upstream/ipython Commit - r8064:01e35e51

Backport PR : removed references to h5py dependence in octave magic documentation...

MinRK -

r8064:01e35e51

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IPython/extensions/octavemagic.py

0 +2 -2

             # -*- coding: utf-8 -*-
             """
             ===========
             octavemagic
             ===========
             Magics for interacting with Octave via oct2py.
             .. note::
-              The ``oct2py`` module needs to be installed separately, and in turn depends
+              The ``oct2py`` module needs to be installed separately and
-              on ``h5py``.  Both can be obtained using ``easy_install`` or ``pip``.
+              can be obtained using ``easy_install`` or ``pip``.
             Usage
             =====
             ``%octave``
             {OCTAVE_DOC}
             ``%octave_push``
             {OCTAVE_PUSH_DOC}
             ``%octave_pull``
             {OCTAVE_PULL_DOC}
             """
             #-----------------------------------------------------------------------------
             #  Copyright (C) 2012 The IPython Development Team
             #
             #  Distributed under the terms of the BSD License.  The full license is in
             #  the file COPYING, distributed as part of this software.
             #-----------------------------------------------------------------------------
             import tempfile
             from glob import glob
             from shutil import rmtree
             import numpy as np
             import oct2py
             from xml.dom import minidom
             from IPython.core.displaypub import publish_display_data
             from IPython.core.magic import (Magics, magics_class, line_magic,
                                             line_cell_magic)
             from IPython.testing.skipdoctest import skip_doctest
             from IPython.core.magic_arguments import (
                 argument, magic_arguments, parse_argstring
             )
             from IPython.utils.py3compat import unicode_to_str
             class OctaveMagicError(oct2py.Oct2PyError):
                 pass
             _mimetypes = {'png' : 'image/png',
                          'svg' : 'image/svg+xml',
                          'jpg' : 'image/jpeg',
                           'jpeg': 'image/jpeg'}
             @magics_class
             class OctaveMagics(Magics):
                 """A set of magics useful for interactive work with Octave via oct2py.
                 """
                 def __init__(self, shell):
                     """
                     Parameters
                     ----------
                     shell : IPython shell
                     """
                     super(OctaveMagics, self).__init__(shell)
                     self._oct = oct2py.Oct2Py()
                     self._plot_format = 'png'
                     # Allow publish_display_data to be overridden for
                     # testing purposes.
                     self._publish_display_data = publish_display_data
                 def _fix_gnuplot_svg_size(self, image, size=None):
                     """
                     GnuPlot SVGs do not have height/width attributes.  Set
                     these to be the same as the viewBox, so that the browser
                     scales the image correctly.
                     Parameters
                     ----------
                     image : str
                         SVG data.
                     size : tuple of int
                         Image width, height.
                     """
                     (svg,) = minidom.parseString(image).getElementsByTagName('svg')
                     viewbox = svg.getAttribute('viewBox').split(' ')
                     if size is not None:
                         width, height = size
                     else:
                         width, height = viewbox[2:]
                     svg.setAttribute('width', '%dpx' % width)
                     svg.setAttribute('height', '%dpx' % height)
                     return svg.toxml()
                 @skip_doctest
                 @line_magic
                 def octave_push(self, line):
                     '''
                     Line-level magic that pushes a variable to Octave.
                     `line` should be made up of whitespace separated variable names in the
                     IPython namespace::
                         In [7]: import numpy as np
                         In [8]: X = np.arange(5)
                         In [9]: X.mean()
                         Out[9]: 2.0
                         In [10]: %octave_push X
                         In [11]: %octave mean(X)
                         Out[11]: 2.0
                     '''
                     inputs = line.split(' ')
                     for input in inputs:
                         input = unicode_to_str(input)
                         self._oct.put(input, self.shell.user_ns[input])
                 @skip_doctest
                 @line_magic
                 def octave_pull(self, line):
                     '''
                     Line-level magic that pulls a variable from Octave.
                         In [18]: _ = %octave x = [1 2; 3 4]; y = 'hello'
                         In [19]: %octave_pull x y
                         In [20]: x
                         Out[20]:
                         array([[ 1.,  2.],
                                [ 3.,  4.]])
