aiohttp.web.Request) -> aiohttp.web.FileResponse:
+            return aiohttp.web.FileResponse(self.frontend_src / "index.html")
+
+        app = aiohttp.web.Application()
+
+        # Add CORS middleware if enabled
+        if self.enable_cors:
+            app.middlewares.append(
+                aiohttp_middlewares.cors.cors_middleware(allow_all=True)
+            )
+
+        # Define routes
+        self._sio.attach(app, socketio_path="/ws/socket.io")
+        app.router.add_static("/assets", self.frontend_src / "assets")
+        app.router.add_get("/service-properties", self._service_properties_route)
+        app.router.add_get("/web-settings", self._web_settings_route)
+        app.router.add_get("/custom.css", self._styles_route)
+        app.add_subapp("/api/", create_api_application(self.state_manager))
+
+        app.router.add_get(r"/", index)
+        app.router.add_get(r"/{tail:.*}", index)
+
+        await aiohttp.web._run_app(
+            app,
+            host=self.host,
+            port=self.port,
+            handle_signals=False,
+            print=logger.info,
+            shutdown_timeout=0.1,
         )
-        # overwrite uvicorn's signal handlers, otherwise it will bogart SIGINT and
-        # SIGTERM, which makes it impossible to escape out of
-        self.web_server.install_signal_handlers = lambda: None  # type: ignore[method-assign]
-        await self.web_server.serve()
+
+    async def _service_properties_route(
+        self,
+        request: aiohttp.web.Request,
+    ) -> aiohttp.web.Response:
+        return aiohttp.web.json_response(self.state_manager.cache_manager.cache)
+
+    async def _web_settings_route(
+        self,
+        request: aiohttp.web.Request,
+    ) -> aiohttp.web.Response:
+        return aiohttp.web.json_response(self.web_settings)
+
+    async def _styles_route(
+        self,
+        request: aiohttp.web.Request,
+    ) -> aiohttp.web.FileResponse | aiohttp.web.Response:
+        if self.css is not None:
+            return aiohttp.web.FileResponse(self.css)
+
+        return aiohttp.web.Response(content_type="text/css")
 
     def _initialise_configuration(self) -> None:
         logger.debug("Initialising web server configuration...")
 
-        file_path = self._service_config_dir / "web_settings.json"
-
         if self._generate_web_settings:
-            # File does not exist, create it with default content
             logger.debug("Generating web settings file...")
+            file_path = self._service_config_dir / "web_settings.json"
+
+            # File does not exist, create it with default content
             file_path.parent.mkdir(
                 parents=True, exist_ok=True
             )  # Ensure directory exists
@@ -148,54 +202,3 @@ class WebServer:
             }
 
         return current_web_settings
-
-    def _setup_socketio(self) -> None:
-        self._sio = setup_sio_server(self.observer, self.enable_cors, self._loop)
-        self.__sio_app = socketio.ASGIApp(self._sio)
-
-    def _setup_fastapi_app(self) -> None:  # noqa: C901
-        app = FastAPI()
-
-        if self.enable_cors:
-            app.add_middleware(
-                CORSMiddleware,
-                allow_credentials=True,
-                allow_origins=["*"],
-                allow_methods=["*"],
-                allow_headers=["*"],
-            )
-        app.mount("/ws", self.__sio_app)
-
-        @app.get("/version")
-        def version() -> str:
-            return __version__
-
-        @app.get("/name")
-        def name() -> str:
-            return type(self.service).__name__
-
-        @app.get("/service-properties")
-        def service_properties() -> dict[str, Any]:
-            return self.state_manager.cache  # type: ignore
-
-        @app.get("/web-settings")
-        def web_settings() -> dict[str, Any]:
-            return self.web_settings
-
-        # exposing custom.css file provided by user
-        @app.get("/custom.css")
-        async def styles() -> Response:
-            if self.css is not None:
-                return FileResponse(str(self.css))
-
-            return Response(content="", media_type="text/css")
-
-        app.mount(
-            "/",
-            StaticFiles(
-                directory=self.frontend_src,
-                html=True,
-            ),
-        )
-
-        self.__fastapi_app = app

src/pydase/task/autostart.py

@@ -0,0 +1,46 @@
+from typing import Any
+
+import pydase.data_service.data_service
+import pydase.task.task
+from pydase.task.task_status import TaskStatus
+from pydase.utils.helpers import is_property_attribute
+
+
+def autostart_service_tasks(
+    service: pydase.data_service.data_service.DataService,
+) -> None:
+    """Starts the service tasks defined with the `autostart` keyword argument.
+
+    This method goes through the attributes of the passed service and its nested
+    [`DataService`][pydase.DataService] instances and calls the start method on
+    autostart-tasks.
+    """
+
+    for attr in dir(service):
+        if is_property_attribute(service, attr) or attr in {
+            "_observers",
+            "__dict__",
+        }:  # prevent eval of property attrs and recursion
+            continue
+
+        val = getattr(service, attr)
+        if isinstance(val, pydase.task.task.Task):
+            if val.autostart and val.status == TaskStatus.NOT_RUNNING:
+                val.start()
+            else:
+                continue
+        else:
+            autostart_nested_service_tasks(val)
+
+
+def autostart_nested_service_tasks(
+    service: pydase.data_service.data_service.DataService | list[Any] | dict[Any, Any],
+) -> None:
+    if isinstance(service, pydase.DataService):
+        autostart_service_tasks(service)
+    elif isinstance(service, list):
+        for entry in service:
+            autostart_nested_service_tasks(entry)
+    elif isinstance(service, dict):
+        for entry in service.values():
+            autostart_nested_service_tasks(entry)

src/pydase/task/decorator.py

@@ -0,0 +1,145 @@
+import logging
+from collections.abc import Callable, Coroutine
+from typing import Any, Generic, TypeVar, overload
+
+from pydase.data_service.data_service import DataService
+from pydase.task.task import Task
+
+logger = logging.getLogger(__name__)
+
+R = TypeVar("R")
+
+
+class PerInstanceTaskDescriptor(Generic[R]):
+    """
+    A descriptor class that provides a unique [`Task`][pydase.task.task.Task] object
+    for each instance of a [`DataService`][pydase.data_service.data_service.DataService]
+    class.
+
+    The `PerInstanceTaskDescriptor` is used to transform an asynchronous function into a
+    task that is managed independently for each instance of a `DataService` subclass.
+    This allows tasks to be initialized, started, and stopped on a per-instance basis,
+    providing better control over task execution within the service.
+
+    The `PerInstanceTaskDescriptor` is not intended to be used directly. Instead, it is
+    used internally by the `@task` decorator to manage task objects for each instance of
+    the service class.
+    """
+
+    def __init__(
+        self,
+        func: Callable[[Any], Coroutine[None, None, R]]
+        | Callable[[], Coroutine[None, None, R]],
+        autostart: bool = False,
+    ) -> None:
+        self.__func = func
+        self.__autostart = autostart
+        self.__task_instances: dict[object, Task[R]] = {}
+
+    def __set_name__(self, owner: type[DataService], name: str) -> None:
+        """Stores the name of the task within the owning class. This method is called
+        automatically when the descriptor is assigned to a class attribute.
+        """
+
+        self.__task_name = name
+
+    @overload
+    def __get__(
+        self, instance: None, owner: type[DataService]
+    ) -> "PerInstanceTaskDescriptor[R]":
+        """Returns the descriptor itself when accessed through the class."""
+
+    @overload
+    def __get__(self, instance: DataService, owner: type[DataService]) -> Task[R]:
+        """Returns the `Task` object associated with the specific `DataService`
+        instance.
+        If no task exists for the instance, a new `Task` object is created and stored
+        in the `__task_instances` dictionary.
+        """
+
+    def __get__(
+        self, instance: DataService | None, owner: type[DataService]
+    ) -> "Task[R] | PerInstanceTaskDescriptor[R]":
+        if instance is None:
+            return self
+
+        # Create a new Task object for this instance, using the function's name.
+        if instance not in self.__task_instances:
+            self.__task_instances[instance] = instance._initialise_new_objects(
+                self.__task_name,
+                Task(self.__func.__get__(instance, owner), autostart=self.__autostart),
+            )
+
+        return self.__task_instances[instance]
+
+
+def task(
+    *, autostart: bool = False
+) -> Callable[
+    [
+        Callable[[Any], Coroutine[None, None, R]]
+        | Callable[[], Coroutine[None, None, R]]
+    ],
+    PerInstanceTaskDescriptor[R],
+]:
+    """
+    A decorator to define an asynchronous function as a per-instance task within a
+    [`DataService`][pydase.DataService] class.
+
+    This decorator transforms an asynchronous function into a
+    [`Task`][pydase.task.task.Task] object that is unique to each instance of the
+    `DataService` class. The resulting `Task` object provides methods like `start()`
+    and `stop()` to control the execution of the task, and manages the task's lifecycle
+    independently for each instance of the service.
+
+    The decorator is particularly useful for defining tasks that need to run
+    periodically or perform asynchronous operations, such as polling data sources,
+    updating databases, or any recurring job that should be managed within the context
+    of a `DataService`.
+    time.
+
+    Args:
+        autostart:
+            If set to True, the task will automatically start when the service is
+            initialized. Defaults to False.
+
+    Returns:
+        A decorator that wraps an asynchronous function in a
+        [`PerInstanceTaskDescriptor`][pydase.task.decorator.PerInstanceTaskDescriptor]
+        object, which, when accessed, provides an instance-specific
+        [`Task`][pydase.task.task.Task] object.
+
+    Example:
+        ```python
+        import asyncio
+
+        import pydase
+        from pydase.task.decorator import task
+
+
+        class MyService(pydase.DataService):
+            @task(autostart=True)
+            async def my_task(self) -> None:
+                while True:
+                    # Perform some periodic work
+                    await asyncio.sleep(1)
+
+
+        if __name__ == "__main__":
+            service = MyService()
+            pydase.Server(service=service).run()
+        ```
+
+        In this example, `my_task` is defined as a task using the `@task` decorator, and
+        it will start automatically when the service is initialized because
+        `autostart=True` is set. You can manually start or stop the task using
+        `service.my_task.start()` and `service.my_task.stop()`, respectively.
+    """
+
+    def decorator(
+        func: Callable[[Any], Coroutine[None, None, R]]
+        | Callable[[], Coroutine[None, None, R]],
+    ) -> PerInstanceTaskDescriptor[R]:
+        return PerInstanceTaskDescriptor(func, autostart=autostart)
+
+    return decorator

