.. highlight:: c

.. _howto-clinic:

**********************
Argument Clinic How-To
**********************

:author: Larry Hastings

**Source code:** :source:`Tools/clinic/clinic.py`.

.. topic:: Abstract

  Argument Clinic is a preprocessor for CPython C files.
  It was introduced in Python 3.4 with :pep:`436`,
  in order to provide introspection signatures,
  and to generate performant and tailor-made boilerplate code
  for argument parsing in CPython builtins,
  module level functions, and class methods.
  This document is divided in four major sections:

  * :ref:`clinic-background` talks about the basic concepts and goals of
    Argument Clinic.
  * :ref:`clinic-reference` describes the command-line interface and Argument
    Clinic terminology.
  * :ref:`clinic-tutorial` guides you through all the steps required to
    adapt an existing C function to Argument Clinic.
  * :ref:`clinic-howtos` details how to handle specific tasks.


.. note::

  Argument Clinic is considered internal-only
  for CPython.  Its use is not supported for files outside
  CPython, and no guarantees are made regarding backwards
  compatibility for future versions.  In other words: if you
  maintain an external C extension for CPython, you're welcome
  to experiment with Argument Clinic in your own code.  But the
  version of Argument Clinic that ships with the next version
  of CPython *could* be totally incompatible and break all your code.


.. _clinic-background:

Background
==========

Basic concepts
--------------

When Argument Clinic is run on a file, either via the :ref:`clinic-cli`
or via ``make clinic``, it will scan over the input files looking for
:term:`start lines <start line>`:

.. code-block:: none

    /*[clinic input]

When it finds one, it reads everything up to the :term:`end line`:

.. code-block:: none

    [clinic start generated code]*/

Everything in between these two lines is Argument Clinic :term:`input`.
When Argument Clinic parses input, it generates :term:`output`.
The output is rewritten into the C file immediately after the input,
followed by a :term:`checksum line`.
All of these lines, including the :term:`start line` and :term:`checksum line`,
are collectively called an Argument Clinic :term:`block`:

.. code-block:: none

    /*[clinic input]
    ... clinic input goes here ...
    [clinic start generated code]*/
    ... clinic output goes here ...
    /*[clinic end generated code: ...]*/

If you run Argument Clinic on the same file a second time, Argument Clinic
will discard the old :term:`output` and write out the new output with a fresh
:term:`checksum line`.
If the :term:`input` hasn't changed, the output won't change either.

.. note::

   You should never modify the output of an Argument Clinic block,
   as any change will be lost in future Argument Clinic runs;
   Argument Clinic will detect an output checksum mismatch and regenerate the
   correct output.
   If you are not happy with the generated output,
   you should instead change the input until it produces the output you want.


.. _clinic-reference:

Reference
=========


.. _clinic-terminology:

Terminology
-----------

.. glossary::

   start line
      The line ``/*[clinic input]``.
      This line marks the beginning of Argument Clinic input.
      Note that the *start line* opens a C block comment.

   end line
      The line ``[clinic start generated code]*/``.
      The *end line* marks the _end_ of Argument Clinic :term:`input`,
      but at the same time marks the _start_ of Argument Clinic :term:`output`,
      thus the text *"clinic start start generated code"*
      Note that the *end line* closes the C block comment opened
      by the *start line*.

   checksum
      A hash to distinguish unique :term:`inputs <input>`
      and :term:`outputs <output>`.

   checksum line
      A line that looks like ``/*[clinic end generated code: ...]*/``.
      The three dots will be replaced by a :term:`checksum` generated from the
      :term:`input`, and a :term:`checksum` generated from the :term:`output`.
      The checksum line marks the end of Argument Clinic generated code,
      and is used by Argument Clinic to determine if it needs to regenerate
      output.

   input
      The text between the :term:`start line` and the :term:`end line`.
      Note that the start and end lines open and close a C block comment;
      the *input* is thus a part of that same C block comment.

   output
      The text between the :term:`end line` and the :term:`checksum line`.

   block
      All text from the :term:`start line` to the :term:`checksum line` inclusively.


.. _clinic-cli:

Command-line interface
----------------------

The Argument Clinic :abbr:`CLI (Command-Line Interface)` is typically used to
process a single source file, like this:

.. code-block:: shell-session

    $ python3 ./Tools/clinic/clinic.py foo.c

The CLI supports the following options:

.. program:: ./Tools/clinic/clinic.py [-h] [-f] [-o OUTPUT] [-v] \
             [--converters] [--make] [--srcdir SRCDIR] [FILE ...]

.. option:: -h, --help

   Print CLI usage.

.. option:: -f, --force

   Force output regeneration.

.. option:: -o, --output OUTPUT

   Redirect file output to OUTPUT

.. option:: -v, --verbose

   Enable verbose mode.

.. option:: --converters

   Print a list of all supported converters and return converters.

.. option:: --make

   Walk :option:`--srcdir` to run over all relevant files.

.. option:: --srcdir SRCDIR

   The directory tree to walk in :option:`--make` mode.

.. option:: FILE ...

   The list of files to process.


.. _clinic-tutorial:

Tutorial
========

The best way to get a sense of how Argument Clinic works is to
convert a function to work with it.  Here, then, are the bare
minimum steps you'd need to follow to convert a function to
work with Argument Clinic.  Note that for code you plan to
check in to CPython, you really should take the conversion farther,
using some of the :ref:`advanced concepts <clinic-howtos>`
you'll see later on in the document,
like :ref:`clinic-howto-return-converters`
and :ref:`clinic-howto-self-converter`.
But we'll keep it simple for this walkthrough so you can learn.

First, make sure you're working with a freshly updated checkout
of the CPython trunk.

Next, find a Python builtin that calls either :c:func:`PyArg_ParseTuple`
or :c:func:`PyArg_ParseTupleAndKeywords`, and hasn't been converted
to work with Argument Clinic yet.
For this tutorial, we'll be using
:py:meth:`_pickle.Pickler.dump <pickle.Pickler.dump>`.

If the call to the :c:func:`!PyArg_Parse*` function uses any of the
following format units...:

   .. code-block:: none

       O&
       O!
       es
       es#
       et
       et#

... or if it has multiple calls to :c:func:`PyArg_ParseTuple`,
you should choose a different function.
(See :ref:`clinic-howto-advanced-converters` for those scenarios.)

Also, if the function has multiple calls to :c:func:`!PyArg_ParseTuple`
or :c:func:`PyArg_ParseTupleAndKeywords` where it supports different
types for the same argument, or if the function uses something besides
:c:func:`!PyArg_Parse*` functions to parse its arguments, it probably
isn't suitable for conversion to Argument Clinic.  Argument Clinic
doesn't support generic functions or polymorphic parameters.

Next, add the following boilerplate above the function,
creating our input block::

    /*[clinic input]
    [clinic start generated code]*/

Cut the docstring and paste it in between the ``[clinic]`` lines,
removing all the junk that makes it a properly quoted C string.
When you're done you should have just the text, based at the left
margin, with no line wider than 80 characters.
Argument Clinic will preserve indents inside the docstring.

If the old docstring had a first line that looked like a function
signature, throw that line away; The docstring doesn't need it anymore ---
when you use :py:func:`help` on your builtin in the future,
the first line will be built automatically based on the function's signature.

