Merge pull request #152 from tiqi-group/feat/client_context_manager

feat: adds a context manager to the client, fixes running loop issue
updates Readme and docs
2025-12-19 04:31:19 +01:00 · 2024-08-13 07:16:05 +02:00 · 2024-08-13 07:14:33 +02:00 · 2024-08-13 07:14:33 +02:00 · 2024-08-13 07:04:10 +02:00 · 2024-08-13 07:03:49 +02:00
8 changed files with 338 additions and 386 deletions
--- a/README.md
+++ b/README.md
@@ -34,9 +34,6 @@
 - [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)
@@ -154,7 +151,7 @@ if __name__ == "__main__":
    Server(service).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).

 ### Accessing the Web Interface

@@ -164,7 +161,7 @@ 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:

@@ -173,7 +170,8 @@ 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>:<service_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
@@ -185,30 +183,7 @@ 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
-
-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 Another Service
-
-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(hostname="<ip_addr>", port=8001, block_until_connected=False).proxy
-
-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.
+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](https://pydase.readthedocs.io/en/latest/user-guide/interaction/main/#python-client).

 ### RESTful API
 The `pydase` RESTful API allows for standard HTTP-based interactions and provides access to various functionalities through specific routes. 
@@ -875,7 +850,6 @@ 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: 
@@ -890,7 +864,6 @@ 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()
@@ -898,112 +871,14 @@ 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 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"
-
-
-service_instance = Service()
-pydase.Server(service_instance).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](./docs/images/Tailoring_frontend_component_layout.png)
-
-### 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

--- a/docs/user-guide/interaction/Python
+++ b/docs/user-guide/interaction/Python
@@ -1,13 +1,14 @@
-# Python Client
+# 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(hostname="<ip_addr>", port=8001).proxy
+# 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
@@ -19,6 +20,19 @@ 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.

+## 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.
@@ -32,7 +46,8 @@ import pydase

 class MyService(pydase.DataService):
    # Initialize the client without blocking the constructor
-    proxy = pydase.Client(hostname="<ip_addr>", port=8001, block_until_connected=False).proxy
+    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()
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,91 +1,103 @@
 # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.

+[[package]]
+name = "aiohappyeyeballs"
+version = "2.3.4"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = "<4.0,>=3.8"
+files = [
+    {file = "aiohappyeyeballs-2.3.4-py3-none-any.whl", hash = "sha256:40a16ceffcf1fc9e142fd488123b2e218abc4188cf12ac20c67200e1579baa42"},
+    {file = "aiohappyeyeballs-2.3.4.tar.gz", hash = "sha256:7e1ae8399c320a8adec76f6c919ed5ceae6edd4c3672f4d9eae2b27e37c80ff6"},
+]
+
 [[package]]
 name = "aiohttp"
-version = "3.9.5"
+version = "3.10.1"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
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 [package.extras]
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 [[package]]
 name = "aiohttp-middlewares"
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 ]

 [package.dependencies]
@@ -2127,28 +2159,29 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]

 [[package]]
 name = "ruff"
-version = "0.2.2"
+version = "0.5.6"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "ruff-0.5.6.tar.gz", hash = "sha256:07c9e3c2a8e1fe377dd460371c3462671a728c981c3205a5217291422209f642"},
 ]

 [[package]]
@@ -2431,4 +2464,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "80dda5533cf7111fd83407e0cce9228a99af644a6ffab4fa1abe085f4272cabf"
+content-hash = "54e25a68577a912301aa9125e3f3de545e03a199a79b2153c106285b92febbba"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pydase"
-version = "0.8.5"
+version = "0.9.0"
 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"
@@ -29,9 +29,8 @@ 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"
-requests = "^2.32.3"

 [tool.poetry.group.docs]
 optional = true
--- a/src/pydase/client/client.py
+++ b/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__)