src/pydase/task/task.py

@@ -0,0 +1,148 @@
+import asyncio
+import inspect
+import logging
+from collections.abc import Callable, Coroutine
+from typing import (
+    Generic,
+    TypeVar,
+)
+
+import pydase.data_service.data_service
+from pydase.task.task_status import TaskStatus
+from pydase.utils.helpers import current_event_loop_exists
+
+logger = logging.getLogger(__name__)
+
+R = TypeVar("R")
+
+
+class Task(pydase.data_service.data_service.DataService, Generic[R]):
+    """A class representing a task within the `pydase` framework.
+
+    The `Task` class wraps an asynchronous function and provides methods to manage its
+    lifecycle, such as `start()` and `stop()`. It is typically used to perform periodic
+    or recurring jobs in a [`DataService`][pydase.DataService], like reading
+    sensor data, updating databases, or executing other background tasks.
+
+    When a function is decorated with the [`@task`][pydase.task.decorator.task]
+    decorator, it is replaced by a `Task` instance that controls the execution of the
+    original function.
+
+    Args:
+        func:
+            The asynchronous function that this task wraps. It must be a coroutine
+            without arguments.
+        autostart:
+            If set to True, the task will automatically start when the service is
+            initialized. Defaults to False.
+
+    Example:
+        ```python
+        import asyncio
+
+        import pydase
+        from pydase.task.decorator import task
+
+
+        class MyService(pydase.DataService):
+            @task(autostart=True)
+            async def my_task(self) -> None:
+                while True:
+                    # Perform some periodic work
+                    await asyncio.sleep(1)
+
+
+        if __name__ == "__main__":
+            service = MyService()
+            pydase.Server(service=service).run()
+        ```
+
+        In this example, `my_task` is defined as a task using the `@task` decorator, and
+        it will start automatically when the service is initialized because
+        `autostart=True` is set. You can manually start or stop the task using
+        `service.my_task.start()` and `service.my_task.stop()`, respectively.
+    """
+
+    def __init__(
+        self,
+        func: Callable[[], Coroutine[None, None, R | None]],
+        *,
+        autostart: bool = False,
+    ) -> None:
+        super().__init__()
+        self._autostart = autostart
+        self._func_name = func.__name__
+        self._func = func
+        self._task: asyncio.Task[R | None] | None = None
+        self._status = TaskStatus.NOT_RUNNING
+        self._result: R | None = None
+
+        if not current_event_loop_exists():
+            self._loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(self._loop)
+        else:
+            self._loop = asyncio.get_event_loop()
+
+    @property
+    def autostart(self) -> bool:
+        """Defines if the task should be started automatically when the
+        [`Server`][pydase.Server] starts."""
+        return self._autostart
+
+    @property
+    def status(self) -> TaskStatus:
+        """Returns the current status of the task."""
+        return self._status
+
+    def start(self) -> None:
+        """Starts the asynchronous task if it is not already running."""
+        if self._task:
+            return
+
+        def task_done_callback(task: asyncio.Task[R | None]) -> None:
+            """Handles tasks that have finished.
+
+            Updates the task status, calls the defined callbacks, and logs and re-raises
+            exceptions.
+            """
+
+            self._task = None
+            self._status = TaskStatus.NOT_RUNNING
+
+            exception = task.exception()
+            if exception is not None:
+                # Handle the exception, or you can re-raise it.
+                logger.error(
+                    "Task '%s' encountered an exception: %s: %s",
+                    self._func_name,
+                    type(exception).__name__,
+                    exception,
+                )
+                raise exception
+
+            self._result = task.result()
+
+        async def run_task() -> R | None:
+            if inspect.iscoroutinefunction(self._func):
+                logger.info("Starting task %r", self._func_name)
+                self._status = TaskStatus.RUNNING
+                res: Coroutine[None, None, R | None] = self._func()
+                try:
+                    return await res
+                except asyncio.CancelledError:
+                    logger.info("Task '%s' was cancelled", self._func_name)
+                    return None
+            logger.warning(
+                "Cannot start task %r. Function has not been bound yet", self._func_name
+            )
+            return None
+
+        logger.info("Creating task %r", self._func_name)
+        self._task = self._loop.create_task(run_task())
+        self._task.add_done_callback(task_done_callback)
+
+    def stop(self) -> None:
+        """Stops the running asynchronous task by cancelling it."""
+
+        if self._task:
+            self._task.cancel()

src/pydase/task/task_status.py

@@ -0,0 +1,8 @@
+import enum
+
+
+class TaskStatus(enum.Enum):
+    """Possible statuses of a [`Task`][pydase.task.task.Task]."""
+
+    RUNNING = "running"
+    NOT_RUNNING = "not_running"

src/pydase/units.py

@@ -3,7 +3,7 @@ from typing import TypedDict
 import pint
 
 units: pint.UnitRegistry = pint.UnitRegistry(autoconvert_offset_to_baseunit=True)
-units.default_format = "~P"  # pretty and short format
+units.formatter.default_format = "~P"  # pretty and short format
 
 Quantity = pint.Quantity
 Unit = units.Unit
@@ -21,18 +21,20 @@ def convert_to_quantity(
     Convert a given value into a pint.Quantity object with the specified unit.
 
     Args:
-        value (QuantityDict | float | int | Quantity):
+        value:
             The value to be converted into a Quantity object.
+
             - If value is a float or int, it will be directly converted to the specified
               unit.
             - If value is a dict, it must have keys 'magnitude' and 'unit' to represent
               the value and unit.
             - If value is a Quantity object, it will remain unchanged.\n
-        unit (str, optional): The target unit for conversion. If empty and value is not
-            a Quantity object, it will assume a unitless quantity.
+        unit:
+            The target unit for conversion. If empty and value is not a Quantity object,
+            it will assume a unitless quantity.
 
     Returns:
-        Quantity: The converted value as a pint.Quantity object with the specified unit.
+        The converted value as a pint.Quantity object with the specified unit.
 
     Examples:
         >>> convert_to_quantity(5, 'm')
@@ -42,9 +44,9 @@ def convert_to_quantity(
         >>> convert_to_quantity(10.0 * u.units.V)
         <Quantity(10.0, 'volt')>
 
-    Notes:
-        - If unit is not provided and value is a float or int, the resulting Quantity
-          will be unitless.
+    Note:
+        If unit is not provided and value is a float or int, the resulting Quantity will
+        be unitless.
     """
 
     if isinstance(value, int | float):

src/pydase/utils/decorators.py

@@ -10,9 +10,9 @@ class FunctionDefinitionError(Exception):
 
 
 def frontend(func: Callable[..., Any]) -> Callable[..., Any]:
-    """
-    Decorator to mark a DataService method for frontend rendering. Ensures that the
-    method does not contain arguments, as they are not supported for frontend rendering.
+    """Decorator to mark a [`DataService`][pydase.DataService] method for frontend
+    rendering. Ensures that the method does not contain arguments, as they are not
+    supported for frontend rendering.
     """
 
     if function_has_arguments(func):

src/pydase/utils/helpers.py

@@ -60,6 +60,10 @@ def parse_full_access_path(path: str) -> list[str]:
         list[str]
             A list of components that make up the path, including attribute names,
             numeric indices, and string keys as separate elements.
+
+    Example:
+        >>> parse_full_access_path('dict_attr["some_key"].attr_name["other_key"]')
+        ["dict_attr", '["some_key"]', "attr_name", '["other_key"]']
     """
     # Matches:
     # \w+ - Words
@@ -110,24 +114,26 @@ def get_class_and_instance_attributes(obj: object) -> dict[str, Any]:
 
     If an attribute exists at both the instance and class level,the value from the
     instance attribute takes precedence.
-    The __root__ object is removed as this will lead to endless recursion in the for
-    loops.
     """
 
     return dict(chain(type(obj).__dict__.items(), obj.__dict__.items()))
 
 
 def get_object_by_path_parts(target_obj: Any, path_parts: list[str]) -> Any:
+    """Gets nested attribute of `target_object` specified by `path_parts`.
+
+    Raises:
+        AttributeError: Attribute does not exist.
+        KeyError: Key in dict does not exist.
+        IndexError: Index out of list range.
+        TypeError: List index in the path is not a valid integer.
+    """
     for part in path_parts:
         if part.startswith("["):
             deserialized_part = parse_serialized_key(part)
             target_obj = target_obj[deserialized_part]
         else:
-            try:
-                target_obj = getattr(target_obj, part)
-            except AttributeError:
-                logger.debug("Attribute %a does not exist in the object.", part)
-                return None
+            target_obj = getattr(target_obj, part)
     return target_obj
 
 
@@ -145,12 +151,21 @@ def get_object_attr_from_path(target_obj: Any, path: str) -> Any:
         the path does not exist, the function logs a debug message and returns None.
 
