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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.
Nathaniel J. Smith -
r18548:61431d7d
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IPython: Productive Interactive Computing

Overview

Welcome to IPython. Our full documentation is available on our website; if you downloaded a built source distribution the docs/source directory contains the plaintext version of these manuals. If you have Sphinx installed, you can build them by typing cd docs; make html for local browsing.

Dependencies and supported Python versions

For full details, see the installation section of the manual. The basic parts of IPython only need the Python standard library, but much of its more advanced functionality requires extra packages.

Officially, IPython requires Python version 2.7, or 3.3 and above. IPython 1.x is the last IPython version to support Python 2.6 and 3.2.

Instant running

You can run IPython from this directory without even installing it system-wide by typing at the terminal:

$ python -m IPython

Development installation

If you want to hack on certain parts, e.g. the IPython notebook, in a clean environment (such as a virtualenv) you can use pip to grab the necessary dependencies quickly:

$ git clone --recursive https://github.com/ipython/ipython.git
$ cd ipython
$ pip install -e ".[notebook]" --user

This installs the necessary packages and symlinks IPython into your current environment so that you can work on your local repo copy and run it from anywhere:

$ ipython notebook

The same process applies for other parts, such as the qtconsole (the extras_require attribute in the setup.py file lists all the possibilities).

Git Hooks and Submodules

IPython now uses git submodules to ship its javascript dependencies. If you run IPython from git master, you may need to update submodules once in a while with:

$ git submodule update

or:

$ python setup.py submodule

We have some git hooks for helping keep your submodules always in sync, see our git-hooks directory for more info.