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# PyO3: Architecture

This document roughly describes the high-level architecture of PyO3.
If you want to become familiar with the codebase you are in the right place!

## Overview

PyO3 provides a bridge between Rust and Python, based on the [Python/C API].
Thus, PyO3 has low-level bindings of these API as its core.
On top of that, we have higher-level bindings to operate Python objects safely.
Also, to define Python classes and functions in Rust code, we have `trait PyClass` and a set of
protocol traits (e.g., `PyIterProtocol`) for supporting object protocols (i.e., `__dunder__` methods).
Since implementing `PyClass` requires lots of boilerplate, we have a proc-macro `#[pyclass]`.

To summarize, there are six main parts to the PyO3 codebase.

1. [Low-level bindings of Python/C API.](#1-low-level-bindings-of-python-capi)
   - [`src/ffi`]
2. [Bindings to Python objects.](#2-bindings-to-python-objects)
   - [`src/instance.rs`] and [`src/types`]
3. [`PyClass` and related functionalities.](#3-pyclass-and-related-functionalities)
   - [`src/pycell.rs`], [`src/pyclass.rs`], and more
4. [Protocol methods like `__getitem__`.](#4-protocol-methods)
   - [`src/class`]
5. [Procedural macros to simplify usage for users.](#5-procedural-macros-to-simplify-usage-for-users)
   - [`src/derive_utils.rs`], [`pyo3-macros`] and [`pyo3-macros-backend`]
6. [`build.rs` and `pyo3-build-config`](#6-buildrs-and-pyo3-build-config)
   - [`build.rs`](https://github.com/PyO3/pyo3/tree/main/build.rs)
   - [`pyo3-build-config`]

## 1. Low-level bindings of Python/C API

[`src/ffi`] contains wrappers of [Python/C API].

We aim to provide straight-forward Rust wrappers resembling the file structure of
[`cpython/Include`](https://github.com/python/cpython/tree/v3.9.2/Include).

However, we still lack some APIs and are continuously updating the module to match
the file contents upstream in CPython.
The tracking issue is [#1289](https://github.com/PyO3/pyo3/issues/1289), and contribution is welcome.

In the [`src/ffi`] module, there is lots of conditional compilation such as `#[cfg(Py_LIMITED_API)]`,
`#[cfg(Py_37)]`, and `#[cfg(PyPy)]`.
`Py_LIMITED_API` corresponds to `#define Py_LIMITED_API` macro in Python/C API.
With `Py_LIMITED_API`, we can build a Python-version-agnostic binary called an
[abi3 wheel](https://pyo3.rs/latest/building_and_distribution.html#py_limited_apiabi3).
`Py_37` means that the API is available from Python >= 3.7.
There are also `Py_38`, `Py_39`, and so on.
`PyPy` means that the API definition is for PyPy.
Those flags are set in [`build.rs`](#6-buildrs-and-pyo3-build-config).

## 2. Bindings to Python objects

[`src/types`] contains bindings to [built-in types](https://docs.python.org/3/library/stdtypes.html)
of Python, such as `dict` and `list`.
For historical reasons, Python's `object` is called `PyAny` in PyO3 and located in [`src/types/any.rs`].
Currently, `PyAny` is a straightforward wrapper of `ffi::PyObject`, defined as:

```rust
#[repr(transparent)]
pub struct PyAny(UnsafeCell<ffi::PyObject>);
```

All built-in types are defined as a C struct.
For example, `dict` is defined as:

```c
typedef struct {
    /* Base object */
    PyObject ob_base;
    /* Number of items in the dictionary */
    Py_ssize_t ma_used;
    /* Dictionary version */
    uint64_t ma_version_tag;
    PyDictKeysObject *ma_keys;
    PyObject **ma_values;
} PyDictObject;
```

However, we cannot access such a specific data structure with `#[cfg(Py_LIMITED_API)]` set.
Thus, all builtin objects are implemented as opaque types by wrapping `PyAny`, e.g.,:

```rust
#[repr(transparent)]
pub struct PyDict(PyAny);
```

Note that `PyAny` is not a pointer, and it is usually used as a pointer to the object in the
Python heap, as `&PyAny`.
This design choice can be changed
(see the discussion in [#1056](https://github.com/PyO3/pyo3/issues/1056)).

Since we need lots of boilerplate for implementing common traits for these types
(e.g., `AsPyPointer`, `AsRef<PyAny>`, and `Debug`), we have some macros in
[`src/types/mod.rs`].

## 3. `PyClass` and related functionalities

[`src/pycell.rs`], [`src/pyclass.rs`], and [`src/type_object.rs`] contain types and
traits to make `#[pyclass]` work.
Also, [`src/pyclass_init.rs`] and [`src/pyclass_slots.rs`] have related functionalities.

To realize object-oriented programming in C, all Python objects must have the following two fields
at the beginning.

```rust
#[repr(C)]
pub struct PyObject {
    pub ob_refcnt: usize,
    pub ob_type: *mut PyTypeObject,
    ...
}
```

Thanks to this guarantee, casting `*mut A` to `*mut PyObject` is valid if `A` is a Python object.

To ensure this guarantee, we have a wrapper struct `PyCell<T>` in [`src/pycell.rs`] which is roughly:

```rust
#[repr(C)]
pub struct PyCell<T: PyClass> {
    object: crate::ffi::PyObject,
    inner: T,
}
```

Thus, when copying a Rust struct to a Python object, we first allocate `PyCell` on the Python heap and then
move `T` into it.
Also, `PyCell` provides [RefCell](https://doc.rust-lang.org/std/cell/struct.RefCell.html)-like methods
to ensure Rust's borrow rules.
See [the documentation](https://docs.rs/pyo3/latest/pyo3/pycell/struct.PyCell.html) for more.