     Raises:
-        ValueError: If a list index in the path is not a valid integer.
+        AttributeError: Attribute does not exist.
+        KeyError: Key in dict does not exist.
+        IndexError: Index out of list range.
+        TypeError: List index in the path is not a valid integer.
     """
     path_parts = parse_full_access_path(path)
     return get_object_by_path_parts(target_obj, path_parts)
 
 
+def get_task_class() -> type:
+    from pydase.task.task import Task
+
+    return Task
+
+
 def get_component_classes() -> list[type]:
     """
     Returns references to the component classes in a list.
@@ -185,3 +200,48 @@ def function_has_arguments(func: Callable[..., Any]) -> bool:
 
     # Check if there are any parameters left which would indicate additional arguments.
     return len(parameters) > 0
+
+
+def is_descriptor(obj: object) -> bool:
+    """Check if an object is a descriptor."""
+
+    # Exclude functions, methods, builtins and properties
+    if (
+        inspect.isfunction(obj)
+        or inspect.ismethod(obj)
+        or inspect.isbuiltin(obj)
+        or isinstance(obj, property)
+    ):
+        return False
+
+    # Check if it has any descriptor methods
+    return any(hasattr(obj, method) for method in ("__get__", "__set__", "__delete__"))
+
+
+def current_event_loop_exists() -> bool:
+    """Check if an event loop has been set."""
+    import asyncio
+
+    return asyncio.get_event_loop_policy()._local._loop is not None  # type: ignore
+
+
+def normalize_full_access_path_string(s: str) -> str:
+    """Normalizes a string representing a full access path by converting double quotes
+    to single quotes.
+
+    This function is useful for ensuring consistency in strings that represent access
+    paths containing dictionary keys, by replacing all double quotes (`"`) with single
+    quotes (`'`).
+
+    Args:
+        s (str): The input string to be normalized.
+
+    Returns:
+        A new string with all double quotes replaced by single quotes.
+
+    Example:
+        >>> normalize_full_access_path_string('dictionary["first"].my_task')
+        "dictionary['first'].my_task"
+    """
+
+    return s.replace('"', "'")

src/pydase/utils/logging.py

@@ -1,16 +1,58 @@
 import asyncio
 import logging
+import logging.config
 import sys
+from collections.abc import Callable
 from copy import copy
+from typing import ClassVar, Literal
 
+import click
 import socketio  # type: ignore[import-untyped]
-import uvicorn.logging
-from uvicorn.config import LOGGING_CONFIG
 
 import pydase.config
 
+logger = logging.getLogger(__name__)
 
-class DefaultFormatter(uvicorn.logging.ColourizedFormatter):
+if pydase.config.OperationMode().environment == "development":
+    LOG_LEVEL = logging.DEBUG
+else:
+    LOG_LEVEL = logging.INFO
+
+LOGGING_CONFIG = {
+    "version": 1,
+    "disable_existing_loggers": False,
+    "formatters": {
+        "default": {
+            "()": "pydase.utils.logging.DefaultFormatter",
+            "fmt": "%(asctime)s.%(msecs)03d | %(levelprefix)s | "
+            "%(name)s:%(funcName)s:%(lineno)d - %(message)s",
+            "datefmt": "%Y-%m-%d %H:%M:%S",
+        },
+    },
+    "handlers": {
+        "default": {
+            "formatter": "default",
+            "class": "logging.StreamHandler",
+            "stream": "ext://sys.stderr",
+        },
+    },
+    "loggers": {
+        "pydase": {"handlers": ["default"], "level": LOG_LEVEL, "propagate": False},
+        "aiohttp_middlewares": {
+            "handlers": ["default"],
+            "level": logging.WARNING,
+            "propagate": False,
+        },
+        "aiohttp": {
+            "handlers": ["default"],
+            "level": logging.INFO,
+            "propagate": False,
+        },
+    },
+}
+
+
+class DefaultFormatter(logging.Formatter):
     """
     A custom log formatter class that:
 
@@ -19,6 +61,36 @@ class DefaultFormatter(uvicorn.logging.ColourizedFormatter):
       for formatting the output, instead of the plain text message.
     """
 
+    level_name_colors: ClassVar[dict[int, Callable[..., str]]] = {
+        logging.DEBUG: lambda level_name: click.style(str(level_name), fg="cyan"),
+        logging.INFO: lambda level_name: click.style(str(level_name), fg="green"),
+        logging.WARNING: lambda level_name: click.style(str(level_name), fg="yellow"),
+        logging.ERROR: lambda level_name: click.style(str(level_name), fg="red"),
+        logging.CRITICAL: lambda level_name: click.style(
+            str(level_name), fg="bright_red"
+        ),
+    }
+
+    def __init__(
+        self,
+        fmt: str | None = None,
+        datefmt: str | None = None,
+        style: Literal["%", "{", "$"] = "%",
+        use_colors: bool | None = None,
+    ):
+        if use_colors in (True, False):
+            self.use_colors = use_colors
+        else:
+            self.use_colors = sys.stdout.isatty()
+        super().__init__(fmt=fmt, datefmt=datefmt, style=style)
+
+    def color_level_name(self, level_name: str, level_no: int) -> str:
+        def default(level_name: str) -> str:
+            return str(level_name)
+
+        func = self.level_name_colors.get(level_no, default)
+        return func(level_name)
+
     def formatMessage(self, record: logging.LogRecord) -> str:  # noqa: N802
         recordcopy = copy(record)
         levelname = recordcopy.levelname
@@ -47,7 +119,8 @@ class SocketIOHandler(logging.Handler):
         self._sio = sio
 
     def format(self, record: logging.LogRecord) -> str:
-        return f"{record.name}:{record.funcName}:{record.lineno} - {record.message}"
+        msg = record.getMessage()
+        return f"{record.name}:{record.funcName}:{record.lineno} - {msg}"
 
     def emit(self, record: logging.LogRecord) -> None:
         log_entry = self.format(record)
@@ -64,86 +137,16 @@ class SocketIOHandler(logging.Handler):
         )
 
 
-def setup_logging(level: str | int | None = None) -> None:
+def setup_logging() -> None:
     """
     Configures the logging settings for the application.
 
     This function sets up logging with specific formatting and colorization of log
-    messages. The log level is determined based on the application's operation mode,
-    with an option to override the level. By default, in a development environment, the
-    log level is set to DEBUG, whereas in other environments, it is set to INFO.
-
-    Args:
-        level (Optional[str | int]):
-            A specific log level to set for the application. If None, the log level is
-            determined based on the application's operation mode. Accepts standard log
-            level names ('DEBUG', 'INFO', etc.) and corresponding numerical values.
-
-    Example:
-
-    ```python
-    >>> import logging
-    >>> setup_logging(logging.DEBUG)
-    >>> setup_logging("INFO")
-    ```
+    messages. The log level is determined based on the application's operation mode. By
+    default, in a development environment, the log level is set to DEBUG, whereas in
+    other environments, it is set to INFO.
     """
 
-    logger = logging.getLogger()
+    logger.debug("Configuring pydase logging.")
 
-    if pydase.config.OperationMode().environment == "development":
-        log_level = logging.DEBUG
-    else:
-        log_level = logging.INFO
-
-    # If a level is specified, check whether it's a string or an integer.
-    if level is not None:
-        if isinstance(level, str):
-            # Convert known log level strings directly to their corresponding logging
-            # module constants.
-            level_name = level.upper()  # Ensure level names are uppercase
-            if hasattr(logging, level_name):
-                log_level = getattr(logging, level_name)
-            else:
-                raise ValueError(
-                    f"Invalid log level: {level}. Must be one of 'DEBUG', 'INFO', "
-                    "'WARNING', 'ERROR', etc."
-                )
-        elif isinstance(level, int):
-            log_level = level  # Directly use integer levels
-        else:
-            raise ValueError("Log level must be a string or an integer.")
-
-    # Set the logger's level.
-    logger.setLevel(log_level)
-
-    # create console handler and set level to debug
-    ch = logging.StreamHandler()
-
-    # add formatter to ch
-    ch.setFormatter(
-        DefaultFormatter(
-            fmt=(
-                "%(asctime)s.%(msecs)03d | %(levelprefix)s | "
-                "%(name)s:%(funcName)s:%(lineno)d - %(message)s"
-            ),
-            datefmt="%Y-%m-%d %H:%M:%S",
-        )
-    )
-
-    # add ch to logger
-    logger.addHandler(ch)
-
-    logger.debug("Configuring service logging.")
-    logging.getLogger("asyncio").setLevel(logging.INFO)
-    logging.getLogger("urllib3").setLevel(logging.INFO)
-
-    # configuring uvicorn logger
-    LOGGING_CONFIG["formatters"]["default"][
-        "fmt"
-    ] = "%(asctime)s.%(msecs)03d | %(levelprefix)s %(message)s"
-    LOGGING_CONFIG["formatters"]["default"]["datefmt"] = "%Y-%m-%d %H:%M:%S"
-    LOGGING_CONFIG["formatters"]["access"]["fmt"] = (
-        "%(asctime)s.%(msecs)03d | %(levelprefix)s %(client_addr)s "
-        '- "%(request_line)s" %(status_code)s'
-    )
-    LOGGING_CONFIG["formatters"]["access"]["datefmt"] = "%Y-%m-%d %H:%M:%S"
+    logging.config.dictConfig(LOGGING_CONFIG)

src/pydase/utils/serialization/deserializer.py

@@ -1,22 +1,31 @@
 import enum
 import logging
+from datetime import datetime
 from typing import TYPE_CHECKING, Any, NoReturn, cast
 
 import pydase
 import pydase.components
 import pydase.units as u
-from pydase.utils.helpers import get_component_classes
-from pydase.utils.serialization.types import SerializedObject
+from pydase.utils.helpers import (
+    get_component_classes,
+)
+from pydase.utils.serialization.types import (
+    SerializedDatetime,
+    SerializedException,
+    SerializedObject,
+)
 
 if TYPE_CHECKING:
     from collections.abc import Callable
 
+
 logger = logging.getLogger(__name__)
 
 
 class Deserializer:
     @classmethod
     def deserialize(cls, serialized_object: SerializedObject) -> Any:
+        """Deserialize `serialized_object` (a `dict`) to a Python object."""
         type_handler: dict[str | None, None | Callable[..., Any]] = {
             None: None,
             "int": cls.deserialize_primitive,
@@ -33,6 +42,7 @@ class Deserializer:
             "dict": cls.deserialize_dict,
             "method": cls.deserialize_method,
             "Exception": cls.deserialize_exception,
+            "datetime": cls.deserialize_datetime,
         }
 
         # First go through handled types (as ColouredEnum is also within the components)
@@ -41,9 +51,9 @@ class Deserializer:
             return handler(serialized_object)
 
