1701 lines
64 KiB
ReStructuredText
1701 lines
64 KiB
ReStructuredText
.. highlightlang:: c
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**********************
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Argument Clinic How-To
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**********************
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:author: Larry Hastings
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.. topic:: Abstract
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Argument Clinic is a preprocessor for CPython C files.
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Its purpose is to automate all the boilerplate involved
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with writing argument parsing code for "builtins".
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This document shows you how to convert your first C
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function to work with Argument Clinic, and then introduces
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some advanced topics on Argument Clinic usage.
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Currently Argument Clinic is considered internal-only
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for CPython. Its use is not supported for files outside
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CPython, and no guarantees are made regarding backwards
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compatibility for future versions. In other words: if you
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maintain an external C extension for CPython, you're welcome
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to experiment with Argument Clinic in your own code. But the
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version of Argument Clinic that ships with CPython 3.5 *could*
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be totally incompatible and break all your code.
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The Goals Of Argument Clinic
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============================
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Argument Clinic's primary goal
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is to take over responsibility for all argument parsing code
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inside CPython. This means that, when you convert a function
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to work with Argument Clinic, that function should no longer
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do any of its own argument parsing—the code generated by
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Argument Clinic should be a "black box" to you, where CPython
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calls in at the top, and your code gets called at the bottom,
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with ``PyObject *args`` (and maybe ``PyObject *kwargs``)
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magically converted into the C variables and types you need.
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In order for Argument Clinic to accomplish its primary goal,
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it must be easy to use. Currently, working with CPython's
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argument parsing library is a chore, requiring maintaining
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redundant information in a surprising number of places.
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When you use Argument Clinic, you don't have to repeat yourself.
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Obviously, no one would want to use Argument Clinic unless
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it's solving their problem—and without creating new problems of
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its own.
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So it's paramount that Argument Clinic generate correct code.
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It'd be nice if the code was faster, too, but at the very least
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it should not introduce a major speed regression. (Eventually Argument
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Clinic *should* make a major speedup possible—we could
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rewrite its code generator to produce tailor-made argument
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parsing code, rather than calling the general-purpose CPython
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argument parsing library. That would make for the fastest
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argument parsing possible!)
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Additionally, Argument Clinic must be flexible enough to
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work with any approach to argument parsing. Python has
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some functions with some very strange parsing behaviors;
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Argument Clinic's goal is to support all of them.
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Finally, the original motivation for Argument Clinic was
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to provide introspection "signatures" for CPython builtins.
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It used to be, the introspection query functions would throw
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an exception if you passed in a builtin. With Argument
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Clinic, that's a thing of the past!
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One idea you should keep in mind, as you work with
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Argument Clinic: the more information you give it, the
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better job it'll be able to do.
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Argument Clinic is admittedly relatively simple right
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now. But as it evolves it will get more sophisticated,
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and it should be able to do many interesting and smart
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things with all the information you give it.
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Basic Concepts And Usage
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========================
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Argument Clinic ships with CPython; you'll find it in ``Tools/clinic/clinic.py``.
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If you run that script, specifying a C file as an argument:
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.. code-block:: shell-session
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$ python3 Tools/clinic/clinic.py foo.c
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Argument Clinic will scan over the file looking for lines that
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look exactly like this:
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.. code-block:: none
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/*[clinic input]
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When it finds one, it reads everything up to a line that looks
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exactly like this:
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.. code-block:: none
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[clinic start generated code]*/
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Everything in between these two lines is input for Argument Clinic.
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All of these lines, including the beginning and ending comment
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lines, are collectively called an Argument Clinic "block".
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When Argument Clinic parses one of these blocks, it
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generates output. This output is rewritten into the C file
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immediately after the block, followed by a comment containing a checksum.
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The Argument Clinic block now looks like this:
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.. code-block:: none
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/*[clinic input]
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... clinic input goes here ...