                         In [21]: y
                         Out[21]: 'hello'
                     '''
                     outputs = line.split(' ')
                     for output in outputs:
                         output = unicode_to_str(output)
                         self.shell.push({output: self._oct.get(output)})
                 @skip_doctest
                 @magic_arguments()
                 @argument(
                     '-i', '--input', action='append',
                     help='Names of input variables to be pushed to Octave. Multiple names '
                          'can be passed, separated by commas with no whitespace.'
                     )
                 @argument(
                     '-o', '--output', action='append',
                     help='Names of variables to be pulled from Octave after executing cell '
                          'body. Multiple names can be passed, separated by commas with no '
                          'whitespace.'
                     )
                 @argument(
                     '-s', '--size', action='store',
                     help='Pixel size of plots, "width,height". Default is "-s 400,250".'
                     )
                 @argument(
                     '-f', '--format', action='store',
                     help='Plot format (png, svg or jpg).'
                     )
                 @argument(
                     'code',
                     nargs='*',
                     )
                 @line_cell_magic
                 def octave(self, line, cell=None):
                     '''
                     Execute code in Octave, and pull some of the results back into the
                     Python namespace.
                         In [9]: %octave X = [1 2; 3 4]; mean(X)
                         Out[9]: array([[ 2., 3.]])
                     As a cell, this will run a block of Octave code, without returning any
                     value::
                         In [10]: %%octave
                            ....: p = [-2, -1, 0, 1, 2]
                            ....: polyout(p, 'x')
                         -2*x^4 - 1*x^3 + 0*x^2 + 1*x^1 + 2
                     In the notebook, plots are published as the output of the cell, e.g.
                     %octave plot([1 2 3], [4 5 6])
                     will create a line plot.
                     Objects can be passed back and forth between Octave and IPython via the
                     -i and -o flags in line::
                         In [14]: Z = np.array([1, 4, 5, 10])
                         In [15]: %octave -i Z mean(Z)
                         Out[15]: array([ 5.])
                         In [16]: %octave -o W W = Z * mean(Z)
                         Out[16]: array([  5.,  20.,  25.,  50.])
                         In [17]: W
                         Out[17]: array([  5.,  20.,  25.,  50.])
                     The size and format of output plots can be specified::
                         In [18]: %%octave -s 600,800 -f svg
                             ...: plot([1, 2, 3]);
                     '''
                     args = parse_argstring(self.octave, line)
                     # arguments 'code' in line are prepended to the cell lines
                     if cell is None:
                         code = ''
                         return_output = True
                         line_mode = True
                     else:
                         code = cell
                         return_output = False
                         line_mode = False
                     code = ' '.join(args.code) + code
                     if args.input:
                         for input in ','.join(args.input).split(','):
                             input = unicode_to_str(input)
                             self._oct.put(input, self.shell.user_ns[input])
                     # generate plots in a temporary directory
                     plot_dir = tempfile.mkdtemp()
                     if args.size is not None:
                         size = args.size
                     else:
                         size = '400,240'
                     if args.format is not None:
                         plot_format = args.format
                     else:
                         plot_format = 'png'
                     pre_call = '''
                     global __ipy_figures = [];
                     page_screen_output(0);
                     function fig_create(src, event)
                       global __ipy_figures;
                       __ipy_figures(size(__ipy_figures) + 1) = src;
                       set(src, "visible", "off");
                     end
                     set(0, 'DefaultFigureCreateFcn', @fig_create);
                     close all;
                     clear ans;
                     # ___<end_pre_call>___ #
                     '''
                     post_call = '''
                     # ___<start_post_call>___ #
                     # Save output of the last execution
                     if exist("ans") == 1
                       _ = ans;
                     else
                       _ = nan;
                     end
                     for f = __ipy_figures
                       outfile = sprintf('%(plot_dir)s/__ipy_oct_fig_%%03d.png', f);
                       try
                         print(f, outfile, '-d%(plot_format)s', '-tight', '-S%(size)s');
                       end