Example docstring summary line::

   /*[clinic input]
   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

If your docstring doesn't have a "summary" line, Argument Clinic will
complain, so let's make sure it has one.  The "summary" line should
be a paragraph consisting of a single 80-column line
at the beginning of the docstring.
(See :pep:`257` regarding docstring conventions.)

Our example docstring consists solely of a summary line, so the sample
code doesn't have to change for this step.

Now, above the docstring, enter the name of the function, followed
by a blank line.  This should be the Python name of the function,
and should be the full dotted path to the function ---
it should start with the name of the module,
include any sub-modules, and if the function is a method on
a class it should include the class name too.

In our example, :mod:`!_pickle` is the module, :py:class:`!Pickler` is the class,
and :py:meth:`!dump` is the method, so the name becomes
:py:meth:`!_pickle.Pickler.dump`::

   /*[clinic input]
   _pickle.Pickler.dump

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

If this is the first time that module or class has been used with Argument
Clinic in this C file,
you must declare the module and/or class.  Proper Argument Clinic hygiene
prefers declaring these in a separate block somewhere near the
top of the C file, in the same way that include files and statics go at
the top.
In our sample code we'll just show the two blocks next to each other.

The name of the class and module should be the same as the one
seen by Python.  Check the name defined in the :c:type:`PyModuleDef`
or :c:type:`PyTypeObject` as appropriate.

When you declare a class, you must also specify two aspects of its type
in C: the type declaration you'd use for a pointer to an instance of
this class, and a pointer to the :c:type:`!PyTypeObject` for this class::

   /*[clinic input]
   module _pickle
   class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
   [clinic start generated code]*/

   /*[clinic input]
   _pickle.Pickler.dump

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

Declare each of the parameters to the function.  Each parameter
should get its own line.  All the parameter lines should be
indented from the function name and the docstring.
The general form of these parameter lines is as follows:

.. code-block:: none

    name_of_parameter: converter

If the parameter has a default value, add that after the
converter:

.. code-block:: none

    name_of_parameter: converter = default_value

Argument Clinic's support for "default values" is quite sophisticated;
see :ref:`clinic-howto-default-values` for more information.

Next, add a blank line below the parameters.

What's a "converter"?
It establishes both the type of the variable used in C,
and the method to convert the Python value into a C value at runtime.
For now you're going to use what's called a "legacy converter" ---
a convenience syntax intended to make porting old code into Argument
Clinic easier.

For each parameter, copy the "format unit" for that
parameter from the :c:func:`PyArg_Parse` format argument and
specify *that* as its converter, as a quoted string.
The "format unit" is the formal name for the one-to-three
character substring of the *format* parameter that tells
the argument parsing function what the type of the variable
is and how to convert it.
For more on format units please see :ref:`arg-parsing`.

For multicharacter format units like ``z#``,
use the entire two-or-three character string.

Sample::

   /*[clinic input]
   module _pickle
   class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
   [clinic start generated code]*/

   /*[clinic input]
   _pickle.Pickler.dump

       obj: 'O'

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

If your function has ``|`` in the format string,
meaning some parameters have default values, you can ignore it.
Argument Clinic infers which parameters are optional
based on whether or not they have default values.

If your function has ``$`` in the format string,
meaning it takes keyword-only arguments,
specify ``*`` on a line by itself before the first keyword-only argument,
indented the same as the parameter lines.

:py:meth:`!_pickle.Pickler.dump` has neither, so our sample is unchanged.

Next, if the existing C function calls :c:func:`PyArg_ParseTuple`
(as opposed to :c:func:`PyArg_ParseTupleAndKeywords`), then all its
arguments are positional-only.

To mark parameters as positional-only in Argument Clinic,
add a ``/`` on a line by itself after the last positional-only parameter,
indented the same as the parameter lines.

Sample::

   /*[clinic input]
   module _pickle
   class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
   [clinic start generated code]*/

   /*[clinic input]
   _pickle.Pickler.dump

       obj: 'O'
       /

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

It can be helpful to write a per-parameter docstring for each parameter.
Since per-parameter docstrings are optional,
you can skip this step if you prefer.

Nevertheless, here's how to add a per-parameter docstring.
The first line of the per-parameter docstring
must be indented further than the parameter definition.
The left margin of this first line establishes
the left margin for the whole per-parameter docstring;
all the text you write will be outdented by this amount.
You can write as much text as you like, across multiple lines if you wish.

Sample::

   /*[clinic input]
   module _pickle
   class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
   [clinic start generated code]*/

   /*[clinic input]
   _pickle.Pickler.dump

       obj: 'O'
           The object to be pickled.
       /

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

Save and close the file, then run ``Tools/clinic/clinic.py`` on it.
With luck everything worked---your block now has output,
and a :file:`.c.h` file has been generated!
Reload the file in your text editor to see the generated code::

   /*[clinic input]
   _pickle.Pickler.dump

       obj: 'O'
           The object to be pickled.
       /

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

   static PyObject *
   _pickle_Pickler_dump(PicklerObject *self, PyObject *obj)
   /*[clinic end generated code: output=87ecad1261e02ac7 input=552eb1c0f52260d9]*/

Obviously, if Argument Clinic didn't produce any output,
it's because it found an error in your input.
Keep fixing your errors and retrying until Argument Clinic processes your file
without complaint.

For readability, most of the glue code has been generated to a :file:`.c.h`
file.  You'll need to include that in your original :file:`.c` file,
typically right after the clinic module block::

   #include "clinic/_pickle.c.h"

Double-check that the argument-parsing code Argument Clinic generated
looks basically the same as the existing code.

First, ensure both places use the same argument-parsing function.
The existing code must call either
:c:func:`PyArg_ParseTuple` or :c:func:`PyArg_ParseTupleAndKeywords`;
ensure that the code generated by Argument Clinic calls the
*exact* same function.

Second, the format string passed in to :c:func:`!PyArg_ParseTuple` or
:c:func:`!PyArg_ParseTupleAndKeywords` should be *exactly* the same
as the hand-written one in the existing function,
up to the colon or semi-colon.

Argument Clinic always generates its format strings
with a ``:`` followed by the name of the function.
If the existing code's format string ends with ``;``,
to provide usage help, this change is harmless --- don't worry about it.

Third, for parameters whose format units require two arguments,
like a length variable, an encoding string, or a pointer
to a conversion function, ensure that the second argument is
*exactly* the same between the two invocations.

Fourth, inside the output portion of the block,
you'll find a preprocessor macro defining the appropriate static
:c:type:`PyMethodDef` structure for this builtin::

   #define __PICKLE_PICKLER_DUMP_METHODDEF    \
   {"dump", (PyCFunction)__pickle_Pickler_dump, METH_O, __pickle_Pickler_dump__doc__},

This static structure should be *exactly* the same as the existing static
:c:type:`!PyMethodDef` structure for this builtin.

If any of these items differ in *any way*,
adjust your Argument Clinic function specification and rerun
``Tools/clinic/clinic.py`` until they *are* the same.

Notice that the last line of its output is the declaration
of your "impl" function.  This is where the builtin's implementation goes.
Delete the existing prototype of the function you're modifying, but leave
the opening curly brace.  Now delete its argument parsing code and the
declarations of all the variables it dumps the arguments into.
Notice how the Python arguments are now arguments to this impl function;
if the implementation used different names for these variables, fix it.