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[clinic start generated code]*/
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... clinic output goes here ...
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/*[clinic end generated code: checksum=...]*/
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If you run Argument Clinic on the same file a second time, Argument Clinic
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will discard the old output and write out the new output with a fresh checksum
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line. However, if the input hasn't changed, the output won't change either.
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You should never modify the output portion of an Argument Clinic block. Instead,
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change the input until it produces the output you want. (That's the purpose of the
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checksum—to detect if someone changed the output, as these edits would be lost
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the next time Argument Clinic writes out fresh output.)
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For the sake of clarity, here's the terminology we'll use with Argument Clinic:
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* The first line of the comment (``/*[clinic input]``) is the *start line*.
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* The last line of the initial comment (``[clinic start generated code]*/``) is the *end line*.
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* The last line (``/*[clinic end generated code: checksum=...]*/``) is the *checksum line*.
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* In between the start line and the end line is the *input*.
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* In between the end line and the checksum line is the *output*.
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* All the text collectively, from the start line to the checksum line inclusively,
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is the *block*. (A block that hasn't been successfully processed by Argument
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Clinic yet doesn't have output or a checksum line, but it's still considered
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a block.)
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Converting Your First Function
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==============================
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The best way to get a sense of how Argument Clinic works is to
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convert a function to work with it. Here, then, are the bare
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minimum steps you'd need to follow to convert a function to
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work with Argument Clinic. Note that for code you plan to
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check in to CPython, you really should take the conversion farther,
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using some of the advanced concepts you'll see later on in
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the document (like "return converters" and "self converters").
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But we'll keep it simple for this walkthrough so you can learn.
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Let's dive in!
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0. Make sure you're working with a freshly updated checkout
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of the CPython trunk.
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1. Find a Python builtin that calls either :c:func:`PyArg_ParseTuple`
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or :c:func:`PyArg_ParseTupleAndKeywords`, and hasn't been converted
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to work with Argument Clinic yet.
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For my example I'm using ``_pickle.Pickler.dump()``.
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2. If the call to the ``PyArg_Parse`` function uses any of the
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following format units:
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.. code-block:: none
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O&
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O!
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es
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es#
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et
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et#
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or if it has multiple calls to :c:func:`PyArg_ParseTuple`,
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you should choose a different function. Argument Clinic *does*
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support all of these scenarios. But these are advanced
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topics—let's do something simpler for your first function.
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Also, if the function has multiple calls to :c:func:`PyArg_ParseTuple`
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or :c:func:`PyArg_ParseTupleAndKeywords` where it supports different
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types for the same argument, or if the function uses something besides
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PyArg_Parse functions to parse its arguments, it probably
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isn't suitable for conversion to Argument Clinic. Argument Clinic
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doesn't support generic functions or polymorphic parameters.
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3. Add the following boilerplate above the function, creating our block::
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/*[clinic input]
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[clinic start generated code]*/
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4. Cut the docstring and paste it in between the ``[clinic]`` lines,
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removing all the junk that makes it a properly quoted C string.
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When you're done you should have just the text, based at the left
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margin, with no line wider than 80 characters.
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(Argument Clinic will preserve indents inside the docstring.)
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If the old docstring had a first line that looked like a function
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signature, throw that line away. (The docstring doesn't need it
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anymore—when you use ``help()`` on your builtin in the future,
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the first line will be built automatically based on the function's
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signature.)
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Sample::
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/*[clinic input]
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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5. If your docstring doesn't have a "summary" line, Argument Clinic will
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complain. So let's make sure it has one. The "summary" line should
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be a paragraph consisting of a single 80-column line
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at the beginning of the docstring.
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(Our example docstring consists solely of a summary line, so the sample
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code doesn't have to change for this step.)
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6. Above the docstring, enter the name of the function, followed
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by a blank line. This should be the Python name of the function,
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and should be the full dotted path
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to the function—it should start with the name of the module,
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include any sub-modules, and if the function is a method on
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a class it should include the class name too.