                     end
                     ''' % locals()
                     code = ' '.join((pre_call, code, post_call))
                     try:
                         text_output = self._oct.run(code, verbose=False)
                     except (oct2py.Oct2PyError) as exception:
                         msg = exception.message
                         msg = msg.split('# ___<end_pre_call>___ #')[1]
                         msg = msg.split('# ___<start_post_call>___ #')[0]
                         raise OctaveMagicError('Octave could not complete execution.  '
                                                'Traceback (currently broken in oct2py): %s'
                                                % msg)
                     key = 'OctaveMagic.Octave'
                     display_data = []
                     # Publish text output
                     if text_output:
                         display_data.append((key, {'text/plain': text_output}))
                     # Publish images
                     images = [open(imgfile, 'rb').read() for imgfile in \
                               glob("%s/*" % plot_dir)]
                     rmtree(plot_dir)
                     plot_mime_type = _mimetypes.get(plot_format, 'image/png')
                     width, height = [int(s) for s in size.split(',')]
                     for image in images:
                         if plot_format == 'svg':
                             image = self._fix_gnuplot_svg_size(image, size=(width, height))
                         display_data.append((key, {plot_mime_type: image}))
                     if args.output:
                         for output in ','.join(args.output).split(','):
                             output = unicode_to_str(output)
                             self.shell.push({output: self._oct.get(output)})
                     for source, data in display_data:
                         self._publish_display_data(source, data)
                     if return_output:
                         ans = self._oct.get('_')
                         # Unfortunately, Octave doesn't have a "None" object,
                         # so we can't return any NaN outputs
                         if np.isscalar(ans) and np.isnan(ans):
                             ans = None
                         return ans
             __doc__ = __doc__.format(
                 OCTAVE_DOC = ' '*8 + OctaveMagics.octave.__doc__,
                 OCTAVE_PUSH_DOC = ' '*8 + OctaveMagics.octave_push.__doc__,
                 OCTAVE_PULL_DOC = ' '*8 + OctaveMagics.octave_pull.__doc__
                 )
             _loaded = False
             def load_ipython_extension(ip):
                 """Load the extension in IPython."""
                 global _loaded
                 if not _loaded:
                     ip.register_magics(OctaveMagics)
                     _loaded = True

docs/examples/notebooks/octavemagic_extension.ipynb

0 +1 -1

             {
              "metadata": {
               "name": "octavemagic_extension"
              },
              "nbformat": 3,
              "nbformat_minor": 0,
              "worksheets": [
               {
                "cells": [
                 {
                  "cell_type": "heading",
                  "level": 1,
                  "metadata": {},
                  "source": [
                   "octavemagic: Octave inside IPython"
                  ]
                 },
                 {
                  "cell_type": "heading",
                  "level": 2,
                  "metadata": {},
                  "source": [
                   "Installation"
                  ]
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
-                  "The `octavemagic` extension provides the ability to interact with Octave.  It depends on the `oct2py` and `h5py` packages,\n",
+                  "The `octavemagic` extension provides the ability to interact with Octave.  It depends on the `oct2py` package,\n",
                   "which may be installed using `easy_install`.\n",
                   "\n",
                   "To enable the extension, load it as follows:"
                  ]
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "%load_ext octavemagic"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [],
                  "prompt_number": 18
                 },
                 {
                  "cell_type": "heading",
                  "level": 2,
                  "metadata": {},
                  "source": [
                   "Overview"
                  ]
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
                   "Loading the extension enables three magic functions: `%octave`, `%octave_push`, and `%octave_pull`.\n",
                   "\n",
                   "The first is for executing one or more lines of Octave, while the latter allow moving variables between the Octave and Python workspace.\n",
                   "Here you see an example of how to execute a single line of Octave, and how to transfer the generated value back to Python:"
                  ]
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "x = %octave [1 2; 3 4];\n",
                   "x"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "pyout",
                    "prompt_number": 19,
                    "text": [
                     "array([[ 1.,  2.],\n",
                     "       [ 3.,  4.]])"