         # Custom types like Components or DataService classes
-        component_class = cls.get_component_class(serialized_object["type"])
-        if component_class:
-            return cls.deserialize_component_type(serialized_object, component_class)
+        service_base_class = cls.get_service_base_class(serialized_object["type"])
+        if service_base_class:
+            return cls.deserialize_data_service(serialized_object, service_base_class)
 
         return None
 
@@ -57,6 +67,10 @@ class Deserializer:
     def deserialize_quantity(cls, serialized_object: SerializedObject) -> Any:
         return u.convert_to_quantity(serialized_object["value"])  # type: ignore
 
+    @classmethod
+    def deserialize_datetime(cls, serialized_object: SerializedDatetime) -> datetime:
+        return datetime.fromisoformat(serialized_object["value"])
+
     @classmethod
     def deserialize_enum(
         cls,
@@ -88,27 +102,27 @@ class Deserializer:
         return
 
     @classmethod
-    def deserialize_exception(cls, serialized_object: SerializedObject) -> NoReturn:
+    def deserialize_exception(cls, serialized_object: SerializedException) -> NoReturn:
         import builtins
 
         try:
-            exception = getattr(builtins, serialized_object["name"])  # type: ignore
+            exception = getattr(builtins, serialized_object["name"])
         except AttributeError:
             exception = type(serialized_object["name"], (Exception,), {})  # type: ignore
         raise exception(serialized_object["value"])
 
     @staticmethod
-    def get_component_class(type_name: str | None) -> type | None:
+    def get_service_base_class(type_name: str | None) -> type | None:
         for component_class in get_component_classes():
             if type_name == component_class.__name__:
                 return component_class
-        if type_name == "DataService":
+        if type_name in ("DataService", "Task"):
             import pydase
 
             return pydase.DataService
         return None
 
-    @classmethod
+    @classmethod  # TODO: this shouldn't be a class method
     def create_attr_property(cls, serialized_attr: SerializedObject) -> property:
         attr_name = serialized_attr["full_access_path"].split(".")[-1]
 
@@ -125,7 +139,7 @@ class Deserializer:
         return property(get, set)
 
     @classmethod
-    def deserialize_component_type(
+    def deserialize_data_service(
         cls, serialized_object: SerializedObject, base_class: type
     ) -> Any:
         def create_proxy_class(serialized_object: SerializedObject) -> type:
@@ -148,4 +162,5 @@ class Deserializer:
 
 
 def loads(serialized_object: SerializedObject) -> Any:
+    """Deserialize `serialized_object` (a `dict`) to a Python object."""
     return Deserializer.deserialize(serialized_object)

src/pydase/utils/serialization/serializer.py

@@ -3,17 +3,20 @@ from __future__ import annotations
 import inspect
 import logging
 import sys
+from datetime import datetime
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Literal, cast
 
 import pydase.units as u
 from pydase.data_service.abstract_data_service import AbstractDataService
-from pydase.data_service.task_manager import TaskStatus
+from pydase.task.task_status import TaskStatus
 from pydase.utils.decorators import render_in_frontend
 from pydase.utils.helpers import (
     get_attribute_doc,
     get_component_classes,
     get_data_service_class_reference,
+    get_task_class,
+    is_property_attribute,
     parse_full_access_path,
     parse_serialized_key,
 )
@@ -21,6 +24,7 @@ from pydase.utils.serialization.types import (
     DataServiceTypes,
     SerializedBool,
     SerializedDataService,
+    SerializedDatetime,
     SerializedDict,
     SerializedEnum,
     SerializedException,
@@ -49,41 +53,59 @@ class SerializationPathError(Exception):
     pass
 
 
-class SerializationValueError(Exception):
-    pass
-
-
 class Serializer:
-    @staticmethod
-    def serialize_object(obj: Any, access_path: str = "") -> SerializedObject:  # noqa: C901
+    """Serializes objects into
+    [`SerializedObject`][pydase.utils.serialization.types.SerializedObject]
+    representations.
+    """
+
+    @classmethod
+    def serialize_object(cls, obj: Any, access_path: str = "") -> SerializedObject:  # noqa: C901
+        """Serialize `obj` to a
+        [`SerializedObject`][pydase.utils.serialization.types.SerializedObject].
+
+        Args:
+            obj:
+                Object to be serialized.
+            access_path:
+                String corresponding to the full access path of the object. This will be
+                prepended to the full_access_path in the SerializedObject entries.
+
+        Returns:
+            Dictionary representation of `obj`.
+        """
+
         result: SerializedObject
 
         if isinstance(obj, Exception):
-            result = Serializer._serialize_exception(obj)
+            result = cls._serialize_exception(obj)
+
+        elif isinstance(obj, datetime):
+            result = cls._serialize_datetime(obj, access_path=access_path)
 
         elif isinstance(obj, AbstractDataService):
-            result = Serializer._serialize_data_service(obj, access_path=access_path)
+            result = cls._serialize_data_service(obj, access_path=access_path)
 
         elif isinstance(obj, list):
-            result = Serializer._serialize_list(obj, access_path=access_path)
+            result = cls._serialize_list(obj, access_path=access_path)
 
         elif isinstance(obj, dict):
-            result = Serializer._serialize_dict(obj, access_path=access_path)
+            result = cls._serialize_dict(obj, access_path=access_path)
 
         # Special handling for u.Quantity
         elif isinstance(obj, u.Quantity):
-            result = Serializer._serialize_quantity(obj, access_path=access_path)
+            result = cls._serialize_quantity(obj, access_path=access_path)
 
         # Handling for Enums
         elif isinstance(obj, Enum):
-            result = Serializer._serialize_enum(obj, access_path=access_path)
+            result = cls._serialize_enum(obj, access_path=access_path)
 
         # Methods and coroutines
         elif inspect.isfunction(obj) or inspect.ismethod(obj):
-            result = Serializer._serialize_method(obj, access_path=access_path)
+            result = cls._serialize_method(obj, access_path=access_path)
 
         elif isinstance(obj, int | float | bool | str | None):
-            result = Serializer._serialize_primitive(obj, access_path=access_path)
+            result = cls._serialize_primitive(obj, access_path=access_path)
 
         try:
             return result
@@ -92,8 +114,9 @@ class Serializer:
                 f"Could not serialized object of type {type(obj)}."
             )
 
-    @staticmethod
+    @classmethod
     def _serialize_primitive(
+        cls,
         obj: float | bool | str | None,
         access_path: str,
     ) -> (
@@ -112,8 +135,18 @@ class Serializer:
             "value": obj,
         }
 
-    @staticmethod
-    def _serialize_exception(obj: Exception) -> SerializedException:
+    @classmethod
+    def _serialize_datetime(cls, obj: datetime, access_path: str) -> SerializedDatetime:
+        return {
+            "type": "datetime",
+            "value": str(obj),
+            "doc": None,
+            "full_access_path": access_path,
+            "readonly": True,
+        }
+
+    @classmethod
+    def _serialize_exception(cls, obj: Exception) -> SerializedException:
         return {
             "full_access_path": "",
             "doc": None,
@@ -123,8 +156,8 @@ class Serializer:
             "name": obj.__class__.__name__,
         }
 
-    @staticmethod
-    def _serialize_enum(obj: Enum, access_path: str = "") -> SerializedEnum:
+    @classmethod
+    def _serialize_enum(cls, obj: Enum, access_path: str = "") -> SerializedEnum:
         import pydase.components.coloured_enum
 
         value = obj.name
@@ -149,9 +182,9 @@ class Serializer:
             },
         }
 
-    @staticmethod
+    @classmethod
     def _serialize_quantity(
-        obj: u.Quantity, access_path: str = ""
+        cls, obj: u.Quantity, access_path: str = ""
     ) -> SerializedQuantity:
         doc = get_attribute_doc(obj)
         value: u.QuantityDict = {"magnitude": obj.m, "unit": str(obj.u)}
@@ -163,13 +196,15 @@ class Serializer:
             "doc": doc,
         }
 
-    @staticmethod
-    def _serialize_dict(obj: dict[str, Any], access_path: str = "") -> SerializedDict:
+    @classmethod
+    def _serialize_dict(
+        cls, obj: dict[str, Any], access_path: str = ""
+    ) -> SerializedDict:
         readonly = False
         doc = get_attribute_doc(obj)
         value = {}
         for key, val in obj.items():
-            value[key] = Serializer.serialize_object(
+            value[key] = cls.serialize_object(
                 val, access_path=f'{access_path}["{key}"]'
             )
         return {
@@ -180,12 +215,12 @@ class Serializer:
             "doc": doc,
         }
 
-    @staticmethod
-    def _serialize_list(obj: list[Any], access_path: str = "") -> SerializedList:
+    @classmethod
+    def _serialize_list(cls, obj: list[Any], access_path: str = "") -> SerializedList:
         readonly = False
         doc = get_attribute_doc(obj)
         value = [
-            Serializer.serialize_object(o, access_path=f"{access_path}[{i}]")
+            cls.serialize_object(o, access_path=f"{access_path}[{i}]")
             for i, o in enumerate(obj)
         ]
         return {
@@ -196,9 +231,9 @@ class Serializer:
             "doc": doc,
         }
 
-    @staticmethod
+    @classmethod
     def _serialize_method(
-        obj: Callable[..., Any], access_path: str = ""
+        cls, obj: Callable[..., Any], access_path: str = ""
     ) -> SerializedMethod:
         readonly = True
         doc = get_attribute_doc(obj)
@@ -231,9 +266,9 @@ class Serializer:
             "frontend_render": frontend_render,
         }
 
-    @staticmethod
+    @classmethod
     def _serialize_data_service(
-        obj: AbstractDataService, access_path: str = ""
+        cls, obj: AbstractDataService, access_path: str = ""
     ) -> SerializedDataService:
         readonly = False
         doc = get_attribute_doc(obj)
@@ -247,6 +282,10 @@ class Serializer:
         if component_base_cls:
             obj_type = component_base_cls.__name__  # type: ignore
 