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Sample::
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/*[clinic input]
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_pickle.Pickler.dump
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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7. If this is the first time that module or class has been used with Argument
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Clinic in this C file,
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you must declare the module and/or class. Proper Argument Clinic hygiene
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prefers declaring these in a separate block somewhere near the
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top of the C file, in the same way that include files and statics go at
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the top. (In our sample code we'll just show the two blocks next to
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each other.)
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The name of the class and module should be the same as the one
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seen by Python. Check the name defined in the :c:type:`PyModuleDef`
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or :c:type:`PyTypeObject` as appropriate.
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When you declare a class, you must also specify two aspects of its type
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in C: the type declaration you'd use for a pointer to an instance of
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this class, and a pointer to the :c:type:`PyTypeObject` for this class.
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Sample::
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/*[clinic input]
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module _pickle
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class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
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[clinic start generated code]*/
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/*[clinic input]
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_pickle.Pickler.dump
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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8. Declare each of the parameters to the function. Each parameter
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should get its own line. All the parameter lines should be
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indented from the function name and the docstring.
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The general form of these parameter lines is as follows::
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name_of_parameter: converter
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If the parameter has a default value, add that after the
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converter::
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name_of_parameter: converter = default_value
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Argument Clinic's support for "default values" is quite sophisticated;
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please see :ref:`the section below on default values <default_values>`
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for more information.
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Add a blank line below the parameters.
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What's a "converter"? It establishes both the type
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of the variable used in C, and the method to convert the Python
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value into a C value at runtime.
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For now you're going to use what's called a "legacy converter"—a
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convenience syntax intended to make porting old code into Argument
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Clinic easier.
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For each parameter, copy the "format unit" for that
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parameter from the ``PyArg_Parse()`` format argument and
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specify *that* as its converter, as a quoted
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string. ("format unit" is the formal name for the one-to-three
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character substring of the ``format`` parameter that tells
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the argument parsing function what the type of the variable
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is and how to convert it. For more on format units please
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see :ref:`arg-parsing`.)
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For multicharacter format units like ``z#``, use the
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entire two-or-three character string.
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Sample::
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/*[clinic input]
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module _pickle
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class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
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[clinic start generated code]*/
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/*[clinic input]
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_pickle.Pickler.dump
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obj: 'O'
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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9. If your function has ``|`` in the format string, meaning some
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parameters have default values, you can ignore it. Argument
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Clinic infers which parameters are optional based on whether
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or not they have default values.
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If your function has ``$`` in the format string, meaning it
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takes keyword-only arguments, specify ``*`` on a line by
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itself before the first keyword-only argument, indented the
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same as the parameter lines.
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(``_pickle.Pickler.dump`` has neither, so our sample is unchanged.)
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10. If the existing C function calls :c:func:`PyArg_ParseTuple`
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(as opposed to :c:func:`PyArg_ParseTupleAndKeywords`), then all its
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arguments are positional-only.
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To mark all parameters as positional-only in Argument Clinic,
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add a ``/`` on a line by itself after the last parameter,
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indented the same as the parameter lines.
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Currently this is all-or-nothing; either all parameters are
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positional-only, or none of them are. (In the future Argument
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Clinic may relax this restriction.)
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Sample::
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/*[clinic input]
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module _pickle
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class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
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[clinic start generated code]*/
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/*[clinic input]
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_pickle.Pickler.dump
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obj: 'O'
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/
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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11. It's helpful to write a per-parameter docstring for each parameter.
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But per-parameter docstrings are optional; you can skip this step
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if you prefer.
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Here's how to add a per-parameter docstring. The first line
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of the per-parameter docstring must be indented further than the
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parameter definition. The left margin of this first line establishes
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the left margin for the whole per-parameter docstring; all the text
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you write will be outdented by this amount. You can write as much
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text as you like, across multiple lines if you wish.