                    ]
                   }
                  ],
                  "prompt_number": 19
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "a = [1, 2, 3]\n",
                   "\n",
                   "%octave_push a\n",
                   "%octave a = a * 2;\n",
                   "%octave_pull a\n",
                   "a"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "pyout",
                    "prompt_number": 20,
                    "text": [
                     "array([[2, 4, 6]])"
                    ]
                   }
                  ],
                  "prompt_number": 20
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
                   "When using the cell magic, `%%octave` (note the double `%`), multiple lines of Octave can be executed together.  Unlike\n",
                   "with the single cell magic, no value is returned, so we use the `-i` and `-o` flags to specify input and output variables."
                  ]
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "%%octave -i x -o y\n",
                   "y = x + 3;"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [],
                  "prompt_number": 21
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "y"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "pyout",
                    "prompt_number": 22,
                    "text": [
                     "array([[ 4.,  5.],\n",
                     "       [ 6.,  7.]])"
                    ]
                   }
                  ],
                  "prompt_number": 22
                 },
                 {
                  "cell_type": "heading",
                  "level": 2,
                  "metadata": {},
                  "source": [
                   "Plotting"
                  ]
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
                   "Plot output is automatically captured and displayed, and using the `-f` flag you may choose its format (currently, `png` and `svg` are supported)."
                  ]
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "%%octave -f svg\n",
                   "\n",
                   "p = [12 -2.5 -8 -0.1 8];\n",
                   "x = 0:0.01:1;\n",
                   "\n",
                   "polyout(p, 'x')\n",
                   "plot(x, polyval(p, x));"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "display_data",
                    "text": [
                     "12*x^4 - 2.5*x^3 - 8*x^2 - 0.1*x^1 + 8"
                    ]
                   },
                   {
                    "output_type": "display_data",
                    "svg": [
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                     "</g>\n",
                     "\t<a xlink:title=\"Plot #1\">\n",
                     "<g style=\"fill:none; color:red; stroke:currentColor; stroke-width:0.50; stroke-linecap:butt; stroke-linejoin:miter\">\n",
                     "\t<path d=\"M36.4,45.5 L37.8,45.6 L39.2,45.7 L40.6,45.8 L42.1,45.9 L43.5,46.1 L44.9,46.3 L46.3,46.6    L47.7,46.9 L49.1,47.3 L50.6,47.6 L52.0,48.0 L53.4,48.5 L54.8,49.0 L56.2,49.5 L57.6,50.0    L59.0,50.6 L60.5,51.3 L61.9,51.9 L63.3,52.6 L64.7,53.3 L66.1,54.1 L67.5,54.9 L68.9,55.7    L70.4,56.5 L71.8,57.3 L73.2,58.2 L74.6,59.1 L76.0,60.1 L77.4,61.0 L78.9,62.0 L80.3,63.0    L81.7,64.0 L83.1,65.0 L84.5,66.0 L85.9,67.0 L87.3,68.1 L88.8,69.1 L90.2,70.2 L91.6,71.3    L93.0,72.3 L94.4,73.4 L95.8,74.4 L97.2,75.5 L98.7,76.5 L100.1,77.5 L101.5,78.5 L102.9,79.5    L104.3,80.5 L105.7,81.4 L107.2,82.4 L108.6,83.2 L110.0,84.1 L111.4,84.9 L112.8,85.7 L114.2,86.5    L115.6,87.2 L117.1,87.8 L118.5,88.4 L119.9,89.0 L121.3,89.5 L122.7,89.9 L124.1,90.3 L125.5,90.6    L127.0,90.8 L128.4,91.0 L129.8,91.0 L131.2,91.0 L132.6,90.9 L134.0,90.7 L135.5,90.4 L136.9,90.0    L138.3,89.5 L139.7,88.9 L141.1,88.2 L142.5,87.4 L143.9,86.4 L145.4,85.3 L146.8,84.1 L148.2,82.8    L149.6,81.3 L151.0,79.6 L152.4,77.8 L153.8,75.9 L155.3,73.8 L156.7,71.5 L158.1,69.0 L159.5,66.4    L160.9,63.6 L162.3,60.6 L163.8,57.4 L165.2,54.0 L166.6,50.4 L168.0,46.6 L169.4,42.6 L170.8,38.3    L172.2,33.9 L173.7,29.2 L175.1,24.2 L176.5,19.0 L177.9,13.6 \" stroke=\"rgb(  0,   0, 255)\"/>\n",
                     "</g>\n",
                     "\t</a>\n",
                     "<g style=\"fill:none; color:black; stroke:currentColor; stroke-width:0.50; stroke-linecap:butt; stroke-linejoin:miter\">\n",
                     "</g>\n",
                     "</svg>"
                    ]
                   }
                  ],
                  "prompt_number": 23
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
                   "The plot size is adjusted using the `-s` flag:"
                  ]
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "%%octave -s 500,500\n",
                   "\n",
                   "# butterworth filter, order 2, cutoff pi/2 radians\n",
