Hardcopy of pybind11 instead of using git submodules (#552)

* removed pybind as submodule
* added hardcopy of pybind11 2.10.0
* rename pybind11 folder to avoid conflicts when changing branch

Co-authored-by: Dhanya Thattil <dhanya.thattil@psi.ch>

libs/pybind/docs/advanced/embedding.rst

@@ -0,0 +1,262 @@
+.. _embedding:
+
+Embedding the interpreter
+#########################
+
+While pybind11 is mainly focused on extending Python using C++, it's also
+possible to do the reverse: embed the Python interpreter into a C++ program.
+All of the other documentation pages still apply here, so refer to them for
+general pybind11 usage. This section will cover a few extra things required
+for embedding.
+
+Getting started
+===============
+
+A basic executable with an embedded interpreter can be created with just a few
+lines of CMake and the ``pybind11::embed`` target, as shown below. For more
+information, see :doc:`/compiling`.
+
+.. code-block:: cmake
+
+    cmake_minimum_required(VERSION 3.4)
+    project(example)
+
+    find_package(pybind11 REQUIRED)  # or `add_subdirectory(pybind11)`
+
+    add_executable(example main.cpp)
+    target_link_libraries(example PRIVATE pybind11::embed)
+
+The essential structure of the ``main.cpp`` file looks like this:
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h> // everything needed for embedding
+    namespace py = pybind11;
+
+    int main() {
+        py::scoped_interpreter guard{}; // start the interpreter and keep it alive
+
+        py::print("Hello, World!"); // use the Python API
+    }
+
+The interpreter must be initialized before using any Python API, which includes
+all the functions and classes in pybind11. The RAII guard class ``scoped_interpreter``
+takes care of the interpreter lifetime. After the guard is destroyed, the interpreter
+shuts down and clears its memory. No Python functions can be called after this.
+
+Executing Python code
+=====================
+
+There are a few different ways to run Python code. One option is to use ``eval``,
+``exec`` or ``eval_file``, as explained in :ref:`eval`. Here is a quick example in
+the context of an executable with an embedded interpreter:
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h>
+    namespace py = pybind11;
+
+    int main() {
+        py::scoped_interpreter guard{};
+
+        py::exec(R"(
+            kwargs = dict(name="World", number=42)
+            message = "Hello, {name}! The answer is {number}".format(**kwargs)
+            print(message)
+        )");
+    }
+
+Alternatively, similar results can be achieved using pybind11's API (see
+:doc:`/advanced/pycpp/index` for more details).
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h>
+    namespace py = pybind11;
+    using namespace py::literals;
+
+    int main() {
+        py::scoped_interpreter guard{};
+
+        auto kwargs = py::dict("name"_a="World", "number"_a=42);
+        auto message = "Hello, {name}! The answer is {number}"_s.format(**kwargs);
+        py::print(message);
+    }
+
+The two approaches can also be combined:
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h>
+    #include <iostream>
+
+    namespace py = pybind11;
+    using namespace py::literals;
+
+    int main() {
+        py::scoped_interpreter guard{};
+
+        auto locals = py::dict("name"_a="World", "number"_a=42);
+        py::exec(R"(
+            message = "Hello, {name}! The answer is {number}".format(**locals())
+        )", py::globals(), locals);
+
+        auto message = locals["message"].cast<std::string>();
+        std::cout << message;
+    }
+
+Importing modules
+=================
+
+Python modules can be imported using ``module_::import()``:
+
+.. code-block:: cpp
+
+    py::module_ sys = py::module_::import("sys");
+    py::print(sys.attr("path"));
+
+For convenience, the current working directory is included in ``sys.path`` when
+embedding the interpreter. This makes it easy to import local Python files:
+
+.. code-block:: python
+
+    """calc.py located in the working directory"""
+
+
+    def add(i, j):
+        return i + j
+
+
+.. code-block:: cpp
+
+    py::module_ calc = py::module_::import("calc");
+    py::object result = calc.attr("add")(1, 2);
+    int n = result.cast<int>();
+    assert(n == 3);
+
+Modules can be reloaded using ``module_::reload()`` if the source is modified e.g.
+by an external process. This can be useful in scenarios where the application
+imports a user defined data processing script which needs to be updated after