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Sample::
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/*[clinic input]
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module _pickle
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class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
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[clinic start generated code]*/
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/*[clinic input]
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_pickle.Pickler.dump
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obj: 'O'
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The object to be pickled.
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/
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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12. Save and close the file, then run ``Tools/clinic/clinic.py`` on
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it. With luck everything worked---your block now has output, and
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a ``.c.h`` file has been generated! Reopen the file in your
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text editor to see::
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/*[clinic input]
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_pickle.Pickler.dump
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obj: 'O'
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The object to be pickled.
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/
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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static PyObject *
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_pickle_Pickler_dump(PicklerObject *self, PyObject *obj)
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/*[clinic end generated code: output=87ecad1261e02ac7 input=552eb1c0f52260d9]*/
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Obviously, if Argument Clinic didn't produce any output, it's because
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it found an error in your input. Keep fixing your errors and retrying
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until Argument Clinic processes your file without complaint.
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For readability, most of the glue code has been generated to a ``.c.h``
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file. You'll need to include that in your original ``.c`` file,
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typically right after the clinic module block::
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#include "clinic/_pickle.c.h"
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13. Double-check that the argument-parsing code Argument Clinic generated
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looks basically the same as the existing code.
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First, ensure both places use the same argument-parsing function.
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The existing code must call either
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:c:func:`PyArg_ParseTuple` or :c:func:`PyArg_ParseTupleAndKeywords`;
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ensure that the code generated by Argument Clinic calls the
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*exact* same function.
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Second, the format string passed in to :c:func:`PyArg_ParseTuple` or
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:c:func:`PyArg_ParseTupleAndKeywords` should be *exactly* the same
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as the hand-written one in the existing function, up to the colon
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or semi-colon.
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(Argument Clinic always generates its format strings
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with a ``:`` followed by the name of the function. If the
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existing code's format string ends with ``;``, to provide
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usage help, this change is harmless—don't worry about it.)
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Third, for parameters whose format units require two arguments
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(like a length variable, or an encoding string, or a pointer
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to a conversion function), ensure that the second argument is
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*exactly* the same between the two invocations.
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Fourth, inside the output portion of the block you'll find a preprocessor
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macro defining the appropriate static :c:type:`PyMethodDef` structure for
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this builtin::
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#define __PICKLE_PICKLER_DUMP_METHODDEF \
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{"dump", (PyCFunction)__pickle_Pickler_dump, METH_O, __pickle_Pickler_dump__doc__},
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This static structure should be *exactly* the same as the existing static
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:c:type:`PyMethodDef` structure for this builtin.
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If any of these items differ in *any way*,
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adjust your Argument Clinic function specification and rerun
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``Tools/clinic/clinic.py`` until they *are* the same.
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14. Notice that the last line of its output is the declaration
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of your "impl" function. This is where the builtin's implementation goes.
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Delete the existing prototype of the function you're modifying, but leave
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the opening curly brace. Now delete its argument parsing code and the
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declarations of all the variables it dumps the arguments into.
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Notice how the Python arguments are now arguments to this impl function;
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if the implementation used different names for these variables, fix it.
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Let's reiterate, just because it's kind of weird. Your code should now
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look like this::
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static return_type
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your_function_impl(...)
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/*[clinic end generated code: checksum=...]*/
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{
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...
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Argument Clinic generated the checksum line and the function prototype just
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above it. You should write the opening (and closing) curly braces for the
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function, and the implementation inside.
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Sample::
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/*[clinic input]
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module _pickle
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class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
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[clinic start generated code]*/
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/*[clinic end generated code: checksum=da39a3ee5e6b4b0d3255bfef95601890afd80709]*/
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/*[clinic input]
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_pickle.Pickler.dump
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obj: 'O'
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The object to be pickled.
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/
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Write a pickled representation of obj to the open file.