                   "b = [0.292893218813452  0.585786437626905  0.292893218813452];\n",
                   "a = [1  0  0.171572875253810];\n",
                   "freqz(b, a, 32);"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "display_data",
                    "png": 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2ZvTl5+jRo0WrkCu02YtuPQtKEYTRdR32HzmO02q1NE0LP0L9gjCTmZ+fX1xcjPquoJdv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\noLWOJ5MfPqUANvwAgmKwshJ2uRwAAAAASUVORK5CYII=\n"
                   }
                  ],
                  "prompt_number": 24
                 },
                 {
                  "cell_type": "code",
                  "collapsed": false,
                  "input": [
                   "%%octave -s 600,200 -f png\n",
                   "\n",
                   "subplot(121);\n",
                   "[x, y] = meshgrid(0:0.1:3);\n",
                   "r = sin(x - 0.5).^2 + cos(y - 0.5).^2;\n",
                   "surf(x, y, r);\n",
                   "\n",
                   "subplot(122);\n",
                   "sombrero()"
                  ],
                  "language": "python",
                  "metadata": {},
                  "outputs": [
                   {
                    "output_type": "display_data",
                    "png": 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o+c0vuXcdy7LFFxupVMr3KaNMwCoUiqSkpLCwsNDQ0MDAwN27dxe/TpNTDoRQ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\n"
                   }
                  ],
                  "prompt_number": 25
                 },
                 {
                  "cell_type": "heading",
                  "level": 2,
                  "metadata": {},
                  "source": [
                   "Future work"
                  ]
                 },
                 {
                  "cell_type": "markdown",
                  "metadata": {},
                  "source": [
                   "After the next release of `oct2py`, we'll add the ability to interrupt/kill the current Octave session without restarting the Python kernel."
                  ]
                 }
                ],
                "metadata": {}
               }
              ]
             }

docs/source/whatsnew/version0.13.txt

0 +1 -2

             =============
 .13 Series
             =============
             Release 0.13
             ============
             IPython 0.13 contains several major new features, as well as a large amount of
             bug and regression fixes.  The previous version (0.12) was released on December
 2011, and in this development cycle we had:
             - ~6 months of work.
             - 373 pull requests merged.
             - 742 issues closed (non-pull requests).
             - contributions from 62 authors.
             - 1760 commits.
             - a diff of 114226 lines.
             The amount of work included in this release is so large, that we can only cover
             here the main highlights; please see our :ref:`detailed release statistics
             <issues_list_013>` for links to every issue and pull request closed on GitHub
             as well as a full list of individual contributors.
             Major Notebook improvements: new user interface and more
             --------------------------------------------------------
             The IPython Notebook, which has proven since its release to be wildly popular,
             has seen a massive amount of work in this release cycle, leading to a
             significantly improved user experience as well as many new features.
             The first user-visible change is a reorganization of the user interface; the
             left panel has been removed and was replaced by a real menu system and a
             toolbar with icons.  Both the toolbar and the header above the menu can be
             collapsed to leave an unobstructed working area:
             .. image:: ../_static/ipy_013_notebook_spectrogram.png
                 :width: 460px
                 :alt: New user interface for Notebook
                 :align: center
                 :target: ../_static/ipy_013_notebook_spectrogram.png
             The notebook handles very long outputs much better than before (this was a
             serious usability issue when running processes that generated massive amounts
             of output).  Now, in the presence of outputs longer than ~100 lines, the
             notebook will automatically collapse to a scrollable area and the entire left
             part of this area controls the display: one click in this area will expand the
             output region completely, and a double-click will hide it completely.  This
             figure shows both the scrolled and hidden modes:
             .. image:: ../_static/ipy_013_notebook_long_out.png
                 :width: 460px
                 :alt: Scrolling and hiding of long output in the notebook.