Let's reiterate, just because it's kind of weird.
Your code should now look like this::

   static return_type
   your_function_impl(...)
   /*[clinic end generated code: input=..., output=...]*/
   {
   ...

Argument Clinic generated the checksum line and the function prototype just
above it.  You should write the opening and closing curly braces for the
function, and the implementation inside.

Sample::

   /*[clinic input]
   module _pickle
   class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
   [clinic start generated code]*/
   /*[clinic end generated code: checksum=da39a3ee5e6b4b0d3255bfef95601890afd80709]*/

   /*[clinic input]
   _pickle.Pickler.dump

       obj: 'O'
           The object to be pickled.
       /

   Write a pickled representation of obj to the open file.
   [clinic start generated code]*/

   PyDoc_STRVAR(__pickle_Pickler_dump__doc__,
   "Write a pickled representation of obj to the open file.\n"
   "\n"
   ...
   static PyObject *
   _pickle_Pickler_dump_impl(PicklerObject *self, PyObject *obj)
   /*[clinic end generated code: checksum=3bd30745bf206a48f8b576a1da3d90f55a0a4187]*/
   {
       /* Check whether the Pickler was initialized correctly (issue3664).
          Developers often forget to call __init__() in their subclasses, which
          would trigger a segfault without this check. */
       if (self->write == NULL) {
           PyErr_Format(PicklingError,
                        "Pickler.__init__() was not called by %s.__init__()",
                        Py_TYPE(self)->tp_name);
           return NULL;
       }

       if (_Pickler_ClearBuffer(self) < 0) {
           return NULL;
       }

       ...

Remember the macro with the :c:type:`PyMethodDef` structure for this function?
Find the existing :c:type:`!PyMethodDef` structure for this
function and replace it with a reference to the macro.  If the builtin
is at module scope, this will probably be very near the end of the file;
if the builtin is a class method, this will probably be below but relatively
near to the implementation.

Note that the body of the macro contains a trailing comma; when you
replace the existing static :c:type:`!PyMethodDef` structure with the macro,
*don't* add a comma to the end.

Sample::

   static struct PyMethodDef Pickler_methods[] = {
       __PICKLE_PICKLER_DUMP_METHODDEF
       __PICKLE_PICKLER_CLEAR_MEMO_METHODDEF
       {NULL, NULL}                /* sentinel */
   };

Argument Clinic may generate new instances of ``_Py_ID``. For example::

   &_Py_ID(new_unique_py_id)

If it does, you'll have to run ``make regen-global-objects``
to regenerate the list of precompiled identifiers at this point.

Finally, compile, then run the relevant portions of the regression-test suite.
This change should not introduce any new compile-time warnings or errors,
and there should be no externally visible change to Python's behavior,
except for one difference: :py:func:`inspect.signature` run on your function
should now provide a valid signature!

Congratulations, you've ported your first function to work with Argument Clinic!


.. _clinic-howtos:

How-to guides
=============


How to rename C functions and variables generated by Argument Clinic
--------------------------------------------------------------------

Argument Clinic automatically names the functions it generates for you.
Occasionally this may cause a problem, if the generated name collides with
the name of an existing C function.  There's an easy solution: override the names
used for the C functions.  Just add the keyword ``"as"``
to your function declaration line, followed by the function name you wish to use.
Argument Clinic will use that function name for the base (generated) function,
then add ``"_impl"`` to the end and use that for the name of the impl function.

For example, if we wanted to rename the C function names generated for
:py:meth:`pickle.Pickler.dump`, it'd look like this::

    /*[clinic input]
    pickle.Pickler.dump as pickler_dumper

    ...

The base function would now be named :c:func:`!pickler_dumper`,
and the impl function would now be named :c:func:`!pickler_dumper_impl`.


Similarly, you may have a problem where you want to give a parameter
a specific Python name, but that name may be inconvenient in C.  Argument
Clinic allows you to give a parameter different names in Python and in C,
using the same ``"as"`` syntax::

    /*[clinic input]
    pickle.Pickler.dump

        obj: object
        file as file_obj: object
        protocol: object = NULL
        *
        fix_imports: bool = True

Here, the name used in Python (in the signature and the ``keywords``
array) would be *file*, but the C variable would be named ``file_obj``.

You can use this to rename the *self* parameter too!


How to convert functions using ``PyArg_UnpackTuple``
----------------------------------------------------

To convert a function parsing its arguments with :c:func:`PyArg_UnpackTuple`,
simply write out all the arguments, specifying each as an ``object``.  You
may specify the *type* argument to cast the type as appropriate.  All
arguments should be marked positional-only (add a ``/`` on a line by itself
after the last argument).

Currently the generated code will use :c:func:`PyArg_ParseTuple`, but this
will change soon.


How to use optional groups
--------------------------

Some legacy functions have a tricky approach to parsing their arguments:
they count the number of positional arguments, then use a ``switch`` statement
to call one of several different :c:func:`PyArg_ParseTuple` calls depending on
how many positional arguments there are.  (These functions cannot accept
keyword-only arguments.)  This approach was used to simulate optional
arguments back before :c:func:`PyArg_ParseTupleAndKeywords` was created.

While functions using this approach can often be converted to
use :c:func:`!PyArg_ParseTupleAndKeywords`, optional arguments, and default values,
it's not always possible.  Some of these legacy functions have
behaviors :c:func:`!PyArg_ParseTupleAndKeywords` doesn't directly support.
The most obvious example is the builtin function :py:func:`range`, which has
an optional argument on the *left* side of its required argument!
Another example is :py:meth:`curses.window.addch`, which has a group of two
arguments that must always be specified together.  (The arguments are
called *x* and *y*; if you call the function passing in *x*,
you must also pass in *y* — and if you don't pass in *x* you may not
pass in *y* either.)

In any case, the goal of Argument Clinic is to support argument parsing
for all existing CPython builtins without changing their semantics.
Therefore Argument Clinic supports
this alternate approach to parsing, using what are called *optional groups*.
Optional groups are groups of arguments that must all be passed in together.
They can be to the left or the right of the required arguments.  They
can *only* be used with positional-only parameters.

.. note:: Optional groups are *only* intended for use when converting
          functions that make multiple calls to :c:func:`PyArg_ParseTuple`!
          Functions that use *any* other approach for parsing arguments
          should *almost never* be converted to Argument Clinic using
          optional groups.  Functions using optional groups currently
          cannot have accurate signatures in Python, because Python just
          doesn't understand the concept.  Please avoid using optional
          groups wherever possible.

To specify an optional group, add a ``[`` on a line by itself before
the parameters you wish to group together, and a ``]`` on a line by itself
after these parameters.  As an example, here's how :py:meth:`curses.window.addch`
uses optional groups to make the first two parameters and the last
parameter optional::

    /*[clinic input]

    curses.window.addch

        [
        x: int
          X-coordinate.
        y: int
          Y-coordinate.
        ]

        ch: object
          Character to add.

        [
        attr: long
          Attributes for the character.
        ]
        /

    ...


Notes:

* For every optional group, one additional parameter will be passed into the
  impl function representing the group.  The parameter will be an int named
  ``group_{direction}_{number}``,
  where ``{direction}`` is either ``right`` or ``left`` depending on whether the group
  is before or after the required parameters, and ``{number}`` is a monotonically
  increasing number (starting at 1) indicating how far away the group is from
  the required parameters.  When the impl is called, this parameter will be set
  to zero if this group was unused, and set to non-zero if this group was used.
  (By used or unused, I mean whether or not the parameters received arguments
  in this invocation.)