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[clinic start generated code]*/
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PyDoc_STRVAR(__pickle_Pickler_dump__doc__,
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"Write a pickled representation of obj to the open file.\n"
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"\n"
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...
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static PyObject *
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_pickle_Pickler_dump_impl(PicklerObject *self, PyObject *obj)
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/*[clinic end generated code: checksum=3bd30745bf206a48f8b576a1da3d90f55a0a4187]*/
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{
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/* Check whether the Pickler was initialized correctly (issue3664).
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Developers often forget to call __init__() in their subclasses, which
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would trigger a segfault without this check. */
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if (self->write == NULL) {
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PyErr_Format(PicklingError,
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"Pickler.__init__() was not called by %s.__init__()",
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Py_TYPE(self)->tp_name);
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return NULL;
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}
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if (_Pickler_ClearBuffer(self) < 0)
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return NULL;
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|
|
...
|
|
|
|
15. 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. So 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 */
|
|
};
|
|
|
|
|
|
16. 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.
|
|
|
|
Well, except for one difference: ``inspect.signature()`` run on your function
|
|
should now provide a valid signature!
|
|
|
|
Congratulations, you've ported your first function to work with Argument Clinic!
|
|
|
|
Advanced Topics
|
|
===============
|
|
|
|
Now that you've had some experience working with Argument Clinic, it's time
|
|
for some advanced topics.
|
|
|
|
|
|
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 ``sys.maxsize``, which must
|
|
start with the name of the module
|
|
|
|
In case you're curious, this is implemented in ``from_builtin()``
|
|
in ``Lib/inspect.py``.
|
|
|
|
(In the future, this may need to get even more elaborate,
|
|
to allow full expressions like ``CONSTANT - 1``.)
|
|
|
|
|
|
Renaming the 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
|
|
``pickle.Pickler.dump``, it'd look like this::
|
|
|
|
/*[clinic input]
|
|
pickle.Pickler.dump as pickler_dumper
|
|
|
|
...
|
|
|
|
The base function would now be named ``pickler_dumper()``,
|
|
and the impl function would now be named ``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!
|
|
|
|
|
|
Converting 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.
|
|
|
|
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 ``range()``, which has
|
|
an optional argument on the *left* side of its required argument!
|
|
Another example is ``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 ``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.
|
|
|
|
|
|
Using 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.
|
|
|
|
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 ``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'`` ``Py_UNICODE``
|
|
``'u#'`` ``Py_UNICODE(zeroes=True)``
|
|
``'w*'`` ``Py_buffer(accept={rwbuffer})``
|
|
``'Y'`` ``PyByteArrayObject``
|
|
``'y'`` ``str(accept={bytes})``
|
|
``'y#'`` ``str(accept={robuffer}, zeroes=True)``
|
|
``'y*'`` ``Py_buffer``
|
|
``'Z'`` ``Py_UNICODE(accept={str, NoneType})``
|
|
``'Z#'`` ``Py_UNICODE(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]*/
|
|
|
|
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.
|
|
|
|
Py_buffer
|
|
---------
|
|
|
|
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).
|
|
|
|
|
|
|
|
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 ``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
|
|
``PyArg_Parse`` call by hand, you could theoretically decide at runtime what
|
|
encoding string to pass in to :c:func:`PyArg_ParseTuple`. 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``.
|
|
|
|
|
|
.. _default_values:
|
|
|
|
Parameter default values
|
|
------------------------
|
|
|
|
Default values for parameters can be any of a number of values.
|
|
At their simplest, they can be string, int, or float literals::
|
|
|
|
foo: str = "abc"
|
|
bar: int = 123
|
|
bat: float = 45.6
|
|
|
|
They can also use any of Python's built-in constants::
|
|
|
|
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``.
|
|
|
|
Expressions specified 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::
|
|
|
|
foo: Py_ssize_t = sys.maxsize - 1
|
|
|
|
``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 "``max_widgets``", you may simply use it::
|
|
|
|
foo: Py_ssize_t = max_widgets
|
|
|
|
If the symbol isn't found in the current module, it fails over to looking in
|
|
``sys.modules``. That's how it can find ``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::
|
|
|
|
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.