+        elif isinstance(obj, get_task_class()):
+            # Check if obj is a pydase task
+            obj_type = "Task"
+
         # Get the set of DataService class attributes
         data_service_attr_set = set(dir(get_data_service_class_reference()))
         # Get the set of the object attributes
@@ -261,29 +300,15 @@ class Serializer:
             if key.startswith("_"):
                 continue  # Skip attributes that start with underscore
 
-            # Skip keys that start with "start_" or "stop_" and end with an async
-            # method name
-            if key.startswith(("start_", "stop_")) and key.split("_", 1)[1] in {
-                name
-                for name, _ in inspect.getmembers(
-                    obj, predicate=inspect.iscoroutinefunction
-                )
-            }:
-                continue
-
             val = getattr(obj, key)
 
             path = f"{access_path}.{key}" if access_path else key
-            serialized_object = Serializer.serialize_object(val, access_path=path)
-
-            # If there's a running task for this method
-            if serialized_object["type"] == "method" and key in obj._task_manager.tasks:
-                serialized_object["value"] = TaskStatus.RUNNING.name
+            serialized_object = cls.serialize_object(val, access_path=path)
 
             value[key] = serialized_object
 
             # If the DataService attribute is a property
-            if isinstance(getattr(obj.__class__, key, None), property):
+            if is_property_attribute(obj, key):
                 prop: property = getattr(obj.__class__, key)
                 value[key]["readonly"] = prop.fset is None
                 value[key]["doc"] = get_attribute_doc(prop)  # overwrite the doc
@@ -299,6 +324,19 @@ class Serializer:
 
 
 def dump(obj: Any) -> SerializedObject:
+    """Serialize `obj` to a
+    [`SerializedObject`][pydase.utils.serialization.types.SerializedObject].
+
+    The [`Serializer`][pydase.utils.serialization.serializer.Serializer] is used for
+    encoding.
+
+    Args:
+        obj:
+            Object to be serialized.
+
+    Returns:
+        Dictionary representation of `obj`.
+    """
     return Serializer.serialize_object(obj)
 
 
@@ -307,12 +345,13 @@ def set_nested_value_by_path(
 ) -> None:
     """
     Set a value in a nested dictionary structure, which conforms to the serialization
-    format used by `pydase.utils.serializer.Serializer`, using a dot-notation path.
+    format used by [`Serializer`][pydase.utils.serialization.serializer.Serializer],
+    using a dot-notation path.
 
     Args:
         serialization_dict:
             The base dictionary representing data serialized with
-            `pydase.utils.serializer.Serializer`.
+            [`Serializer`][pydase.utils.serialization.serializer.Serializer].
         path:
             The dot-notation path (e.g., 'attr1.attr2[0].attr3') indicating where to
             set the value.
@@ -320,8 +359,8 @@ def set_nested_value_by_path(
             The new value to set at the specified path.
 
     Note:
-        - If the index equals the length of the list, the function will append the
-          serialized representation of the 'value' to the list.
+        If the index equals the length of the list, the function will append the
+        serialized representation of the 'value' to the list.
     """
 
     path_parts = parse_full_access_path(path)
@@ -340,7 +379,7 @@ def set_nested_value_by_path(
         next_level_serialized_object = get_container_item_by_key(
             current_dict, path_parts[-1], allow_append=True
         )
-    except (SerializationPathError, SerializationValueError, KeyError) as e:
+    except (SerializationPathError, KeyError) as e:
         logger.error("Error occured trying to change %a: %s", path, e)
         return
 
@@ -424,36 +463,30 @@ def get_container_item_by_key(
 ) -> SerializedObject:
     """
     Retrieve an item from a container specified by the passed key. Add an item to the
-    container if allow_append is set to True.
+    container if `allow_append` is set to `True`.
 
     If specified keys or indexes do not exist, the function can append new elements to
     dictionaries and to lists if `allow_append` is True and the missing element is
     exactly the next sequential index (for lists).
 
     Args:
-        container: dict[str, SerializedObject] | list[SerializedObject]
+        container:
             The container representing serialized data.
-        key: str
+        key:
             The key name representing the attribute in the dictionary, which may include
             direct keys or indexes (e.g., 'attr_name', '["key"]' or '[0]').
-        allow_append: bool
+        allow_append:
             Flag to allow appending a new entry if the specified index is out of range
             by exactly one position.
 
     Returns:
-        SerializedObject
-            The dictionary or list item corresponding to the specified attribute and
-            index.
+        The dictionary or list item corresponding to the specified attribute and index.
 
     Raises:
         SerializationPathError:
             If the path composed of `attr_name` and any specified index is invalid, or
             leads to an IndexError or KeyError. This error is also raised if an attempt
             to access a nonexistent key or index occurs without permission to append.
-        SerializationValueError:
-            If the retrieval results in an object that is expected to be a dictionary
-            but is not, indicating a mismatch between expected and actual serialized
-            data structure.
     """
     processed_key = parse_serialized_key(key)
 
@@ -475,13 +508,12 @@ def get_data_paths_from_serialized_object(  # noqa: C901
     Recursively extracts full access paths from a serialized object.
 
     Args:
-        serialized_obj (SerializedObject):
+        serialized_obj:
             The dictionary representing the serialization of an object. Produced by
             `pydase.utils.serializer.Serializer`.
 
     Returns:
-        list[str]:
-            A list of strings, each representing a full access path in the serialized
+        A list of strings, each representing a full access path in the serialized
             object.
     """
 
@@ -522,12 +554,11 @@ def generate_serialized_data_paths(
     Recursively extracts full access paths from a serialized DataService class instance.
 
     Args:
-        data (dict[str, SerializedObject]):
+        data:
             The value of the "value" key of a serialized DataService class instance.
 
     Returns:
-        list[str]:
-            A list of strings, each representing a full access path in the serialized
+        A list of strings, each representing a full access path in the serialized
             object.
     """
 
@@ -546,3 +577,6 @@ def serialized_dict_is_nested_object(serialized_dict: SerializedObject) -> bool:
     # We are excluding Quantity here as the value corresponding to the "value" key is
     # a dictionary of the form {"magnitude": ..., "unit": ...}
     return serialized_dict["type"] != "Quantity" and (isinstance(value, dict | list))
+
+
+__all__ = ["Serializer", "dump"]

src/pydase/utils/serialization/types.py

@@ -45,6 +45,11 @@ class SerializedString(SerializedObjectBase):
     type: Literal["str"]
 
 
+class SerializedDatetime(SerializedObjectBase):
+    type: Literal["datetime"]
+    value: str
+
+
 class SerializedEnum(SerializedObjectBase):
     name: str
     value: str
@@ -93,7 +98,9 @@ class SerializedException(SerializedObjectBase):
     type: Literal["Exception"]
 
 
-DataServiceTypes = Literal["DataService", "Image", "NumberSlider", "DeviceConnection"]
+DataServiceTypes = Literal[
+    "DataService", "Image", "NumberSlider", "DeviceConnection", "Task"
+]
 
 
 class SerializedDataService(SerializedObjectBase):
@@ -107,6 +114,7 @@ SerializedObject = (
     | SerializedFloat
     | SerializedInteger
     | SerializedString
+    | SerializedDatetime
     | SerializedList
     | SerializedDict
     | SerializedNoneType
@@ -117,3 +125,21 @@ SerializedObject = (
     | SerializedQuantity
     | SerializedNoValue
 )
+"""
+This type can be any of the following:
+
+- SerializedBool
+- SerializedFloat
+- SerializedInteger
+- SerializedString
+- SerializedDatetime
+- SerializedList
+- SerializedDict
+- SerializedNoneType
+- SerializedMethod
+- SerializedException
+- SerializedDataService
+- SerializedEnum
+- SerializedQuantity
+- SerializedNoValue
+"""

tests/client/test_client.py

@@ -7,7 +7,7 @@ import pytest
 from pydase.client.proxy_loader import ProxyAttributeError
 
 
-@pytest.fixture(scope="session")
+@pytest.fixture(scope="module")
 def pydase_client() -> Generator[pydase.Client, None, Any]:
     class SubService(pydase.DataService):
         name = "SubService"
@@ -45,7 +45,7 @@ def pydase_client() -> Generator[pydase.Client, None, Any]:
     thread = threading.Thread(target=server.run, daemon=True)
     thread.start()
 
-    client = pydase.Client(hostname="localhost", port=9999)
+    client = pydase.Client(url="ws://localhost:9999")
 
     yield client
 
@@ -121,12 +121,16 @@ def test_dict(pydase_client: pydase.Client) -> None:
     # pop will remove the dictionary entry on the server
     assert list(pydase_client.proxy.dict_attr.keys()) == ["foo"]
 
+    pydase_client.proxy.dict_attr["non_existent_key"] = "Hello"
+    assert pydase_client.proxy.dict_attr["non_existent_key"] == "Hello"
+
 
 def test_tab_completion(pydase_client: pydase.Client) -> None:
     # Tab completion gets its suggestions from the __dir__ class method
     assert all(
         x in pydase_client.proxy.__dir__()
         for x in [
+            "dict_attr",
             "list_attr",
             "my_method",
             "my_property",

tests/components/test_device_connection.py

@@ -1,15 +1,13 @@
 import asyncio
-import logging
 
 import pydase
 import pydase.components.device_connection
 import pytest
+from pydase.task.autostart import autostart_service_tasks
 from pytest import LogCaptureFixture
 
-logger = logging.getLogger(__name__)
 
-
-@pytest.mark.asyncio
+@pytest.mark.asyncio(scope="function")
 async def test_reconnection(caplog: LogCaptureFixture) -> None:
     class MyService(pydase.components.device_connection.DeviceConnection):
         def __init__(
@@ -22,10 +20,9 @@ async def test_reconnection(caplog: LogCaptureFixture) -> None:
             self._connected = True
 
     service_instance = MyService()
+    autostart_service_tasks(service_instance)
 
     assert service_instance._connected is False
 
-    service_instance._task_manager.start_autostart_tasks()
-
     await asyncio.sleep(0.01)
     assert service_instance._connected is True

tests/components/test_image.py

@@ -1,4 +1,3 @@
-import logging
 
 import pydase
 import pydase.components
@@ -7,8 +6,6 @@ from pydase.data_service.state_manager import StateManager
 from pydase.utils.serialization.serializer import dump
 from pytest import LogCaptureFixture
 