* If there are no required arguments, the optional groups will behave
  as if they're to the right of the required arguments.

* In the case of ambiguity, the argument parsing code
  favors parameters on the left (before the required parameters).

* Optional groups can only contain positional-only parameters.

* Optional groups are *only* intended for legacy code.  Please do not
  use optional groups for new code.


How to use real Argument Clinic converters, instead of "legacy converters"
--------------------------------------------------------------------------

To save time, and to minimize how much you need to learn
to achieve your first port to Argument Clinic, the walkthrough above tells
you to use "legacy converters".  "Legacy converters" are a convenience,
designed explicitly to make porting existing code to Argument Clinic
easier.  And to be clear, their use is acceptable when porting code for
Python 3.4.

However, in the long term we probably want all our blocks to
use Argument Clinic's real syntax for converters.  Why?  A couple
reasons:

* The proper converters are far easier to read and clearer in their intent.
* There are some format units that are unsupported as "legacy converters",
  because they require arguments, and the legacy converter syntax doesn't
  support specifying arguments.
* In the future we may have a new argument parsing library that isn't
  restricted to what :c:func:`PyArg_ParseTuple` supports; this flexibility
  won't be available to parameters using legacy converters.

Therefore, if you don't mind a little extra effort, please use the normal
converters instead of legacy converters.

In a nutshell, the syntax for Argument Clinic (non-legacy) converters
looks like a Python function call.  However, if there are no explicit
arguments to the function (all functions take their default values),
you may omit the parentheses.  Thus ``bool`` and ``bool()`` are exactly
the same converters.

All arguments to Argument Clinic converters are keyword-only.
All Argument Clinic converters accept the following arguments:

  *c_default*
    The default value for this parameter when defined in C.
    Specifically, this will be the initializer for the variable declared
    in the "parse function".  See :ref:`the section on default values <default_values>`
    for how to use this.
    Specified as a string.

  *annotation*
    The annotation value for this parameter.  Not currently supported,
    because :pep:`8` mandates that the Python library may not use
    annotations.

  *unused*
    Wrap the argument with :c:macro:`Py_UNUSED` in the impl function signature.

In addition, some converters accept additional arguments.  Here is a list
of these arguments, along with their meanings:

  *accept*
    A set of Python types (and possibly pseudo-types);
    this restricts the allowable Python argument to values of these types.
    (This is not a general-purpose facility; as a rule it only supports
    specific lists of types as shown in the legacy converter table.)

    To accept ``None``, add ``NoneType`` to this set.

  *bitwise*
    Only supported for unsigned integers.  The native integer value of this
    Python argument will be written to the parameter without any range checking,
    even for negative values.

  *converter*
    Only supported by the ``object`` converter.  Specifies the name of a
    :ref:`C "converter function" <o_ampersand>`
    to use to convert this object to a native type.

  *encoding*
    Only supported for strings.  Specifies the encoding to use when converting
    this string from a Python str (Unicode) value into a C ``char *`` value.


  *subclass_of*
    Only supported for the ``object`` converter.  Requires that the Python
    value be a subclass of a Python type, as expressed in C.

  *type*
    Only supported for the ``object`` and ``self`` converters.  Specifies
    the C type that will be used to declare the variable.  Default value is
    ``"PyObject *"``.

  *zeroes*
    Only supported for strings.  If true, embedded NUL bytes (``'\\0'``) are
    permitted inside the value.  The length of the string will be passed in
    to the impl function, just after the string parameter, as a parameter named
    ``<parameter_name>_length``.

Please note, not every possible combination of arguments will work.
Usually these arguments are implemented by specific :c:func:`PyArg_ParseTuple`
*format units*, with specific behavior.  For example, currently you cannot
call ``unsigned_short`` without also specifying ``bitwise=True``.
Although it's perfectly reasonable to think this would work, these semantics don't
map to any existing format unit.  So Argument Clinic doesn't support it.  (Or, at
least, not yet.)

Below is a table showing the mapping of legacy converters into real
Argument Clinic converters.  On the left is the legacy converter,
on the right is the text you'd replace it with.

=========   =================================================================================
``'B'``     ``unsigned_char(bitwise=True)``
``'b'``     ``unsigned_char``
``'c'``     ``char``
``'C'``     ``int(accept={str})``
``'d'``     ``double``
``'D'``     ``Py_complex``
``'es'``    ``str(encoding='name_of_encoding')``
``'es#'``   ``str(encoding='name_of_encoding', zeroes=True)``
``'et'``    ``str(encoding='name_of_encoding', accept={bytes, bytearray, str})``
``'et#'``   ``str(encoding='name_of_encoding', accept={bytes, bytearray, str}, zeroes=True)``
``'f'``     ``float``
``'h'``     ``short``
``'H'``     ``unsigned_short(bitwise=True)``
``'i'``     ``int``
``'I'``     ``unsigned_int(bitwise=True)``
``'k'``     ``unsigned_long(bitwise=True)``
``'K'``     ``unsigned_long_long(bitwise=True)``
``'l'``     ``long``
``'L'``     ``long long``
``'n'``     ``Py_ssize_t``
``'O'``     ``object``
``'O!'``    ``object(subclass_of='&PySomething_Type')``
``'O&'``    ``object(converter='name_of_c_function')``
``'p'``     ``bool``
``'S'``     ``PyBytesObject``
``'s'``     ``str``
``'s#'``    ``str(zeroes=True)``
``'s*'``    ``Py_buffer(accept={buffer, str})``
``'U'``     ``unicode``
``'u'``     ``wchar_t``
``'u#'``    ``wchar_t(zeroes=True)``
``'w*'``    ``Py_buffer(accept={rwbuffer})``
``'Y'``     ``PyByteArrayObject``
``'y'``     ``str(accept={bytes})``
``'y#'``    ``str(accept={robuffer}, zeroes=True)``
``'y*'``    ``Py_buffer``
``'Z'``     ``wchar_t(accept={str, NoneType})``
``'Z#'``    ``wchar_t(accept={str, NoneType}, zeroes=True)``
``'z'``     ``str(accept={str, NoneType})``
``'z#'``    ``str(accept={str, NoneType}, zeroes=True)``
``'z*'``    ``Py_buffer(accept={buffer, str, NoneType})``
=========   =================================================================================

As an example, here's our sample ``pickle.Pickler.dump`` using the proper
converter::

    /*[clinic input]
    pickle.Pickler.dump

        obj: object
            The object to be pickled.
        /

    Write a pickled representation of obj to the open file.
    [clinic start generated code]*/

One advantage of real converters is that they're more flexible than legacy
converters.  For example, the ``unsigned_int`` converter (and all the
``unsigned_`` converters) can be specified without ``bitwise=True``.  Their
default behavior performs range checking on the value, and they won't accept
negative numbers.  You just can't do that with a legacy converter!

Argument Clinic will show you all the converters it has
available.  For each converter it'll show you all the parameters
it accepts, along with the default value for each parameter.
Just run ``Tools/clinic/clinic.py --converters`` to see the full list.


