.. _pure-mode: Pure Python Mode ================ In some cases, it's desirable to speed up Python code without losing the ability to run it with the Python interpreter. While pure Python scripts can be compiled with Cython, it usually results only in a speed gain of about 20%-50%. To go beyond that, Cython provides language constructs to add static typing and cythonic functionalities to a Python module to make it run much faster when compiled, while still allowing it to be interpreted. This is accomplished via an augmenting ``.pxd`` file, via Python type annotations (following `PEP 484 `_ and `PEP 526 `_), and/or via special functions and decorators available after importing the magic ``cython`` module. All three ways can be combined at need, although projects would commonly decide on a specific way to keep the static type information easy to manage. Although it is not typically recommended over writing straight Cython code in a :file:`.pyx` file, there are legitimate reasons to do this - easier testing and debugging, collaboration with pure Python developers, etc. In pure mode, you are more or less restricted to code that can be expressed (or at least emulated) in Python, plus static type declarations. Anything beyond that can only be done in .pyx files with extended language syntax, because it depends on features of the Cython compiler. Augmenting .pxd --------------- Using an augmenting :file:`.pxd` allows to let the original :file:`.py` file completely untouched. On the other hand, one needs to maintain both the :file:`.pxd` and the :file:`.py` to keep them in sync. While declarations in a :file:`.pyx` file must correspond exactly with those of a :file:`.pxd` file with the same name (and any contradiction results in a compile time error, see :doc:`pxd_files`), the untyped definitions in a :file:`.py` file can be overridden and augmented with static types by the more specific ones present in a :file:`.pxd`. If a :file:`.pxd` file is found with the same name as the :file:`.py` file being compiled, it will be searched for :keyword:`cdef` classes and :keyword:`cdef`/:keyword:`cpdef` functions and methods. The compiler will then convert the corresponding classes/functions/methods in the :file:`.py` file to be of the declared type. Thus if one has a file :file:`A.py`: .. literalinclude:: ../../examples/tutorial/pure/A.py and adds :file:`A.pxd`: .. literalinclude:: ../../examples/tutorial/pure/A.pxd then Cython will compile the :file:`A.py` as if it had been written as follows: .. literalinclude:: ../../examples/tutorial/pure/A_equivalent.pyx Notice how in order to provide the Python wrappers to the definitions in the :file:`.pxd`, that is, to be accessible from Python, * Python visible function signatures must be declared as `cpdef` (with default arguments replaced by a `*` to avoid repetition):: cpdef int myfunction(int x, int y=*) * C function signatures of internal functions can be declared as `cdef`:: cdef double _helper(double a) * `cdef` classes (extension types) are declared as `cdef class`; * `cdef` class attributes must be declared as `cdef public` if read/write Python access is needed, `cdef readonly` for read-only Python access, or plain `cdef` for internal C level attributes; * `cdef` class methods must be declared as `cpdef` for Python visible methods or `cdef` for internal C methods. In the example above, the type of the local variable `a` in `myfunction()` is not fixed and will thus be a Python object. To statically type it, one can use Cython's ``@cython.locals`` decorator (see :ref:`magic_attributes`, and :ref:`magic_attributes_pxd`). Normal Python (:keyword:`def`) functions cannot be declared in :file:`.pxd` files. It is therefore currently impossible to override the types of plain Python functions in :file:`.pxd` files, e.g. to override types of their local variables. In most cases, declaring them as `cpdef` will work as expected. .. _magic_attributes: Magic Attributes ---------------- Special decorators are available from the magic ``cython`` module that can be used to add static typing within the Python file, while being ignored by the interpreter. This option adds the ``cython`` module dependency to the original code, but does not require to maintain a supplementary :file:`.pxd` file. Cython provides a fake version of this module as `Cython.Shadow`, which is available as `cython.py` when Cython is installed, but can be copied to be used by other modules when Cython is not installed. "Compiled" switch ^^^^^^^^^^^^^^^^^ * ``compiled`` is a special variable which is set to ``True`` when the compiler runs, and ``False`` in the interpreter. Thus, the code .. literalinclude:: ../../examples/tutorial/pure/compiled_switch.py will behave differently depending on whether or not the code is executed as a compiled extension (:file:`.so`/:file:`.pyd`) module or a plain :file:`.py` file. Static typing ^^^^^^^^^^^^^ * ``cython.declare`` declares a typed variable in the current scope, which can be used in place of the :samp:`cdef type var [= value]` construct. This has two forms, the first as an assignment (useful as it creates a declaration in interpreted mode as well): .. literalinclude:: ../../examples/tutorial/pure/cython_declare.py and the second mode as a simple function call: .. literalinclude:: ../../examples/tutorial/pure/cython_declare2.py It can also be used to define extension type private, readonly and public attributes: .. literalinclude:: ../../examples/tutorial/pure/cclass.py * ``@cython.locals`` is a decorator that is used to specify the types of local variables in the function body (including the arguments): .. literalinclude:: ../../examples/tutorial/pure/locals.py * ``@cython.returns()`` specifies the function's return type. * ``@cython.exceptval(value=None, *, check=False)`` specifies the function's exception return value and exception check semantics as follows:: @exceptval(-1) # cdef int func() except -1: @exceptval(-1, check=False) # cdef int func() except -1: @exceptval(check=True) # cdef int func() except *: @exceptval(-1, check=True) # cdef int func() except? -1: * Python annotations can be used to declare argument types, as shown in the following example. To avoid conflicts with other kinds of annotation usages, this can be disabled with the directive ``annotation_typing=False``. .. literalinclude:: ../../examples/tutorial/pure/annotations.py This can be combined with the ``@cython.exceptval()`` decorator for non-Python return types: .. literalinclude:: ../../examples/tutorial/pure/exceptval.py Since version 0.27, Cython also supports the variable annotations defined in `PEP 526 `_. This allows to declare types of variables in a Python 3.6 compatible way as follows: .. literalinclude:: ../../examples/tutorial/pure/pep_526.py There is currently no way to express the visibility of object attributes. C types ^^^^^^^ There are numerous types built into the Cython module. It provides all the standard C types, namely ``char``, ``short``, ``int``, ``long``, ``longlong`` as well as their unsigned versions ``uchar``, ``ushort``, ``uint``, ``ulong``, ``ulonglong``. The special ``bint`` type is used for C boolean values and ``Py_ssize_t`` for (signed) sizes of Python containers. For each type, there are pointer types ``p_int``, ``pp_int``, etc., up to three levels deep in interpreted mode, and infinitely deep in compiled mode. Further pointer types can be constructed with ``cython.pointer(cython.int)``, and arrays as ``cython.int[10]``. A limited attempt is made to emulate these more complex types, but only so much can be done from the Python language. The Python types int, long and bool are interpreted as C ``int``, ``long`` and ``bint`` respectively. Also, the Python builtin types ``list``, ``dict``, ``tuple``, etc. may be used, as well as any user defined types. Typed C-tuples can be declared as a tuple of C types. Extension types and cdef functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ * The class decorator ``@cython.cclass`` creates a ``cdef class``. * The function/method decorator ``@cython.cfunc`` creates a :keyword:`cdef` function. * ``@cython.ccall`` creates a :keyword:`cpdef` function, i.e. one that Cython code can call at the C level. * ``@cython.locals`` declares local variables (see above). It can also be used to declare types for arguments, i.e. the local variables that are used in the signature. * ``@cython.inline`` is the equivalent of the C ``inline`` modifier. * ``@cython.final`` terminates the inheritance chain by preventing a type from being used as a base class, or a method from being overridden in subtypes. This enables certain optimisations such as inlined method calls. Here is an example of a :keyword:`cdef` function:: @cython.cfunc @cython.returns(cython.bint) @cython.locals(a=cython.int, b=cython.int) def c_compare(a,b): return a == b Further Cython functions and declarations ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ * ``address`` is used in place of the ``&`` operator:: cython.declare(x=cython.int, x_ptr=cython.p_int) x_ptr = cython.address(x) * ``sizeof`` emulates the `sizeof` operator. It can take both types and expressions. :: cython.declare(n=cython.longlong) print(cython.sizeof(cython.longlong)) print(cython.sizeof(n)) * ``struct`` can be used to create struct types.:: MyStruct = cython.struct(x=cython.int, y=cython.int, data=cython.double) a = cython.declare(MyStruct) is equivalent to the code:: cdef struct MyStruct: int x int y double data cdef MyStruct a * ``union`` creates union types with exactly the same syntax as ``struct``. * ``typedef`` defines a type under a given name:: T = cython.typedef(cython.p_int) # ctypedef int* T * ``cast`` will (unsafely) reinterpret an expression type. ``cython.cast(T, t)`` is equivalent to ``t``. The first attribute must be a type, the second is the expression to cast. Specifying the optional keyword argument ``typecheck=True`` has the semantics of ``t``. :: t1 = cython.cast(T, t) t2 = cython.cast(T, t, typecheck=True) .. _magic_attributes_pxd: Magic Attributes within the .pxd ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The special `cython` module can also be imported and used within the augmenting :file:`.pxd` file. For example, the following Python file :file:`dostuff.py`: .. literalinclude:: ../../examples/tutorial/pure/dostuff.py can be augmented with the following :file:`.pxd` file :file:`dostuff.pxd`: .. literalinclude:: ../../examples/tutorial/pure/dostuff.pxd The :func:`cython.declare()` function can be used to specify types for global variables in the augmenting :file:`.pxd` file. Tips and Tricks --------------- Calling C functions ^^^^^^^^^^^^^^^^^^^ Normally, it isn't possible to call C functions in pure Python mode as there is no general way to support it in normal (uncompiled) Python. However, in cases where an equivalent Python function exists, this can be achieved by combining C function coercion with a conditional import as follows: .. literalinclude:: ../../examples/tutorial/pure/mymodule.pxd .. literalinclude:: ../../examples/tutorial/pure/mymodule.py Note that the "sin" function will show up in the module namespace of "mymodule" here (i.e. there will be a ``mymodule.sin()`` function). You can mark it as an internal name according to Python conventions by renaming it to "_sin" in the ``.pxd`` file as follows:: cdef extern from "math.h": cpdef double _sin "sin" (double x) You would then also change the Python import to ``from math import sin as _sin`` to make the names match again. Using C arrays for fixed size lists ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ C arrays can automatically coerce to Python lists or tuples. This can be exploited to replace fixed size Python lists in Python code by C arrays when compiled. An example: .. literalinclude:: ../../examples/tutorial/pure/c_arrays.py In normal Python, this will use a Python list to collect the counts, whereas Cython will generate C code that uses a C array of C ints.