-logger = logging.getLogger(__name__)
-
 
 def test_image_functions(caplog: LogCaptureFixture) -> None:
     class MyService(pydase.DataService):

tests/components/test_number_slider.py

@@ -8,7 +8,7 @@ from pydase.data_service.data_service_observer import DataServiceObserver
 from pydase.data_service.state_manager import StateManager
 from pytest import LogCaptureFixture
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger("pydase")
 
 
 def test_number_slider(caplog: LogCaptureFixture) -> None:

tests/conftest.py

@@ -0,0 +1,11 @@
+import logging
+
+import pytest
+
+
+@pytest.fixture
+def caplog(caplog: pytest.LogCaptureFixture):
+    logger = logging.getLogger("pydase")
+    logger.propagate = True
+
+    yield caplog

tests/data_service/test_data_service.py

@@ -36,8 +36,7 @@ def test_unexpected_type_change_warning(caplog: LogCaptureFixture) -> None:
 
 
 def test_basic_inheritance_warning(caplog: LogCaptureFixture) -> None:
-    class SubService(DataService):
-        ...
+    class SubService(DataService): ...
 
     class SomeEnum(Enum):
         HI = 0
@@ -57,11 +56,9 @@ def test_basic_inheritance_warning(caplog: LogCaptureFixture) -> None:
         def name(self) -> str:
             return self._name
 
-        def some_method(self) -> None:
-            ...
+        def some_method(self) -> None: ...
 
-        async def some_task(self) -> None:
-            ...
+        async def some_task(self) -> None: ...
 
     ServiceClass()
 
@@ -129,17 +126,12 @@ def test_exposing_methods(caplog: LogCaptureFixture) -> None:
                 return "some method"
 
     class ClassWithTask(pydase.DataService):
-        async def some_task(self, sleep_time: int) -> None:
-            pass
+        @frontend
+        def some_method(self) -> str:
+            return "some method"
 
     ClassWithTask()
 
-    assert (
-        "Async function 'some_task' is defined with at least one argument. If you want "
-        "to use it as a task, remove the argument(s) from the function definition."
-        in caplog.text
-    )
-
 
 def test_dynamically_added_attribute(caplog: LogCaptureFixture) -> None:
     class MyService(DataService):

tests/data_service/test_data_service_cache.py

@@ -1,7 +1,6 @@
 import logging
 
 import pydase
-import pytest
 from pydase.data_service.data_service_observer import DataServiceObserver
 from pydase.data_service.state_manager import StateManager
 
@@ -22,50 +21,14 @@ def test_nested_attributes_cache_callback() -> None:
 
     service_instance.name = "Peepz"
     assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("name")["value"]
+        state_manager.cache_manager.get_value_dict_from_cache("name")["value"]
         == "Peepz"
     )
 
     service_instance.class_attr.name = "Ciao"
     assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("class_attr.name")[
+        state_manager.cache_manager.get_value_dict_from_cache("class_attr.name")[
             "value"
         ]
         == "Ciao"
     )
-
-
-@pytest.mark.asyncio
-async def test_task_status_update() -> None:
-    class ServiceClass(pydase.DataService):
-        name = "World"
-
-        async def my_method(self) -> None:
-            pass
-
-    service_instance = ServiceClass()
-    state_manager = StateManager(service_instance)
-    DataServiceObserver(state_manager)
-
-    assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("my_method")["type"]
-        == "method"
-    )
-    assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("my_method")[
-            "value"
-        ]
-        is None
-    )
-
-    service_instance.start_my_method()  # type: ignore
-    assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("my_method")["type"]
-        == "method"
-    )
-    assert (
-        state_manager._data_service_cache.get_value_dict_from_cache("my_method")[
-            "value"
-        ]
-        == "RUNNING"
-    )

tests/data_service/test_data_service_observer.py

@@ -5,7 +5,7 @@ import pydase
 import pytest
 from pydase.data_service.data_service_observer import DataServiceObserver
 from pydase.data_service.state_manager import StateManager
-from pydase.utils.serialization.serializer import SerializationError
+from pydase.utils.serialization.serializer import SerializationError, dump
 
 logger = logging.getLogger()
 
@@ -146,3 +146,41 @@ def test_private_attribute_does_not_have_to_be_serializable() -> None:
         service_instance.change_publ_attr()
 
     service_instance.change_priv_attr()
+
+
+def test_normalized_attr_path_in_dependent_property_changes(
+    caplog: pytest.LogCaptureFixture,
+) -> None:
+    class SubService(pydase.DataService):
+        _prop = 10.0
+
+        @property
+        def prop(self) -> float:
+            return self._prop
+
+    class MyService(pydase.DataService):
+        def __init__(self) -> None:
+            super().__init__()
+            self.service_dict = {"one": SubService()}
+
+    service_instance = MyService()
+    state_manager = StateManager(service=service_instance)
+    observer = DataServiceObserver(state_manager=state_manager)
+
+    assert observer.property_deps_dict["service_dict['one']._prop"] == [
+        "service_dict['one'].prop"
+    ]
+
+    # We can use dict key path encoded with double quotes
+    state_manager.set_service_attribute_value_by_path(
+        'service_dict["one"]._prop', dump(11.0)
+    )
+    assert service_instance.service_dict["one"].prop == 11.0
+    assert "'service_dict[\"one\"].prop' changed to '11.0'" in caplog.text
+
+    # We can use dict key path encoded with single quotes
+    state_manager.set_service_attribute_value_by_path(
+        "service_dict['one']._prop", dump(12.0)
+    )
+    assert service_instance.service_dict["one"].prop == 12.0
+    assert "'service_dict[\"one\"].prop' changed to '12.0'" in caplog.text

tests/data_service/test_task_manager.py

@@ -1,135 +0,0 @@
-import asyncio
-import logging
-
-import pydase
-import pytest
-from pydase.data_service.data_service_observer import DataServiceObserver
-from pydase.data_service.state_manager import StateManager
-from pytest import LogCaptureFixture
-
-logger = logging.getLogger()
-
-
-@pytest.mark.asyncio
-async def test_autostart_task_callback(caplog: LogCaptureFixture) -> None:
-    class MyService(pydase.DataService):
-        def __init__(self) -> None:
-            super().__init__()
-            self._autostart_tasks = {  # type: ignore
-                "my_task": (),  # type: ignore
-                "my_other_task": (),  # type: ignore
-            }
-
-        async def my_task(self) -> None:
-            logger.info("Triggered task.")
-
-        async def my_other_task(self) -> None:
-            logger.info("Triggered other task.")
-
-    # Your test code here
-    service_instance = MyService()
-    state_manager = StateManager(service_instance)
-    DataServiceObserver(state_manager)
-    service_instance._task_manager.start_autostart_tasks()
-
-    assert "'my_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-    assert "'my_other_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-
-
-@pytest.mark.asyncio
-async def test_DataService_subclass_autostart_task_callback(
-    caplog: LogCaptureFixture,
-) -> None:
-    class MySubService(pydase.DataService):
-        def __init__(self) -> None:
-            super().__init__()
-            self._autostart_tasks = {  # type: ignore
-                "my_task": (),
-                "my_other_task": (),
-            }
-
-        async def my_task(self) -> None:
-            logger.info("Triggered task.")
-
-        async def my_other_task(self) -> None:
-            logger.info("Triggered other task.")
-
-    class MyService(pydase.DataService):
-        sub_service = MySubService()
-
-    service_instance = MyService()
-    state_manager = StateManager(service_instance)
-    DataServiceObserver(state_manager)
-    service_instance._task_manager.start_autostart_tasks()
-
-    assert "'sub_service.my_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-    assert "'sub_service.my_other_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-
-
-@pytest.mark.asyncio
-async def test_DataService_subclass_list_autostart_task_callback(
-    caplog: LogCaptureFixture,
-) -> None:
-    class MySubService(pydase.DataService):
-        def __init__(self) -> None:
-            super().__init__()
-            self._autostart_tasks = {  # type: ignore
-                "my_task": (),
-                "my_other_task": (),
-            }
-
-        async def my_task(self) -> None:
-            logger.info("Triggered task.")
-
-        async def my_other_task(self) -> None:
-            logger.info("Triggered other task.")
-
-    class MyService(pydase.DataService):
-        sub_services_list = [MySubService() for i in range(2)]
-
-    service_instance = MyService()
-    state_manager = StateManager(service_instance)
-    DataServiceObserver(state_manager)
-    service_instance._task_manager.start_autostart_tasks()
-
-    assert (
-        "'sub_services_list[0].my_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-    )
-    assert (
-        "'sub_services_list[0].my_other_task' changed to 'TaskStatus.RUNNING'"
-        in caplog.text
-    )
-    assert (
-        "'sub_services_list[1].my_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-    )
-    assert (
-        "'sub_services_list[1].my_other_task' changed to 'TaskStatus.RUNNING'"
-        in caplog.text
-    )
-
-
-@pytest.mark.asyncio
-async def test_start_and_stop_task_methods(caplog: LogCaptureFixture) -> None:
-    class MyService(pydase.DataService):
-        def __init__(self) -> None:
-            super().__init__()
-
-        async def my_task(self) -> None:
-            while True:
-                logger.debug("Logging message")
-                await asyncio.sleep(0.1)
-
-    # Your test code here
-    service_instance = MyService()
-    state_manager = StateManager(service_instance)
-    DataServiceObserver(state_manager)
-    service_instance.start_my_task()
-    await asyncio.sleep(0.01)
-
-    assert "'my_task' changed to 'TaskStatus.RUNNING'" in caplog.text
-    assert "Logging message" in caplog.text
-    caplog.clear()
-
-    service_instance.stop_my_task()
-    await asyncio.sleep(0.01)
-    assert "Task 'my_task' was cancelled" in caplog.text

tests/observer_pattern/observable/test_decorators.py

@@ -73,7 +73,7 @@ def test_validate_set_timeout(caplog: pytest.LogCaptureFixture) -> None:
             )
             self.thread.start()
 