How to use the ``Py_buffer`` converter
--------------------------------------

When using the ``Py_buffer`` converter
(or the ``'s*'``, ``'w*'``, ``'*y'``, or ``'z*'`` legacy converters),
you *must* not call :c:func:`PyBuffer_Release` on the provided buffer.
Argument Clinic generates code that does it for you (in the parsing function).


.. _clinic-howto-advanced-converters:

How to use advanced converters
------------------------------

Remember those format units you skipped for your first
time because they were advanced?  Here's how to handle those too.

The trick is, all those format units take arguments—either
conversion functions, or types, or strings specifying an encoding.
(But "legacy converters" don't support arguments.  That's why we
skipped them for your first function.)  The argument you specified
to the format unit is now an argument to the converter; this
argument is either *converter* (for ``O&``), *subclass_of* (for ``O!``),
or *encoding* (for all the format units that start with ``e``).

When using *subclass_of*, you may also want to use the other
custom argument for ``object()``: *type*, which lets you set the type
actually used for the parameter.  For example, if you want to ensure
that the object is a subclass of :c:var:`PyUnicode_Type`, you probably want
to use the converter ``object(type='PyUnicodeObject *', subclass_of='&PyUnicode_Type')``.

One possible problem with using Argument Clinic: it takes away some possible
flexibility for the format units starting with ``e``.  When writing a
:c:func:`!PyArg_Parse*` call by hand, you could theoretically decide at runtime what
encoding string to pass to that call.   But now this string must
be hard-coded at Argument-Clinic-preprocessing-time.  This limitation is deliberate;
it made supporting this format unit much easier, and may allow for future optimizations.
This restriction doesn't seem unreasonable; CPython itself always passes in static
hard-coded encoding strings for parameters whose format units start with ``e``.


.. _clinic-howto-default-values:
.. _default_values:

How to assign default values to parameter
-----------------------------------------

Default values for parameters can be any of a number of values.
At their simplest, they can be string, int, or float literals:

.. code-block:: none

    foo: str = "abc"
    bar: int = 123
    bat: float = 45.6

They can also use any of Python's built-in constants:

.. code-block:: none

    yep:  bool = True
    nope: bool = False
    nada: object = None

There's also special support for a default value of ``NULL``, and
for simple expressions, documented in the following sections.


The ``NULL`` default value
^^^^^^^^^^^^^^^^^^^^^^^^^^

For string and object parameters, you can set them to ``None`` to indicate
that there's no default.  However, that means the C variable will be
initialized to ``Py_None``.  For convenience's sakes, there's a special
value called ``NULL`` for just this reason: from Python's perspective it
behaves like a default value of ``None``, but the C variable is initialized
with ``NULL``.


Symbolic default values
^^^^^^^^^^^^^^^^^^^^^^^

The default value you provide for a parameter can't be any arbitrary
expression.  Currently the following are explicitly supported:

* Numeric constants (integer and float)
* String constants
* ``True``, ``False``, and ``None``
* Simple symbolic constants like :py:data:`sys.maxsize`, which must
  start with the name of the module

(In the future, this may need to get even more elaborate,
to allow full expressions like ``CONSTANT - 1``.)


Expressions as default values
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The default value for a parameter can be more than just a literal value.
It can be an entire expression, using math operators and looking up attributes
on objects.  However, this support isn't exactly simple, because of some
non-obvious semantics.

Consider the following example:

.. code-block:: none

    foo: Py_ssize_t = sys.maxsize - 1

:py:data:`sys.maxsize` can have different values on different platforms.  Therefore
Argument Clinic can't simply evaluate that expression locally and hard-code it
in C.  So it stores the default in such a way that it will get evaluated at
runtime, when the user asks for the function's signature.

What namespace is available when the expression is evaluated?  It's evaluated
in the context of the module the builtin came from.  So, if your module has an
attribute called :py:attr:`!max_widgets`, you may simply use it:

.. code-block:: none

    foo: Py_ssize_t = max_widgets

If the symbol isn't found in the current module, it fails over to looking in
:py:data:`sys.modules`.  That's how it can find :py:data:`sys.maxsize` for example.
(Since you don't know in advance what modules the user will load into their interpreter,
it's best to restrict yourself to modules that are preloaded by Python itself.)

Evaluating default values only at runtime means Argument Clinic can't compute
the correct equivalent C default value.  So you need to tell it explicitly.
When you use an expression, you must also specify the equivalent expression
in C, using the *c_default* parameter to the converter:

.. code-block:: none

    foo: Py_ssize_t(c_default="PY_SSIZE_T_MAX - 1") = sys.maxsize - 1

Another complication: Argument Clinic can't know in advance whether or not the
expression you supply is valid.  It parses it to make sure it looks legal, but
it can't *actually* know.  You must be very careful when using expressions to
specify values that are guaranteed to be valid at runtime!

Finally, because expressions must be representable as static C values, there
are many restrictions on legal expressions.  Here's a list of Python features
you're not permitted to use:

* Function calls.
* Inline if statements (``3 if foo else 5``).
* Automatic sequence unpacking (``*[1, 2, 3]``).
* List/set/dict comprehensions and generator expressions.
* Tuple/list/set/dict literals.


.. _clinic-howto-return-converters:

How to use return converters
----------------------------

By default, the impl function Argument Clinic generates for you returns
:c:type:`PyObject * <PyObject>`.
But your C function often computes some C type,
then converts it into the :c:type:`!PyObject *`
at the last moment.  Argument Clinic handles converting your inputs from Python types
into native C types—why not have it convert your return value from a native C type
into a Python type too?

That's what a "return converter" does.  It changes your impl function to return
some C type, then adds code to the generated (non-impl) function to handle converting
that value into the appropriate :c:type:`!PyObject *`.

The syntax for return converters is similar to that of parameter converters.
You specify the return converter like it was a return annotation on the
function itself, using ``->`` notation.

For example:

.. code-block:: c

   /*[clinic input]
   add -> int

       a: int
       b: int
       /

   [clinic start generated code]*/

Return converters behave much the same as parameter converters;
they take arguments, the arguments are all keyword-only, and if you're not changing
any of the default arguments you can omit the parentheses.

(If you use both ``"as"`` *and* a return converter for your function,
the ``"as"`` should come before the return converter.)

There's one additional complication when using return converters: how do you
indicate an error has occurred?  Normally, a function returns a valid (non-``NULL``)
pointer for success, and ``NULL`` for failure.  But if you use an integer return converter,
all integers are valid.  How can Argument Clinic detect an error?  Its solution: each return
converter implicitly looks for a special value that indicates an error.  If you return
that value, and an error has been set (c:func:`PyErr_Occurred` returns a true
value), then the generated code will propagate the error.  Otherwise it will
encode the value you return like normal.

Currently Argument Clinic supports only a few return converters:

.. code-block:: none

    bool
    double
    float
    int
    long
    Py_ssize_t
    size_t
    unsigned int
    unsigned long

None of these take parameters.
For all of these, return ``-1`` to indicate error.

To see all the return converters Argument Clinic supports, along with
their parameters (if any),
just run ``Tools/clinic/clinic.py --converters`` for the full list.


How to clone existing functions
-------------------------------

If you have a number of functions that look similar, you may be able to
use Clinic's "clone" feature.  When you clone an existing function,
you reuse:

* its parameters, including

  * their names,

  * their converters, with all parameters,

  * their default values,

  * their per-parameter docstrings,

  * their *kind* (whether they're positional only,
    positional or keyword, or keyword only), and

* its return converter.