                 :align: center
                 :target: ../_static/ipy_013_notebook_long_out.png
             .. note::
                The auto-folding of long outputs is disabled in Firefox due to bugs in its
                scrolling behavior.  See :ghpull:`2047` for details.
             Uploading notebooks to the dashboard is now easier: in addition to drag and
             drop (which can be finicky sometimes), you can now click on the upload text and
             use a regular file dialog box to select notebooks to upload. Furthermore, the
             notebook dashboard now auto-refreshes its contents and offers buttons to shut
             down any running kernels (:ghpull:`1739`):
             .. image:: ../_static/ipy_013_dashboard.png
                 :width: 460px
                 :alt: Improved dashboard
                 :align: center
                 :target: ../_static/ipy_013_dashboard.png
             Cluster management
             ~~~~~~~~~~~~~~~~~~
             The notebook dashboard can now also start and stop clusters, thansk to a new
             tab in the dashboard user interface:
             .. image:: ../_static/ipy_013_dashboard_cluster.png
                 :width: 460px
                 :alt: Cluster management from the notebook dashboard
                 :align: center
                 :target: ../_static/ipy_013_dashboard_cluster.png
             This interface allows, for each profile you have configured, to start and stop
             a cluster (and optionally override the default number of engines corresponding
             to that configuration).  While this hides all error reporting, once you have a
             configuration that you know works smoothly, it is a very convenient interface
             for controlling your parallel resources.
             New notebook format
             ~~~~~~~~~~~~~~~~~~~
             The notebooks saved now use version 3 of our format, which supports heading
             levels as well as the concept of 'raw' text cells that are not rendered as
             Markdown.  These will be useful with converters_ we are developing, to pass raw
             markup (say LaTeX).  That conversion code is still under heavy development and
             not quite ready for prime time, but we welcome help on this front so that we
             can merge it for full production use as soon as possible.
             .. _converters: https://github.com/ipython/nbconvert
             .. note::
                v3 notebooks can *not* be read by older versions of IPython, but we provide
                a `simple script`_ that you can use in case you need to export a v3
                notebook to share with a v2 user.
             .. _simple script: https://gist.github.com/1935808
             JavaScript refactoring
             ~~~~~~~~~~~~~~~~~~~~~~
             All the client-side JavaScript has been decoupled to ease reuse of parts of the
             machinery without having to build a full-blown notebook. This will make it much
             easier to communicate with an IPython kernel from existing web pages and to
             integrate single cells into other sites, without loading the full notebook
             document-like UI. :ghpull:`1711`.
             This refactoring also enables the possibility of writing dynamic javascript
             widgets that are returned from Python code and that present an interactive view
             to the user, with callbacks in Javascript executing calls to the Kernel.  This
             will enable many interactive elements to be added by users in notebooks.
             An example of this capability has been provided as a proof of concept in
             :file:`docs/examples/widgets` that lets you directly communicate with one or more
             parallel engines, acting as a mini-console for parallel debugging and
             introspection.
             Improved tooltips
             ~~~~~~~~~~~~~~~~~
             The object tooltips have gained some new functionality. By pressing tab several
             times, you can expand them to see more of a docstring, keep them visible as you
             fill in a function's parameters, or transfer the information to the pager at the
             bottom of the screen. For the details, look at the example notebook
             :file:`01_notebook_introduction.ipynb`.
             .. figure:: ../_static/ipy_013_notebook_tooltip.png
                 :width: 460px
                 :alt: Improved tooltips in the notebook.
                 :align: center
                 :target: ../_static/ipy_013_notebook_tooltip.png
                 The new notebook tooltips.
