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These are straightforward, finite-effort coding or writing projects.

Use Py_VISIT

The Py_VISIT() macro in objimpl.h was introduced to make coding of most tp_traverse slots straightforward, uniform, and obviously correct. For example, see cycle_traverse() in itertoolsmodule.c. Most older modules that define tp_traverse copy/paste/edit the tedious callback dance by hand, and several even define their own work-alike macros. These should be rewritten to use the standard Py_VISIT macro.

Use Py_CLEAR

The Py_CLEAR macro in object.h was introduced to make coding of "decref and NULL out a containee pointer" operations safe. The reasons for why this is important but tricky to achieve are explained in a comment block before that macro in current trunk source. tp_clear and even tp_dealloc slot implementations should generally use Py_CLEAR now.

Clean up 64-bit compiler warnings

There are many 64-bit warnings produced by icc when using the -Wp64 flag. icc is freely available for a one month trial license. NealNorwitz has a license and can make the warnings available on the web if anyone is interest in getting rid of these warnings. In addition, there is a patch to gcc to produce such warnings.

Make modules Py_ssize_t clean

Some modules don't use Py_ssize_t. They need a code review. Any module which declares an int (rather than a Py_ssize_t) for size and passes its address to PyArgs_ParseTuple(args, "s#", &str, &size) needs to be updated. An example of a module that has already been updated is Modules/_codecsmodule.c

Check for consistent memory API usage

http://mail.python.org/pipermail/python-dev/2006-March/062848.html

Verify that if PyMem_* APIs are used to (re)allocate memory, that PyMem_* APIs are used to free memory. Same deal with PyObject_* APIs. (ie, ensure that PyMem_* and PyObject_* memory APIs aren't mixed.)

Verify all int/long C APIs are correct

With the conversion to use Py_ssize_t, it's important that we didn't miss any APIs. There are very few APIs which take (or return) a long. But there are still quite a few that take/return an int. All of these are believed to be correct, but more reviewers could help. Any API which returns an int is fine if the value is known to fit in 32 bits (like APIs that return a value between -2 and 2).

Add Py_LOCAL, Py_LOCAL_INLINE declarations

At the NeedForSpeed sprint, these macros were added to use a faster calling convention on Windows. There are probably many modules where these macros could be used.

Currently these macros only make a difference on Windows. Are there other pragmas that could be used with GCC or other compilers?

Use Py_MEMCPY

Py_MEMCPY can be used instead of memcpy in cases where the copied blocks are often very short. While most platforms have highly optimized code for large transfers, the setup costs for memcpy are often quite high. MEMCPY solves this by doing short copies "in line".

Using this macro gave a 20% speed improvement to some string functions. Are there other uses of memcpy() in CPython that would also benefit?

Create tests for sequences over 2GB

It would be great if someone could try to put together some tests for bigmem machines. The tests should be broken up by those that require 2+ GB of memory, those that take 4+, etc. Many people won't have boxes with that much memory. Ultimately, the tests should be incorporated into the test suite with a special designation similar to -u all. I'm thinking -G # where # is the size of RAM in GB.

The test cases should test all methods (don't forget slicing operations) at boundary points, particularly just before and after 2GB. Strings are probably the easiest. There's unicode too. lists, dicts are good but will take more than 16 GB of RAM, so those can be pushed out some.

See http://python.org/sf/1471578

Test suite improvements

See [ImprovingLibTests].

Wiki updates

Update the PerlPhrasebook for the current state of Python and Perl.

Write a Java or Ruby phrasebook.

Clean up the organization of database-related pages in the wiki.

Unable to edit the page? See the FrontPage for instructions.