The only thing not copied from the original function is its docstring;
the syntax allows you to specify a new docstring.

Here's the syntax for cloning a function::

    /*[clinic input]
    module.class.new_function [as c_basename] = module.class.existing_function

    Docstring for new_function goes here.
    [clinic start generated code]*/

(The functions can be in different modules or classes.  I wrote
``module.class`` in the sample just to illustrate that you must
use the full path to *both* functions.)

Sorry, there's no syntax for partially cloning a function, or cloning a function
then modifying it.  Cloning is an all-or nothing proposition.

Also, the function you are cloning from must have been previously defined
in the current file.


How to call Python code
-----------------------

The rest of the advanced topics require you to write Python code
which lives inside your C file and modifies Argument Clinic's
runtime state.  This is simple: you simply define a Python block.

A Python block uses different delimiter lines than an Argument
Clinic function block.  It looks like this::

    /*[python input]
    # python code goes here
    [python start generated code]*/

All the code inside the Python block is executed at the
time it's parsed.  All text written to stdout inside the block
is redirected into the "output" after the block.

As an example, here's a Python block that adds a static integer
variable to the C code::

    /*[python input]
    print('static int __ignored_unused_variable__ = 0;')
    [python start generated code]*/
    static int __ignored_unused_variable__ = 0;
    /*[python checksum:...]*/


.. _clinic-howto-self-converter:

How to use the "self converter"
-------------------------------

Argument Clinic automatically adds a "self" parameter for you
using a default converter.  It automatically sets the ``type``
of this parameter to the "pointer to an instance" you specified
when you declared the type.  However, you can override
Argument Clinic's converter and specify one yourself.
Just add your own *self* parameter as the first parameter in a
block, and ensure that its converter is an instance of
:class:`!self_converter` or a subclass thereof.

What's the point?  This lets you override the type of ``self``,
or give it a different default name.

How do you specify the custom type you want to cast ``self`` to?
If you only have one or two functions with the same type for ``self``,
you can directly use Argument Clinic's existing ``self`` converter,
passing in the type you want to use as the *type* parameter::

    /*[clinic input]

    _pickle.Pickler.dump

      self: self(type="PicklerObject *")
      obj: object
      /

    Write a pickled representation of the given object to the open file.
    [clinic start generated code]*/

On the other hand, if you have a lot of functions that will use the same
type for ``self``, it's best to create your own converter, subclassing
:class:`!self_converter` but overwriting the :py:attr:`!type` member::

    /*[python input]
    class PicklerObject_converter(self_converter):
        type = "PicklerObject *"
    [python start generated code]*/

    /*[clinic input]

    _pickle.Pickler.dump

      self: PicklerObject
      obj: object
      /

    Write a pickled representation of the given object to the open file.
    [clinic start generated code]*/


How to use the "defining class" converter
-----------------------------------------

Argument Clinic facilitates gaining access to the defining class of a method.
This is useful for :ref:`heap type <heap-types>` methods that need to fetch
module level state.  Use :c:func:`PyType_FromModuleAndSpec` to associate a new
heap type with a module.  You can now use :c:func:`PyType_GetModuleState` on
the defining class to fetch the module state, for example from a module method.

Example from :source:`Modules/zlibmodule.c`.
First, ``defining_class`` is added to the clinic input::

    /*[clinic input]
    zlib.Compress.compress

      cls: defining_class
      data: Py_buffer
        Binary data to be compressed.
      /


After running the Argument Clinic tool, the following function signature is
generated::

    /*[clinic start generated code]*/
    static PyObject *
    zlib_Compress_compress_impl(compobject *self, PyTypeObject *cls,
                                Py_buffer *data)
    /*[clinic end generated code: output=6731b3f0ff357ca6 input=04d00f65ab01d260]*/


The following code can now use ``PyType_GetModuleState(cls)`` to fetch the
module state::

    zlibstate *state = PyType_GetModuleState(cls);


Each method may only have one argument using this converter, and it must appear
after ``self``, or, if ``self`` is not used, as the first argument.  The argument
will be of type ``PyTypeObject *``.  The argument will not appear in the
:py:attr:`!__text_signature__`.

The ``defining_class`` converter is not compatible with :py:meth:`!__init__`
and :py:meth:`!__new__` methods, which cannot use the :c:macro:`METH_METHOD`
convention.

It is not possible to use ``defining_class`` with slot methods.  In order to
fetch the module state from such methods, use :c:func:`PyType_GetModuleByDef`
to look up the module and then :c:func:`PyModule_GetState` to fetch the module
state.  Example from the ``setattro`` slot method in
:source:`Modules/_threadmodule.c`::

    static int
    local_setattro(localobject *self, PyObject *name, PyObject *v)
    {
        PyObject *module = PyType_GetModuleByDef(Py_TYPE(self), &thread_module);
        thread_module_state *state = get_thread_state(module);
        ...
    }


See also :pep:`573`.


How to write a custom converter
-------------------------------

As we hinted at in the previous section... you can write your own converters!
A converter is simply a Python class that inherits from :py:class:`!CConverter`.
The main purpose of a custom converter is if you have a parameter using
the ``O&`` format unit—parsing this parameter means calling
a :c:func:`PyArg_ParseTuple` "converter function".

Your converter class should be named ``*something*_converter``.
If the name follows this convention, then your converter class
will be automatically registered with Argument Clinic; its name
will be the name of your class with the ``_converter`` suffix
stripped off.  (This is accomplished with a metaclass.)

You shouldn't subclass :py:meth:`!CConverter.__init__`.  Instead, you should
write a :py:meth:`!converter_init` function. :py:meth:`!converter_init`
always accepts a *self* parameter; after that, all additional
parameters *must* be keyword-only.  Any arguments passed in to
the converter in Argument Clinic will be passed along to your
:py:meth:`!converter_init`.

There are some additional members of :py:class:`!CConverter` you may wish
to specify in your subclass.  Here's the current list:

.. module:: clinic

.. class:: CConverter

   .. attribute:: type

      The C type to use for this variable.
      :attr:`!type` should be a Python string specifying the type,
      e.g. ``'int'``.
      If this is a pointer type, the type string should end with ``' *'``.

   .. attribute:: default

      The Python default value for this parameter, as a Python value.
      Or the magic value ``unspecified`` if there is no default.

   .. attribute:: py_default

      :attr:`!default` as it should appear in Python code,
      as a string.
      Or ``None`` if there is no default.

   .. attribute:: c_default

      :attr:`!default` as it should appear in C code,
      as a string.
      Or ``None`` if there is no default.

   .. attribute:: c_ignored_default

      The default value used to initialize the C variable when
      there is no default, but not specifying a default may
      result in an "uninitialized variable" warning.  This can
      easily happen when using option groups—although
      properly written code will never actually use this value,
      the variable does get passed in to the impl, and the
      C compiler will complain about the "use" of the
      uninitialized value.  This value should always be a
      non-empty string.

   .. attribute:: converter

      The name of the C converter function, as a string.

   .. attribute:: impl_by_reference

      A boolean value.  If true,
      Argument Clinic will add a ``&`` in front of the name of
      the variable when passing it into the impl function.

   .. attribute:: parse_by_reference

      A boolean value.  If true,
      Argument Clinic will add a ``&`` in front of the name of
      the variable when passing it into :c:func:`PyArg_ParseTuple`.


