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Backport PR #2384: Adapt inline backend to changes in matplotlib...
Backport PR #2384: Adapt inline backend to changes in matplotlib Matplotlib recently merged https://github.com/matplotlib/matplotlib/pull/1125 that makes it simpler to use objective oriented figure creation by automatically creating the right canvas for the backend. To solve that all backends must provide a backend_xxx.FigureCanvas. This is obviosly missing from the inline backend. The change is needed to make the inline backend work with mpl's 1.2.x branch which is due to released soon. Simply setting the default canvas equal to a Agg canvas appears to work for both svg and png figures but I'm not sure weather that is the right approach. Should the canvas depend on the figure format and provide a svg canvas for a svg figure? (Note that before this change to matplotlib the canvas from a plt.figure call seams to be a agg type in all cases) Edit: I made the pull request against 0.13.1 since it would be good to have this in the stable branch for when mpl is released. Just let me know and I can rebase it against master
Brian Granger - - Load All Authors

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.. _history:
=======
History
=======
Origins
=======
IPython was starting in 2001 by Fernando Perez while he was a graduate student
at the University of Colorado, Boulder. IPython as we know it today grew out
of the following three projects:
* ipython by Fernando Pérez. Fernando began using Python and ipython began as
an outgrowth of his desire for things like Mathematica-style prompts, access
to previous output (again like Mathematica's % syntax) and a flexible
configuration system (something better than :envvar:`PYTHONSTARTUP`).
* IPP by Janko Hauser. Very well organized, great usability. Had
an old help system. IPP was used as the "container" code into
which Fernando added the functionality from ipython and LazyPython.
* LazyPython by Nathan Gray. Simple but very powerful. The quick
syntax (auto parens, auto quotes) and verbose/colored tracebacks
were all taken from here.
Here is how Fernando describes the early history of IPython:
When I found out about IPP and LazyPython I tried to join all three
into a unified system. I thought this could provide a very nice
working environment, both for regular programming and scientific
computing: shell-like features, IDL/Matlab numerics, Mathematica-type
prompt history and great object introspection and help facilities. I
think it worked reasonably well, though it was a lot more work than I
had initially planned.