`PyCell<T>` requires that `T` implements `PyClass`.
This trait is somewhat complex and derives many traits, but the most important one is `PyTypeObject`
in [`src/type_object.rs`].
`PyTypeObject` is also implemented for built-in types.
In Python, all objects have their types, and types are also objects of `type`.
For example, you can see `type({})` shows `dict` and `type(type({}))` shows `type` in Python REPL.
`T: PyTypeObject` implies that `T` has a corresponding type object.

## 4. Protocol methods

Python has some built-in special methods called dunder, such as `__iter__`.
They are called [abstract objects layer](https://docs.python.org/3/c-api/abstract.html) in
Python/C API.
We provide a way to implement those protocols by using `#[pyproto]` and specific traits, such
as `PyIterProtocol`.
[`src/class`] defines these traits.
Each protocol method has a corresponding FFI function.
For example, `PyIterProtocol::__iter__` has
`pub unsafe extern "C" fn iter<T>(slf: *mut PyObject) -> *mut PyObject`.
When `#[pyproto]` finds that `T` implements `PyIterProtocol::__iter__`, it automatically
sets `iter<T>` on the type object of `T`.

Also, [`src/class/methods.rs`] has utilities for `#[pyfunction]` and [`src/class/impl_.rs`] has
some internal tricks for making `#[pyproto]` flexible.

## 5. Procedural macros to simplify usage for users.

[`pyo3-macros`] provides six proc-macro APIs: `pymodule`, `pyproto`, `pyfunction`, `pyclass`,
`pymethods`, and `#[derive(FromPyObject)]`.
[`pyo3-macros-backend`] has the actual implementations of these APIs.
[`src/derive_utils.rs`] contains some utilities used in code generated by these proc-macros,
such as parsing function arguments.

## 6. `build.rs` and `pyo3-build-config`

PyO3 supports a wide range of OSes, interpreters and use cases. The correct environment must be
detected at build time in order to set up relevant conditional compilation correctly. This logic
is captured in the [`pyo3-build-config`] crate, which is a `build-dependency` of `pyo3` and
`pyo3-macros`, and can also be used by downstream users in the same way.

In [`pyo3-build-config`]'s `build.rs` the build environment is detected and inlined into the crate
as a "config file". This works in all cases except for cross-compiling, where it is necessary to
capture this from the `pyo3` `build.rs` to get some extra environment variables that Cargo doesn't
set for build dependencies.

The `pyo3` `build.rs` also runs some safety checks such as ensuring the Python version detected is
actually supported.

Some of the functionality of `pyo3-build-config`:
- Find the interpreter for build and detect the Python version.
  - We have to set some version flags like `#[cfg(Py_3_7)]`.
  - If the interpreter is PyPy, we set `#[cfg(PyPy)`.
  - If the `PYO3_CONFIG_FILE` environment variable is set then that file's contents will be used
    instead of any detected configuration.
  - If the `PYO3_NO_PYTHON` environment variable is set then the interpreter detection is bypassed
    entirely and only abi3 extensions can be built.
- Check if we are building a Python extension.
  - If we are building an extension (e.g., Python library installable by `pip`),
    we don't link `libpython`.
    Currently we use the `extension-module` feature for this purpose. This may change in the future.
    See [#1123](https://github.com/PyO3/pyo3/pull/1123).
- Cross-compiling configuration
  - If `TARGET` architecture and `HOST` architecture differ, we find cross compile information
    from environment variables (`PYO3_CROSS_LIB_DIR` and `PYO3_CROSS_PYTHON_VERSION`) or system files.

<!-- External Links -->

[python/c api]: https://docs.python.org/3/c-api/

<!-- Crates -->

[`pyo3-macros`]: https://github.com/PyO3/pyo3/tree/main/pyo3-macros
[`pyo3-macros-backend`]: https://github.com/PyO3/pyo3/tree/main/pyo3-macros-backend
[`pyo3-build-config`]: https://github.com/PyO3/pyo3/tree/main/pyo3-build-config

<!-- Directories -->

[`src/class`]: https://github.com/PyO3/pyo3/tree/main/src/class
[`src/ffi`]: https://github.com/PyO3/pyo3/tree/main/src/ffi
[`src/types`]: https://github.com/PyO3/pyo3/tree/main/src/types

<!-- Files -->

[`src/derive_utils.rs`]: https://github.com/PyO3/pyo3/blob/main/src/derive_utils.rs
[`src/instance.rs`]: https://github.com/PyO3/pyo3/tree/main/src/instance.rs
[`src/pycell.rs`]: https://github.com/PyO3/pyo3/tree/main/src/pycell.rs
[`src/pyclass.rs`]: https://github.com/PyO3/pyo3/tree/main/src/pyclass.rs
[`src/pyclass_init.rs`]: https://github.com/PyO3/pyo3/tree/main/src/pyclass_init.rs
[`src/pyclass_slot.rs`]: https://github.com/PyO3/pyo3/tree/main/src/pyclass_slot.rs
[`src/type_object.rs`]: https://github.com/PyO3/pyo3/tree/main/src/type_object.rs
[`src/class/methods.rs`]: https://github.com/PyO3/pyo3/tree/main/src/class/methods.rs
[`src/class/impl_.rs`]: https://github.com/PyO3/pyo3/tree/main/src/class/impl_.rs
[`src/types/any.rs`]: https://github.com/PyO3/pyo3/tree/main/src/types/any.rs
[`src/types/mod.rs`]: https://github.com/PyO3/pyo3/tree/main/src/types/mod.rs