Here's the simplest example of a custom converter, from :source:`Modules/zlibmodule.c`::

    /*[python input]

    class ssize_t_converter(CConverter):
        type = 'Py_ssize_t'
        converter = 'ssize_t_converter'

    [python start generated code]*/
    /*[python end generated code: output=da39a3ee5e6b4b0d input=35521e4e733823c7]*/

This block adds a converter to Argument Clinic named ``ssize_t``.  Parameters
declared as ``ssize_t`` will be declared as type :c:type:`Py_ssize_t`, and will
be parsed by the ``'O&'`` format unit, which will call the
``ssize_t_converter`` converter function.  ``ssize_t`` variables
automatically support default values.

More sophisticated custom converters can insert custom C code to
handle initialization and cleanup.
You can see more examples of custom converters in the CPython
source tree; grep the C files for the string :py:class:`!CConverter`.


How to write a custom return converter
--------------------------------------

Writing a custom return converter is much like writing
a custom converter.  Except it's somewhat simpler, because return
converters are themselves much simpler.

Return converters must subclass :py:class:`!CReturnConverter`.
There are no examples yet of custom return converters,
because they are not widely used yet.  If you wish to
write your own return converter, please read :source:`Tools/clinic/clinic.py`,
specifically the implementation of :py:class:`!CReturnConverter` and
all its subclasses.


How to convert ``METH_O`` and ``METH_NOARGS`` functions
-------------------------------------------------------

To convert a function using :c:macro:`METH_O`, make sure the function's
single argument is using the ``object`` converter, and mark the
arguments as positional-only::

    /*[clinic input]
    meth_o_sample

         argument: object
         /
    [clinic start generated code]*/


To convert a function using :c:macro:`METH_NOARGS`, just don't specify
any arguments.

You can still use a self converter, a return converter, and specify
a *type* argument to the object converter for :c:macro:`METH_O`.


How to convert ``tp_new`` and ``tp_init`` functions
---------------------------------------------------

You can convert :c:member:`~PyTypeObject.tp_new` and
:c:member:`~PyTypeObject.tp_init` functions.
Just name them ``__new__`` or ``__init__`` as appropriate.  Notes:

* The function name generated for ``__new__`` doesn't end in ``__new__``
  like it would by default.  It's just the name of the class, converted
  into a valid C identifier.

* No :c:type:`PyMethodDef` ``#define`` is generated for these functions.

* ``__init__`` functions return ``int``, not ``PyObject *``.

* Use the docstring as the class docstring.

* Although ``__new__`` and ``__init__`` functions must always
  accept both the ``args`` and ``kwargs`` objects, when converting
  you may specify any signature for these functions that you like.
  (If your function doesn't support keywords, the parsing function
  generated will throw an exception if it receives any.)


How to change and redirect Clinic's output
------------------------------------------

It can be inconvenient to have Clinic's output interspersed with
your conventional hand-edited C code.  Luckily, Clinic is configurable:
you can buffer up its output for printing later (or earlier!), or write
its output to a separate file.  You can also add a prefix or suffix to
every line of Clinic's generated output.

While changing Clinic's output in this manner can be a boon to readability,
it may result in Clinic code using types before they are defined, or
your code attempting to use Clinic-generated code before it is defined.
These problems can be easily solved by rearranging the declarations in your file,
or moving where Clinic's generated code goes.  (This is why the default behavior
of Clinic is to output everything into the current block; while many people
consider this hampers readability, it will never require rearranging your
code to fix definition-before-use problems.)

Let's start with defining some terminology:

*field*
  A field, in this context, is a subsection of Clinic's output.
  For example, the ``#define`` for the :c:type:`PyMethodDef` structure
  is a field, called ``methoddef_define``.  Clinic has seven
  different fields it can output per function definition:

  .. code-block:: none

      docstring_prototype
      docstring_definition
      methoddef_define
      impl_prototype
      parser_prototype
      parser_definition
      impl_definition

  All the names are of the form ``"<a>_<b>"``,
  where ``"<a>"`` is the semantic object represented (the parsing function,
  the impl function, the docstring, or the methoddef structure) and ``"<b>"``
  represents what kind of statement the field is.  Field names that end in
  ``"_prototype"``
  represent forward declarations of that thing, without the actual body/data
  of the thing; field names that end in ``"_definition"`` represent the actual
  definition of the thing, with the body/data of the thing.  (``"methoddef"``
  is special, it's the only one that ends with ``"_define"``, representing that
  it's a preprocessor #define.)

*destination*
  A destination is a place Clinic can write output to.  There are
  five built-in destinations:

  ``block``
    The default destination: printed in the output section of
    the current Clinic block.

  ``buffer``
    A text buffer where you can save text for later.  Text sent
    here is appended to the end of any existing text.  It's an
    error to have any text left in the buffer when Clinic finishes
    processing a file.

  ``file``
    A separate "clinic file" that will be created automatically by Clinic.
    The filename chosen for the file is ``{basename}.clinic{extension}``,
    where ``basename`` and ``extension`` were assigned the output
    from ``os.path.splitext()`` run on the current file.  (Example:
    the ``file`` destination for :file:`_pickle.c` would be written to
    :file:`_pickle.clinic.c`.)

    **Important: When using a** ``file`` **destination, you**
    *must check in* **the generated file!**

  ``two-pass``
    A buffer like ``buffer``.  However, a two-pass buffer can only
    be dumped once, and it prints out all text sent to it during
    all processing, even from Clinic blocks *after* the dumping point.

  ``suppress``
    The text is suppressed—thrown away.


Clinic defines five new directives that let you reconfigure its output.

The first new directive is ``dump``:

.. code-block:: none

   dump <destination>

This dumps the current contents of the named destination into the output of
the current block, and empties it.  This only works with ``buffer`` and
``two-pass`` destinations.

The second new directive is ``output``.  The most basic form of ``output``
is like this:

.. code-block:: none

    output <field> <destination>

This tells Clinic to output *field* to *destination*.  ``output`` also
supports a special meta-destination, called ``everything``, which tells
Clinic to output *all* fields to that *destination*.

``output`` has a number of other functions:

.. code-block:: none

    output push
    output pop
    output preset <preset>


``output push`` and ``output pop`` allow you to push and pop
configurations on an internal configuration stack, so that you
can temporarily modify the output configuration, then easily restore
the previous configuration.  Simply push before your change to save
the current configuration, then pop when you wish to restore the
previous configuration.

``output preset`` sets Clinic's output to one of several built-in
preset configurations, as follows:

  ``block``
    Clinic's original starting configuration.  Writes everything
    immediately after the input block.

    Suppress the ``parser_prototype``
    and ``docstring_prototype``, write everything else to ``block``.

  ``file``
    Designed to write everything to the "clinic file" that it can.
    You then ``#include`` this file near the top of your file.
    You may need to rearrange your file to make this work, though
    usually this just means creating forward declarations for various
    ``typedef`` and ``PyTypeObject`` definitions.

    Suppress the ``parser_prototype``
    and ``docstring_prototype``, write the ``impl_definition`` to
    ``block``, and write everything else to ``file``.

    The default filename is ``"{dirname}/clinic/{basename}.h"``.