-        def __del__(self) -> None:
+        def close_connection(self) -> None:
             self.loop.call_soon_threadsafe(self.loop.stop)
             self.thread.join()
 
@@ -126,3 +126,4 @@ def test_validate_set_timeout(caplog: pytest.LogCaptureFixture) -> None:
         )
 
     service_instance.value_2 = 3.0  # no assertion raised
+    service_instance._driver.close_connection()

tests/observer_pattern/observable/test_observable.py

@@ -5,7 +5,7 @@ import pytest
 from pydase.observer_pattern.observable import Observable
 from pydase.observer_pattern.observer import Observer
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger("pydase")
 
 
 class MyObserver(Observer):

tests/observer_pattern/observable/test_observable_dict.py

@@ -5,7 +5,7 @@ import pytest
 from pydase.observer_pattern.observable import Observable
 from pydase.observer_pattern.observer import Observer
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger("pydase")
 
 
 class MyObserver(Observer):

tests/observer_pattern/observable/test_observable_object.py

@@ -5,7 +5,7 @@ import pytest
 from pydase.observer_pattern.observable import Observable
 from pydase.observer_pattern.observer import Observer
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger("pydase")
 
 
 class MyObserver(Observer):

tests/server/web_server/api/v1/test_endpoints.py

@@ -0,0 +1,194 @@
+import json
+import threading
+from collections.abc import Generator
+from typing import Any
+
+import aiohttp
+import pydase
+import pytest
+
+
+@pytest.fixture()
+def pydase_server() -> Generator[None, None, None]:
+    class SubService(pydase.DataService):
+        name = "SubService"
+
+    subservice_instance = SubService()
+
+    class MyService(pydase.DataService):
+        def __init__(self) -> None:
+            super().__init__()
+            self._readonly_attr = "MyService"
+            self._my_property = 12.1
+            self.sub_service = SubService()
+            self.list_attr = [1, 2]
+            self.dict_attr = {
+                "foo": subservice_instance,
+                "dotted.key": subservice_instance,
+            }
+
+        @property
+        def my_property(self) -> float:
+            return self._my_property
+
+        @my_property.setter
+        def my_property(self, value: float) -> None:
+            self._my_property = value
+
+        @property
+        def readonly_attr(self) -> str:
+            return self._readonly_attr
+
+        def my_method(self, input_str: str) -> str:
+            return input_str
+
+    server = pydase.Server(MyService(), web_port=9998)
+    thread = threading.Thread(target=server.run, daemon=True)
+    thread.start()
+
+    yield
+
+
+@pytest.mark.parametrize(
+    "access_path, expected",
+    [
+        (
+            "readonly_attr",
+            {
+                "full_access_path": "readonly_attr",
+                "doc": None,
+                "readonly": False,
+                "type": "str",
+                "value": "MyService",
+            },
+        ),
+        (
+            "sub_service.name",
+            {
+                "full_access_path": "sub_service.name",
+                "doc": None,
+                "readonly": False,
+                "type": "str",
+                "value": "SubService",
+            },
+        ),
+        (
+            "list_attr[0]",
+            {
+                "full_access_path": "list_attr[0]",
+                "doc": None,
+                "readonly": False,
+                "type": "int",
+                "value": 1,
+            },
+        ),
+        (
+            'dict_attr["foo"]',
+            {
+                "full_access_path": 'dict_attr["foo"]',
+                "doc": None,
+                "name": "SubService",
+                "readonly": False,
+                "type": "DataService",
+                "value": {
+                    "name": {
+                        "doc": None,
+                        "full_access_path": 'dict_attr["foo"].name',
+                        "readonly": False,
+                        "type": "str",
+                        "value": "SubService",
+                    }
+                },
+            },
+        ),
+    ],
+)
+@pytest.mark.asyncio()
+async def test_get_value(
+    access_path: str,
+    expected: dict[str, Any],
+    pydase_server: None,
+) -> None:
+    async with aiohttp.ClientSession("http://localhost:9998") as session:
+        resp = await session.get(f"/api/v1/get_value?access_path={access_path}")
+        content = json.loads(await resp.text())
+        assert content == expected
+
+
+@pytest.mark.parametrize(
+    "access_path, new_value, ok",
+    [
+        (
+            "sub_service.name",
+            {
+                "full_access_path": "sub_service.name",
+                "doc": None,
+                "readonly": False,
+                "type": "str",
+                "value": "New Name",
+            },
+            True,
+        ),
+        (
+            "list_attr[0]",
+            {
+                "full_access_path": "list_attr[0]",
+                "doc": None,
+                "readonly": False,
+                "type": "int",
+                "value": 11,
+            },
+            True,
+        ),
+        (
+            'dict_attr["foo"].name',
+            {
+                "full_access_path": 'dict_attr["foo"].name',
+                "doc": None,
+                "readonly": False,
+                "type": "str",
+                "value": "foo name",
+            },
+            True,
+        ),
+        (
+            "readonly_attr",
+            {
+                "full_access_path": "readonly_attr",
+                "doc": None,
+                "readonly": True,
+                "type": "str",
+                "value": "Other Name",
+            },
+            False,
+        ),
+        (
+            "invalid_attribute",
+            {
+                "full_access_path": "invalid_attribute",
+                "doc": None,
+                "readonly": False,
+                "type": "float",
+                "value": 12.0,
+            },
+            False,
+        ),
+    ],
+)
+@pytest.mark.asyncio()
+async def test_update_value(
+    access_path: str,
+    new_value: dict[str, Any],
+    ok: bool,
+    pydase_server: pydase.DataService,
+) -> None:
+    async with aiohttp.ClientSession("http://localhost:9998") as session:
+        resp = await session.put(
+            "/api/v1/update_value",
+            json={"access_path": access_path, "value": new_value},
+        )
+        assert resp.ok == ok
+        if resp.ok:
+            resp = await session.get(f"/api/v1/get_value?access_path={access_path}")
+            content = json.loads(await resp.text())
+            assert content == new_value

