##// END OF EJS Templates
Reset the interactive namespace __warningregistry__ before executing code...
Reset the interactive namespace __warningregistry__ before executing code Fixes #6611. Idea: Right now, people often don't see important warnings when running code in IPython, because (to a first approximation) any given warning will only issue once per session. Blink and you'll miss it! This is a very common contributor to confused emails to numpy-discussion. E.g.: In [5]: 1 / my_array_with_random_contents /home/njs/.user-python2.7-64bit-3/bin/ipython:1: RuntimeWarning: divide by zero encountered in divide #!/home/njs/.user-python2.7-64bit-3/bin/python Out[5]: array([ 1.77073316, -2.29765021, -2.01800811, ..., 1.13871243, -1.08302964, -8.6185091 ]) Oo, right, guess I gotta be careful of those zeros -- thanks, numpy, for giving me that warning! A few days later: In [592]: 1 / some_other_array Out[592]: array([ 3.07735763, 0.50769289, 0.83984078, ..., -0.67563917, -0.85736257, -1.36511271]) Oops, it turns out that this array had a zero in it too, and that's going to bite me later. But no warning this time! The effect of this commit is to make it so that warnings triggered by the code in cell 5 do *not* suppress warnings triggered by the code in cell 592. Note that this only applies to warnings triggered *directly* by code entered interactively -- if somepkg.foo() calls anotherpkg.bad_func() which issues a warning, then this warning will still only be displayed once, even if multiple cells call somepkg.foo(). But if cell 5 and cell 592 both call anotherpkg.bad_func() directly, then both will get warnings. (Important exception: if foo() is defined *interactively*, and calls anotherpkg.bad_func(), then every cell that calls foo() will display the warning again. This is unavoidable without fixes to CPython upstream.) Explanation: Python's warning system has some weird quirks. By default, it tries to suppress duplicate warnings, where "duplicate" means the same warning message triggered twice by the same line of code. This requires determining which line of code is responsible for triggering a warning, and this is controlled by the stacklevel= argument to warnings.warn. Basically, though, the idea is that if foo() calls bar() which calls baz() which calls some_deprecated_api(), then baz() will get counted as being "responsible", and the warning system will make a note that the usage of some_deprecated_api() inside baz() has already been warned about and doesn't need to be warned about again. So far so good. To accomplish this, obviously, there has to be a record of somewhere which line this was. You might think that this would be done by recording the filename:linenumber pair in a dict inside the warnings module, or something like that. You would be wrong. What actually happens is that the warnings module will use stack introspection to reach into baz()'s execution environment, create a global (module-level) variable there named __warningregistry__, and then, inside this dictionary, record just the line number. Basically, it assumes that any given module contains only one line 1, only one line 2, etc., so storing the filename is irrelevant. Obviously for interactive code this is totally wrong -- all cells share the same execution environment and global namespace, and they all contain a new line 1. Currently the warnings module treats these as if they were all the same line. In fact they are not the same line; once we have executed a given chunk of code, we will never see those particular lines again. As soon as a given chunk of code finishes executing, its line number labels become meaningless, and the corresponding warning registry entries become meaningless as well. Therefore, with this patch we delete the __warningregistry__ each time we execute a new block of code.

File last commit:

r12244:99f85cc0
r18548:61431d7d
Show More
CONTRIBUTING.md
40 lines | 1.8 KiB | text/x-minidsrc | MarkdownLexer

Opening an Issue

When opening a new Issue, please take the following steps:

  1. Search GitHub and/or Google for your issue to avoid duplicate reports.
    Keyword searches for your error messages are most helpful.

  2. If possible, try updating to master and reproducing your issue,
    because we may have already fixed it.

  3. Try to include a minimal reproducible test case

  4. Include relevant system information. Start with the output of:

    python -c "import IPython; print(IPython.sys_info())"

    And include any relevant package versions, depending on the issue,
    such as matplotlib, numpy, Qt, Qt bindings (PyQt/PySide), tornado, web browser, etc.

Pull Requests

Some guidelines on contributing to IPython:

  • All work is submitted via Pull Requests.
  • Pull Requests can be submitted as soon as there is code worth discussing.
    Pull Requests track the branch, so you can continue to work after the PR is submitted.
    Review and discussion can begin well before the work is complete,
    and the more discussion the better.
    The worst case is that the PR is closed.
  • Pull Requests should generally be made against master
  • Pull Requests should be tested, if feasible:
    • bugfixes should include regression tests
    • new behavior should at least get minimal exercise
  • New features and backwards-incompatible changes should be documented by adding
    a new file to the pr directory, see the README.md
    there
    for details.

Travis does a pretty good job testing IPython and Pull Requests,
but it may make sense to manually perform tests (possibly with our test_pr script),
particularly for PRs that affect IPython.parallel or Windows.

For more detailed information, see our GitHub Workflow.