  ``buffer``
    Save up most of the output from Clinic, to be written into
    your file near the end.  For Python files implementing modules
    or builtin types, it's recommended that you dump the buffer
    just above the static structures for your module or
    builtin type; these are normally very near the end.  Using
    ``buffer`` may require even more editing than ``file``, if
    your file has static ``PyMethodDef`` arrays defined in the
    middle of the file.

    Suppress the ``parser_prototype``, ``impl_prototype``,
    and ``docstring_prototype``, write the ``impl_definition`` to
    ``block``, and write everything else to ``file``.

  ``two-pass``
    Similar to the ``buffer`` preset, but writes forward declarations to
    the ``two-pass`` buffer, and definitions to the ``buffer``.
    This is similar to the ``buffer`` preset, but may require
    less editing than ``buffer``.  Dump the ``two-pass`` buffer
    near the top of your file, and dump the ``buffer`` near
    the end just like you would when using the ``buffer`` preset.

    Suppresses the ``impl_prototype``, write the ``impl_definition``
    to ``block``, write ``docstring_prototype``, ``methoddef_define``,
    and ``parser_prototype`` to ``two-pass``, write everything else
    to ``buffer``.

  ``partial-buffer``
    Similar to the ``buffer`` preset, but writes more things to ``block``,
    only writing the really big chunks of generated code to ``buffer``.
    This avoids the definition-before-use problem of ``buffer`` completely,
    at the small cost of having slightly more stuff in the block's output.
    Dump the ``buffer`` near the end, just like you would when using
    the ``buffer`` preset.

    Suppresses the ``impl_prototype``, write the ``docstring_definition``
    and ``parser_definition`` to ``buffer``, write everything else to ``block``.

The third new directive is ``destination``:

.. code-block:: none

    destination <name> <command> [...]

This performs an operation on the destination named ``name``.

There are two defined subcommands: ``new`` and ``clear``.

The ``new`` subcommand works like this:

.. code-block:: none

    destination <name> new <type>

This creates a new destination with name ``<name>`` and type ``<type>``.

There are five destination types:

    ``suppress``
        Throws the text away.

    ``block``
        Writes the text to the current block.  This is what Clinic
        originally did.

    ``buffer``
        A simple text buffer, like the "buffer" builtin destination above.

    ``file``
        A text file.  The file destination takes an extra argument,
        a template to use for building the filename, like so:

            destination <name> new <type> <file_template>

        The template can use three strings internally that will be replaced
        by bits of the filename:

            {path}
                The full path to the file, including directory and full filename.
            {dirname}
                The name of the directory the file is in.
            {basename}
                Just the name of the file, not including the directory.
            {basename_root}
                Basename with the extension clipped off
                (everything up to but not including the last '.').
            {basename_extension}
                The last '.' and everything after it.  If the basename
                does not contain a period, this will be the empty string.

        If there are no periods in the filename, {basename} and {filename}
        are the same, and {extension} is empty.  "{basename}{extension}"
        is always exactly the same as "{filename}"."

    ``two-pass``
        A two-pass buffer, like the "two-pass" builtin destination above.


The ``clear`` subcommand works like this:

.. code-block:: none

    destination <name> clear

It removes all the accumulated text up to this point in the destination.
(I don't know what you'd need this for, but I thought maybe it'd be
useful while someone's experimenting.)

The fourth new directive is ``set``:

.. code-block:: none

    set line_prefix "string"
    set line_suffix "string"

``set`` lets you set two internal variables in Clinic.
``line_prefix`` is a string that will be prepended to every line of Clinic's output;
``line_suffix`` is a string that will be appended to every line of Clinic's output.

Both of these support two format strings:

  ``{block comment start}``
    Turns into the string ``/*``, the start-comment text sequence for C files.

  ``{block comment end}``
    Turns into the string ``*/``, the end-comment text sequence for C files.

The final new directive is one you shouldn't need to use directly,
called ``preserve``:

.. code-block:: none

    preserve

This tells Clinic that the current contents of the output should be kept, unmodified.
This is used internally by Clinic when dumping output into ``file`` files; wrapping
it in a Clinic block lets Clinic use its existing checksum functionality to ensure
the file was not modified by hand before it gets overwritten.


How to use the ``#ifdef`` trick
-------------------------------

If you're converting a function that isn't available on all platforms,
there's a trick you can use to make life a little easier.  The existing
code probably looks like this::

    #ifdef HAVE_FUNCTIONNAME
    static module_functionname(...)
    {
    ...
    }
    #endif /* HAVE_FUNCTIONNAME */

And then in the ``PyMethodDef`` structure at the bottom the existing code
will have:

.. code-block:: none

    #ifdef HAVE_FUNCTIONNAME
    {'functionname', ... },
    #endif /* HAVE_FUNCTIONNAME */

In this scenario, you should enclose the body of your impl function inside the ``#ifdef``,
like so::

    #ifdef HAVE_FUNCTIONNAME
    /*[clinic input]
    module.functionname
    ...
    [clinic start generated code]*/
    static module_functionname(...)
    {
    ...
    }
    #endif /* HAVE_FUNCTIONNAME */

Then, remove those three lines from the :c:type:`PyMethodDef` structure,
replacing them with the macro Argument Clinic generated:

.. code-block:: none

    MODULE_FUNCTIONNAME_METHODDEF

(You can find the real name for this macro inside the generated code.
Or you can calculate it yourself: it's the name of your function as defined
on the first line of your block, but with periods changed to underscores,
uppercased, and ``"_METHODDEF"`` added to the end.)

Perhaps you're wondering: what if ``HAVE_FUNCTIONNAME`` isn't defined?
The ``MODULE_FUNCTIONNAME_METHODDEF`` macro won't be defined either!

Here's where Argument Clinic gets very clever.  It actually detects that the
Argument Clinic block might be deactivated by the ``#ifdef``.  When that
happens, it generates a little extra code that looks like this::

    #ifndef MODULE_FUNCTIONNAME_METHODDEF
        #define MODULE_FUNCTIONNAME_METHODDEF
    #endif /* !defined(MODULE_FUNCTIONNAME_METHODDEF) */

That means the macro always works.  If the function is defined, this turns
into the correct structure, including the trailing comma.  If the function is
undefined, this turns into nothing.

However, this causes one ticklish problem: where should Argument Clinic put this
extra code when using the "block" output preset?  It can't go in the output block,
because that could be deactivated by the ``#ifdef``.  (That's the whole point!)

In this situation, Argument Clinic writes the extra code to the "buffer" destination.
This may mean that you get a complaint from Argument Clinic:

.. code-block:: none

    Warning in file "Modules/posixmodule.c" on line 12357:
    Destination buffer 'buffer' not empty at end of file, emptying.

When this happens, just open your file, find the ``dump buffer`` block that
Argument Clinic added to your file (it'll be at the very bottom), then
move it above the :c:type:`PyMethodDef` structure where that macro is used.


How to use Argument Clinic in Python files
------------------------------------------

It's actually possible to use Argument Clinic to preprocess Python files.
There's no point to using Argument Clinic blocks, of course, as the output
wouldn't make any sense to the Python interpreter.  But using Argument Clinic
to run Python blocks lets you use Python as a Python preprocessor!

Since Python comments are different from C comments, Argument Clinic
blocks embedded in Python files look slightly different.  They look like this:

.. code-block:: python3

    #/*[python input]
    #print("def foo(): pass")
    #[python start generated code]*/
    def foo(): pass
    #/*[python checksum:...]*/
