The embedded 40250 script layer needs its own interpreter on five platforms. 2.7 is end-of-life, so nothing can be fetched from the target SDKs and the source is vendored (official 2.7.18 tarball, trimmed to 25MB; Lib/ stays for step 3's python27.zip). cpython-2.7.18/CMakeLists.txt builds one `mtpython` static library from exactly the 133 objects the reference libpython2.7.a contains, off by default behind -DMTGODOT_EMBED_PYTHON=ON. The source list and the built-in module table (config/config.c, 39 entries) are shared; pyconfig.h is a probe result and is not, so each platform keeps its own under config/<platform>/, regenerated by tools/py_embed/gen_pyconfig.sh and checked against the shared table. Three vendor patches, documented in docs/THIRD-PARTY.md: configure/configure.ac learn arm64 on macOS, and posixmodule.c undefines the process-control calls it hard-defines past pyconfig.h when building for iOS. macOS (ctest python.embed: every builtin imports, codecs and pickle work off the vendored Lib/), Android arm64 and iOS arm64 build. Linux needs a Linux host and Windows needs a MinGW-vs-MSVC decision; both are noted for step 4. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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31 lines
1.2 KiB
Plaintext
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Klocwork has a static analysis tool (K7) which is similar to Coverity.
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They will run their tool on the Python source code on demand.
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The results are available at:
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https://opensource.klocwork.com/
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Currently, only Neal Norwitz has access to the analysis reports. Other
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people can be added by request.
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K7 was first run on the Python 2.5 source code in mid-July 2006.
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This is after Coverity had been making their results available.
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There were originally 175 defects reported. Most of these
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were false positives. However, there were numerous real issues
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also uncovered.
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Each warning has a unique id and comments that can be made on it.
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When checking in changes due to a K7 report, the unique id
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as reported by the tool was added to the SVN commit message.
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A comment was added to the K7 warning indicating the SVN revision
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in addition to any analysis.
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False positives were also annotated so that the comments can
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be reviewed and reversed if the analysis was incorrect.
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A second run was performed on 10-Aug-2006. The tool was tuned to remove
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some false positives and perform some additional checks. ~150 new
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warnings were produced, primarily related to dereferencing NULL pointers.
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Contact python-dev@python.org for more information.
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