|
|
|
|
|
|
|
|
Using a return converter
|
|
------------------------
|
|
|
|
By default the impl function Argument Clinic generates for you returns ``PyObject *``.
|
|
But your C function often computes some C type, then converts it into the ``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 ``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. 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 (``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
|
|
int
|
|
unsigned int
|
|
long
|
|
unsigned int
|
|
size_t
|
|
Py_ssize_t
|
|
float
|
|
double
|
|
DecodeFSDefault
|
|
|
|
None of these take parameters. For the first three, return -1 to indicate
|
|
error. For ``DecodeFSDefault``, the return type is ``const char *``; return a NULL
|
|
pointer to indicate an error.
|
|
|
|
(There's also an experimental ``NoneType`` converter, which lets you
|
|
return ``Py_None`` on success or ``NULL`` on failure, without having
|
|
to increment the reference count on ``Py_None``. I'm not sure it adds
|
|
enough clarity to be worth using.)
|
|
|
|
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.
|
|
|
|
|
|
Cloning 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.
|
|
|
|
Calling 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:...]*/
|
|
|
|
|
|
Using a "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
|
|
``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
|
|
``self_converter`` but overwriting the ``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]*/
|
|
|
|
|
|
|
|
Writing 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 ``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 ``CConverter.__init__``. Instead, you should
|
|
write a ``converter_init()`` function. ``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
|
|
``converter_init()``.
|
|
|
|
There are some additional members of ``CConverter`` you may wish
|
|
to specify in your subclass. Here's the current list:
|
|
|
|
``type``
|
|
The C type to use for this variable.
|
|
``type`` should be a Python string specifying the type, e.g. ``int``.
|
|
If this is a pointer type, the type string should end with ``' *'``.
|
|
|
|
``default``
|
|
The Python default value for this parameter, as a Python value.
|
|
Or the magic value ``unspecified`` if there is no default.
|
|
|
|
``py_default``
|
|
``default`` as it should appear in Python code,
|
|
as a string.
|
|
Or ``None`` if there is no default.
|
|
|
|
``c_default``
|
|
``default`` as it should appear in C code,
|
|
as a string.
|
|
Or ``None`` if there is no default.
|
|
|
|
``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.
|
|
|
|
``converter``
|
|
The name of the C converter function, as a string.
|
|
|
|
``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.
|
|
|
|
``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 ``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 ``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 ``CConverter``.
|
|
|
|
Writing 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 ``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 ``Tools/clinic/clinic.py``,
|
|
specifically the implementation of ``CReturnConverter`` and
|
|
all its subclasses.
|
|
|
|
METH_O and METH_NOARGS
|
|
----------------------------------------------
|
|
|
|
To convert a function using ``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 ``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 ``METH_O``.
|
|
|
|
tp_new and tp_init functions
|
|
----------------------------------------------
|
|
|
|
You can convert ``tp_new`` and ``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 ``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.)
|
|
|
|
Changing and redirecting 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 ``PyMethodDef`` structure
|
|
is a field, called ``methoddef_define``. Clinic has seven
|
|
different fields it can output per function definition::
|
|
|
|
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 ``_pickle.c`` would be written to
|
|
``_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``::
|
|
|
|
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::
|
|
|
|
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::
|
|
|
|
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``::
|
|
|
|
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::
|
|
|
|
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::
|
|
|
|
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``::
|
|
|
|
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``::
|
|
|
|
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.
|
|
|
|
|
|
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 ``PyMethodDef`` structure,
|
|
replacing them with the macro Argument Clinic generated::
|
|
|
|
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 ``PyMethodDef`` structure where that macro is used.
|
|
|
|
|
|
|
|
Using 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:...]*/
|