@@ -24,7 +31,10 @@ class NotifyDict(TypedDict):

 def asyncio_loop_thread(loop: asyncio.AbstractEventLoop) -> None:
    asyncio.set_event_loop(loop)
-    loop.run_forever()
+    try:
+        loop.run_forever()
+    except RuntimeError:
+        logger.debug("Tried starting even loop, but it is running already")


 class ProxyClass(ProxyClassMixin, pydase.components.DeviceConnection):
@@ -80,12 +90,12 @@ class Client:
            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.
+        url (str):
+            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 (bool):
            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
@@ -94,12 +104,11 @@ 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)
@@ -107,29 +116,48 @@ class Client:
            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 +169,7 @@ 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:
--- a/src/pydase/server/web_server/api/v1/endpoints.py
+++ b/src/pydase/server/web_server/api/v1/endpoints.py
@@ -1,12 +1,15 @@
 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.deserializer import loads
-from pydase.utils.serialization.serializer import Serializer, dump
 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"]
@@ -32,4 +35,4 @@ def trigger_method(state_manager: StateManager, data: TriggerMethodDict) -> Any:
    serialized_kwargs = data.get("kwargs", None)
    kwargs: dict[str, Any] = loads(serialized_kwargs) if serialized_kwargs else {}

-    return dump(method(*args, **kwargs))
+    return Serializer.serialize_object(method(*args, **kwargs))
--- a/src/pydase/server/web_server/sio_setup.py
+++ b/src/pydase/server/web_server/sio_setup.py
@@ -22,7 +22,6 @@ from pydase.utils.serialization.serializer import SerializedObject
 logger = logging.getLogger(__name__)

 # These functions can be monkey-patched by other libraries at runtime
-loads = pydase.utils.serialization.deserializer.loads
 dump = pydase.utils.serialization.serializer.dump


--- a/tests/client/test_client.py
+++ b/tests/client/test_client.py
@@ -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
Author	SHA1	Message	Date
Mose Müller	2ebdb77433	Merge pull request #152 from tiqi-group/feat/client_context_manager feat: adds a context manager to the client, fixes running loop issue	2024-08-13 07:16:05 +02:00
Mose Müller	5ce30cfeaa	updates Readme and docs	2024-08-13 07:14:33 +02:00
Mose Müller	82d6a7f895	adds a context manager to the client, fixes running loop issue	2024-08-13 07:14:33 +02:00
Mose Müller	9aad9dfbc6	Merge pull request #151 from tiqi-group/breaking/client_arguments Breaking: changing allowed client arguments	2024-08-13 07:04:10 +02:00
Mose Müller	86bac8f9e5	updates version to v0.9.0	2024-08-13 07:03:49 +02:00
Mose Müller	348ff092aa	updates Readme with client instructions	2024-08-12 14:21:13 +02:00
Mose Müller	1ac08bf97d	fixes client test	2024-08-12 13:19:45 +02:00
Mose Müller	42357d7901	breaking: client takes url instead of hostname and port Connecting to secure services (with wss) was not possible. The user has to provide the whole URL now, which makes it much more flexible and less bug-prone.	2024-08-12 13:15:17 +02:00
Mose Müller	014a7b9492	updates ruff dependency	2024-08-05 09:36:32 +02:00
Mose Müller	e0d710644b	sio_setup: removes unused function	2024-08-05 05:27:17 +02:00
Mose Müller	4a9dba30d7	Merge pull request #149 from tiqi-group/feat/allow_monkey_patching_api_endpoints feat: allow monkey patching serilization methods for api endpoints	2024-07-31 09:48:29 +02:00
Mose Müller	9663dea79d	feat: allow monkey patching serilization methods for api endpoints	2024-07-31 08:44:23 +02:00
Mose Müller	81e40860df	moves frontend customization from Readme into docs	2024-07-30 11:27:57 +02:00
Mose Müller	9021e3a903	updates Readme	2024-07-30 11:19:07 +02:00
Mose Müller	2136d1a157	remove requests from dev dependencies	2024-07-30 11:17:35 +02:00