tests/task/test_task.py

@@ -0,0 +1,291 @@
+import asyncio
+import logging
+
+import pydase
+import pytest
+from pydase.data_service.data_service_observer import DataServiceObserver
+from pydase.data_service.state_manager import StateManager
+from pydase.task.autostart import autostart_service_tasks
+from pydase.task.decorator import task
+from pydase.task.task_status import TaskStatus
+from pytest import LogCaptureFixture
+
+logger = logging.getLogger("pydase")
+
+
+@pytest.mark.asyncio(scope="function")
+async def test_start_and_stop_task(caplog: LogCaptureFixture) -> None:
+    class MyService(pydase.DataService):
+        @task()
+        async def my_task(self) -> None:
+            logger.info("Triggered task.")
+            while True:
+                await asyncio.sleep(1)
+
+    # Your test code here
+    service_instance = MyService()
+    state_manager = StateManager(service_instance)
+    DataServiceObserver(state_manager)
+
+    autostart_service_tasks(service_instance)
+    await asyncio.sleep(0.1)
+    assert service_instance.my_task.status == TaskStatus.NOT_RUNNING
+
+    service_instance.my_task.start()
+    await asyncio.sleep(0.1)
+    assert service_instance.my_task.status == TaskStatus.RUNNING
+
+    assert "'my_task.status' changed to 'TaskStatus.RUNNING'" in caplog.text
+    assert "Triggered task." in caplog.text
+    caplog.clear()
+
+    service_instance.my_task.stop()
+    await asyncio.sleep(0.1)
+    assert service_instance.my_task.status == TaskStatus.NOT_RUNNING
+    assert "Task 'my_task' was cancelled" in caplog.text
+
+
+@pytest.mark.asyncio(scope="function")
+async def test_autostart_task(caplog: LogCaptureFixture) -> None:
+    class MyService(pydase.DataService):
+        @task(autostart=True)
+        async def my_task(self) -> None:
+            logger.info("Triggered task.")
+            while True:
+                await asyncio.sleep(1)
+
+    # Your test code here
+    service_instance = MyService()
+    state_manager = StateManager(service_instance)
+    DataServiceObserver(state_manager)
+
+    autostart_service_tasks(service_instance)
+
+    await asyncio.sleep(0.1)
+    assert service_instance.my_task.status == TaskStatus.RUNNING
+
+    assert "'my_task.status' changed to 'TaskStatus.RUNNING'" in caplog.text
+
+
+@pytest.mark.asyncio(scope="function")
+async def test_nested_list_autostart_task(
+    caplog: LogCaptureFixture,
+) -> None:
+    class MySubService(pydase.DataService):
+        @task(autostart=True)
+        async def my_task(self) -> None:
+            logger.info("Triggered task.")
+            while True:
+                await asyncio.sleep(1)
+
+    class MyService(pydase.DataService):
+        sub_services_list = [MySubService() for i in range(2)]
+
+    service_instance = MyService()
+    state_manager = StateManager(service_instance)
+    DataServiceObserver(state_manager)
+    autostart_service_tasks(service_instance)
+
+    await asyncio.sleep(0.1)
+    assert service_instance.sub_services_list[0].my_task.status == TaskStatus.RUNNING
+    assert service_instance.sub_services_list[1].my_task.status == TaskStatus.RUNNING
+
+    assert (
+        "'sub_services_list[0].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+    assert (
+        "'sub_services_list[1].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+
+
+@pytest.mark.asyncio(scope="function")
+async def test_nested_dict_autostart_task(
+    caplog: LogCaptureFixture,
+) -> None:
+    class MySubService(pydase.DataService):
+        @task(autostart=True)
+        async def my_task(self) -> None:
+            logger.info("Triggered task.")
+            while True:
+                await asyncio.sleep(1)
+
+    class MyService(pydase.DataService):
+        sub_services_dict = {"first": MySubService(), "second": MySubService()}
+
+    service_instance = MyService()
+    state_manager = StateManager(service_instance)
+    DataServiceObserver(state_manager)
+
+    autostart_service_tasks(service_instance)
+
+    await asyncio.sleep(0.1)
+
+    assert (
+        service_instance.sub_services_dict["first"].my_task.status == TaskStatus.RUNNING
+    )
+    assert (
+        service_instance.sub_services_dict["second"].my_task.status
+        == TaskStatus.RUNNING
+    )
+
+    assert (
+        "'sub_services_dict[\"first\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"second\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+
+
+@pytest.mark.asyncio(scope="function")
+async def test_manual_start_with_multiple_service_instances(
+    caplog: LogCaptureFixture,
+) -> None:
+    class MySubService(pydase.DataService):
+        @task()
+        async def my_task(self) -> None:
+            logger.info("Triggered task.")
+            while True:
+                await asyncio.sleep(1)
+
+    class MyService(pydase.DataService):
+        sub_services_list = [MySubService() for i in range(2)]
+        sub_services_dict = {"first": MySubService(), "second": MySubService()}
+
+    service_instance = MyService()
+    state_manager = StateManager(service_instance)
+    DataServiceObserver(state_manager)
+
+    autostart_service_tasks(service_instance)
+
+    await asyncio.sleep(0.1)
+
+    assert (
+        service_instance.sub_services_list[0].my_task.status == TaskStatus.NOT_RUNNING
+    )
+    assert (
+        service_instance.sub_services_list[1].my_task.status == TaskStatus.NOT_RUNNING
+    )
+    assert (
+        service_instance.sub_services_dict["first"].my_task.status
+        == TaskStatus.NOT_RUNNING
+    )
+    assert (
+        service_instance.sub_services_dict["second"].my_task.status
+        == TaskStatus.NOT_RUNNING
+    )
+
+    service_instance.sub_services_list[0].my_task.start()
+    await asyncio.sleep(0.01)
+
+    assert service_instance.sub_services_list[0].my_task.status == TaskStatus.RUNNING
+    assert (
+        "'sub_services_list[0].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+    assert (
+        "'sub_services_list[1].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"first\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"second\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+
+    service_instance.sub_services_list[0].my_task.stop()
+    await asyncio.sleep(0.01)
+
+    assert "Task 'my_task' was cancelled" in caplog.text
+    caplog.clear()
+
+    service_instance.sub_services_list[1].my_task.start()
+    await asyncio.sleep(0.01)
+
+    assert service_instance.sub_services_list[1].my_task.status == TaskStatus.RUNNING
+    assert (
+        "'sub_services_list[0].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_list[1].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"first\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"second\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+
+    service_instance.sub_services_list[1].my_task.stop()
+    await asyncio.sleep(0.01)
+
+    assert "Task 'my_task' was cancelled" in caplog.text
+    caplog.clear()
+
+    service_instance.sub_services_dict["first"].my_task.start()
+    await asyncio.sleep(0.01)
+
+    assert (
+        service_instance.sub_services_dict["first"].my_task.status == TaskStatus.RUNNING
+    )
+    assert (
+        "'sub_services_list[0].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_list[1].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"first\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"second\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+
+    service_instance.sub_services_dict["first"].my_task.stop()
+    await asyncio.sleep(0.01)
+
+    assert "Task 'my_task' was cancelled" in caplog.text
+    caplog.clear()
+
+    service_instance.sub_services_dict["second"].my_task.start()
+    await asyncio.sleep(0.01)
+
+    assert (
+        service_instance.sub_services_dict["second"].my_task.status
+        == TaskStatus.RUNNING
+    )
+    assert (
+        "'sub_services_list[0].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_list[1].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"first\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        not in caplog.text
+    )
+    assert (
+        "'sub_services_dict[\"second\"].my_task.status' changed to 'TaskStatus.RUNNING'"
+        in caplog.text
+    )
+
+    service_instance.sub_services_dict["second"].my_task.stop()
+    await asyncio.sleep(0.01)
+
+    assert "Task 'my_task' was cancelled" in caplog.text

tests/utils/serialization/test_deserializer.py

@@ -1,4 +1,5 @@
 import enum
+from datetime import datetime
 from typing import Any
 
 import pydase.components
@@ -137,6 +138,16 @@ def test_loads_primitive_types(obj: Any, obj_serialization: SerializedObject) ->
                 "name": "MyService",
             },
         ),
+        (
+            datetime.fromisoformat("2024-07-09 15:37:08.249845"),
+            {
+                "full_access_path": "",
+                "type": "datetime",
+                "value": "2024-07-09 15:37:08.249845",
+                "readonly": True,
+                "doc": None,
+            },
+        ),
     ],
 )
 def test_loads_advanced_types(obj: Any, obj_serialization: SerializedObject) -> None:

tests/utils/serialization/test_serializer.py

@@ -1,5 +1,5 @@
-import asyncio
 import enum
+from datetime import datetime
 from enum import Enum
 from typing import Any, ClassVar
 
@@ -7,7 +7,7 @@ import pydase
 import pydase.units as u
 import pytest
 from pydase.components.coloured_enum import ColouredEnum
-from pydase.data_service.task_manager import TaskStatus
+from pydase.task.task_status import TaskStatus
 from pydase.utils.decorators import frontend
 from pydase.utils.serialization.serializer import (
     SerializationPathError,
@@ -92,6 +92,16 @@ service_instance = ServiceClass()
                 "doc": None,
             },
         ),
+        (
+            datetime.fromisoformat("2024-07-09 15:37:08.249845"),
+            {
+                "full_access_path": "",
+                "type": "datetime",
+                "value": "2024-07-09 15:37:08.249845",
+                "readonly": True,
+                "doc": None,
+            },
+        ),
     ],
 )
 def test_dump(test_input: Any, expected: dict[str, Any]) -> None:
@@ -196,18 +206,16 @@ def test_ColouredEnum_serialize() -> None:
     }
 
 
-@pytest.mark.asyncio
+@pytest.mark.asyncio(scope="module")
 async def test_method_serialization() -> None:
     class ClassWithMethod(pydase.DataService):
         def some_method(self) -> str:
             return "some method"
 
         async def some_task(self) -> None:
-            while True:
-                await asyncio.sleep(10)
+            pass
 
     instance = ClassWithMethod()
-    instance.start_some_task()  # type: ignore
 
     assert dump(instance)["value"] == {
         "some_method": {
@@ -223,7 +231,7 @@ async def test_method_serialization() -> None:
         "some_task": {
             "full_access_path": "some_task",
             "type": "method",
-            "value": TaskStatus.RUNNING.name,
+            "value": None,
             "readonly": True,
             "doc": None,
             "async": True,
@@ -476,8 +484,7 @@ def test_derived_data_service_serialization() -> None:
         def name(self, value: str) -> None:
             self._name = value
 
-    class DerivedService(BaseService):
-        ...
+    class DerivedService(BaseService): ...
 
     base_service_serialization = dump(BaseService())
     derived_service_serialization = dump(DerivedService())

tests/utils/test_helpers.py

@@ -103,9 +103,21 @@ def test_get_object_by_path_parts(path_parts: list[str], expected: Any) -> None:
     assert get_object_by_path_parts(service_instance, path_parts) == expected
 
 
-def test_get_object_by_path_parts_error(caplog: pytest.LogCaptureFixture) -> None:
-    assert get_object_by_path_parts(service_instance, ["non_existent_attr"]) is None
-    assert "Attribute 'non_existent_attr' does not exist in the object." in caplog.text
+@pytest.mark.parametrize(
+    "path_parts, expected_exception",
+    [
+        (["non_existent_attr"], AttributeError),
+        (["dict_attr", '["non_existent_key"]'], KeyError),
+        (["list_attr", "[2]"], IndexError),
+        (["list_attr", "[1.0]"], TypeError),
+        (["list_attr", '["string_key"]'], TypeError),
+    ],
+)
+def test_get_object_by_path_parts_exception(
+    path_parts: list[str], expected_exception: type[Exception]
+) -> None:
+    with pytest.raises(expected_exception):
+        get_object_by_path_parts(service_instance, path_parts)
 
 
 @pytest.mark.parametrize(

tests/utils/test_logging.py

@@ -1,12 +1,12 @@
 import logging
 
-from pydase.utils.logging import setup_logging
 from pytest import LogCaptureFixture
 
 
 def test_log_error(caplog: LogCaptureFixture):
-    setup_logging("ERROR")
-    logger = logging.getLogger()
+    logger = logging.getLogger("pydase")
+    logger.setLevel(logging.ERROR)
+
     logger.debug("This is a debug message")
     logger.info("This is an info message")
     logger.warning("This is a warning message")
@@ -21,8 +21,9 @@ def test_log_error(caplog: LogCaptureFixture):
 
 
 def test_log_warning(caplog: LogCaptureFixture):
-    setup_logging("WARNING")
-    logger = logging.getLogger()
+    logger = logging.getLogger("pydase")
+    logger.setLevel(logging.WARNING)
+
     logger.debug("This is a debug message")
     logger.info("This is an info message")
     logger.warning("This is a warning message")
@@ -37,10 +38,9 @@ def test_log_warning(caplog: LogCaptureFixture):
 
 
 def test_log_debug(caplog: LogCaptureFixture):
-    setup_logging("DEBUG")
-    logger = (
-        logging.getLogger()
-    )  # Get the root logger or replace with the appropriate logger.
+    logger = logging.getLogger("pydase")
+    logger.setLevel(logging.DEBUG)
+
     logger.debug("This is a debug message")
     logger.info("This is an info message")
     logger.warning("This is a warning message")
@@ -54,10 +54,9 @@ def test_log_debug(caplog: LogCaptureFixture):
 
 
 def test_log_info(caplog: LogCaptureFixture):
-    setup_logging("INFO")
-    logger = (
-        logging.getLogger()
-    )  # Get the root logger or replace with the appropriate logger.
+    logger = logging.getLogger("pydase")
+    logger.setLevel(logging.INFO)
+
     logger.debug("This is a debug message")
     logger.info("This is an info message")
     logger.warning("This is a warning message")