+changes by the user. Note that this function does not reload modules recursively.
+
+.. _embedding_modules:
+
+Adding embedded modules
+=======================
+
+Embedded binary modules can be added using the ``PYBIND11_EMBEDDED_MODULE`` macro.
+Note that the definition must be placed at global scope. They can be imported
+like any other module.
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h>
+    namespace py = pybind11;
+
+    PYBIND11_EMBEDDED_MODULE(fast_calc, m) {
+        // `m` is a `py::module_` which is used to bind functions and classes
+        m.def("add", [](int i, int j) {
+            return i + j;
+        });
+    }
+
+    int main() {
+        py::scoped_interpreter guard{};
+
+        auto fast_calc = py::module_::import("fast_calc");
+        auto result = fast_calc.attr("add")(1, 2).cast<int>();
+        assert(result == 3);
+    }
+
+Unlike extension modules where only a single binary module can be created, on
+the embedded side an unlimited number of modules can be added using multiple
+``PYBIND11_EMBEDDED_MODULE`` definitions (as long as they have unique names).
+
+These modules are added to Python's list of builtins, so they can also be
+imported in pure Python files loaded by the interpreter. Everything interacts
+naturally:
+
+.. code-block:: python
+
+    """py_module.py located in the working directory"""
+    import cpp_module
+
+    a = cpp_module.a
+    b = a + 1
+
+
+.. code-block:: cpp
+
+    #include <pybind11/embed.h>
+    namespace py = pybind11;
+
+    PYBIND11_EMBEDDED_MODULE(cpp_module, m) {
+        m.attr("a") = 1;
+    }
+
+    int main() {
+        py::scoped_interpreter guard{};
+
+        auto py_module = py::module_::import("py_module");
+
+        auto locals = py::dict("fmt"_a="{} + {} = {}", **py_module.attr("__dict__"));
+        assert(locals["a"].cast<int>() == 1);
+        assert(locals["b"].cast<int>() == 2);
+
+        py::exec(R"(
+            c = a + b
+            message = fmt.format(a, b, c)
+        )", py::globals(), locals);
+
+        assert(locals["c"].cast<int>() == 3);
+        assert(locals["message"].cast<std::string>() == "1 + 2 = 3");
+    }
+
+
+Interpreter lifetime
+====================
+
+The Python interpreter shuts down when ``scoped_interpreter`` is destroyed. After
+this, creating a new instance will restart the interpreter. Alternatively, the
+``initialize_interpreter`` / ``finalize_interpreter`` pair of functions can be used
+to directly set the state at any time.
+
+Modules created with pybind11 can be safely re-initialized after the interpreter
+has been restarted. However, this may not apply to third-party extension modules.
+The issue is that Python itself cannot completely unload extension modules and
+there are several caveats with regard to interpreter restarting. In short, not
+all memory may be freed, either due to Python reference cycles or user-created
+global data. All the details can be found in the CPython documentation.
+
+.. warning::
+
+    Creating two concurrent ``scoped_interpreter`` guards is a fatal error. So is
+    calling ``initialize_interpreter`` for a second time after the interpreter
+    has already been initialized.
+
+    Do not use the raw CPython API functions ``Py_Initialize`` and
+    ``Py_Finalize`` as these do not properly handle the lifetime of
+    pybind11's internal data.
+
+
+Sub-interpreter support
+=======================
+
+Creating multiple copies of ``scoped_interpreter`` is not possible because it
+represents the main Python interpreter. Sub-interpreters are something different
+and they do permit the existence of multiple interpreters. This is an advanced
+feature of the CPython API and should be handled with care. pybind11 does not
+currently offer a C++ interface for sub-interpreters, so refer to the CPython
+documentation for all the details regarding this feature.
+
+We'll just mention a couple of caveats the sub-interpreters support in pybind11:
+
+ 1. Sub-interpreters will not receive independent copies of embedded modules.
+    Instead, these are shared and modifications in one interpreter may be
+    reflected in another.
+
+ 2. Managing multiple threads, multiple interpreters and the GIL can be
+    challenging and there are several caveats here, even within the pure
+    CPython API (please refer to the Python docs for details). As for
+    pybind11, keep in mind that ``gil_scoped_release`` and ``gil_scoped_acquire``
+    do not take sub-interpreters into account.