             Other improvements to the Notebook
             ----------------------------------
             These are some other notable small improvements to the notebook, in addition to
             many bug fixes and minor changes to add polish and robustness throughout:
             * The notebook pager (the area at the bottom) is now resizeable by dragging its
               divider handle, a feature that had been requested many times by just about
               anyone who had used the notebook system.  :ghpull:`1705`.
             * It is now possible to open notebooks directly from the command line; for
               example: ``ipython notebook path/`` will automatically set ``path/`` as the
               notebook directory, and ``ipython notebook path/foo.ipynb`` will further
               start with the ``foo.ipynb`` notebook opened.  :ghpull:`1686`.
             * If a notebook directory is specified with ``--notebook-dir`` (or with the
               corresponding configuration flag ``NotebookManager.notebook_dir``), all
               kernels start in this directory.
             * Fix codemirror clearing of cells with ``Ctrl-Z``; :ghpull:`1965`.
             * Text (markdown) cells now line wrap correctly in the notebook, making them
               much easier to edit :ghpull:`1330`.
             * PNG and JPEG figures returned from plots can be interactively resized in the
               notebook, by dragging them from their lower left corner. :ghpull:`1832`.
             * Clear ``In []`` prompt numbers on "Clear All Output".  For more
               version-control-friendly ``.ipynb`` files, we now strip all prompt numbers
               when doing a "Clear all output".  This reduces the amount of noise in
               commit-to-commit diffs that would otherwise show the (highly variable) prompt
               number changes. :ghpull:`1621`.
             * The notebook server now requires *two* consecutive ``Ctrl-C`` within 5
               seconds (or an interactive confirmation) to terminate operation.  This makes
               it less likely that you will accidentally kill a long-running server by
               typing ``Ctrl-C`` in the wrong terminal.  :ghpull:`1609`.
             * Using ``Ctrl-S`` (or ``Cmd-S`` on a Mac) actually saves the notebook rather
               than providing the fairly useless browser html save dialog.  :ghpull:`1334`.
             * Allow accessing local files from the notebook (in urls), by serving any local
               file as the url ``files/<relativepath>``.  This makes it possible to, for
               example, embed local images in a notebook.  :ghpull:`1211`.
             Cell magics
             -----------
             We have completely refactored the magic system, finally moving the magic
             objects to standalone, independent objects instead of being the mixin class
             we'd had since the beginning of IPython (:ghpull:`1732`).  Now, a separate base
             class is provided in :class:`IPython.core.magic.Magics` that users can subclass
             to create their own magics.  Decorators are also provided to create magics from
             simple functions without the need for object orientation.  Please see the
             :ref:`magic` docs for further details.
             All builtin magics now exist in a few subclasses that group together related
             functionality, and the new :mod:`IPython.core.magics` package has been created
             to organize this into smaller files.
             This cleanup was the last major piece of deep refactoring needed from the
             original 2001 codebase.
             We have also introduced a new type of magic function, prefixed with `%%`
             instead of `%`, which operates at the whole-cell level.  A cell magic receives
             two arguments: the line it is called on (like a line magic) and the body of the
             cell below it.
             Cell magics are most natural in the notebook, but they also work in the
             terminal and qt console, with the usual approach of using a blank line to
             signal cell termination.
             For example, to time the execution of several statements::
                 %%timeit x = 0   # setup
                 for i in range(100000):
                     x += i**2
             This is particularly useful to integrate code in another language, and cell
             magics already exist for shell scripts, Cython, R and Octave. Using ``%%script
             /usr/bin/foo``, you can run a cell in any interpreter that accepts code via
             stdin.
             Another handy cell magic makes it easy to write short text files: ``%%file
             ~/save/to/here.txt``.
             The following cell magics are now included by default; all those that use
             special interpreters (Perl, Ruby, bash, etc.) assume you have the requisite
             interpreter installed:
             * ``%%!``: run cell body with the underlying OS shell; this is similar to
               prefixing every line in the cell with ``!``.
             * ``%%bash``: run cell body under bash.
             * ``%%capture``: capture the output of the code in the cell (and stderr as
               well).  Useful to run codes that produce too much output that you don't even
               want scrolled.
             * ``%%file``: save cell body as a file.
             * ``%%perl``: run cell body using Perl.
             * ``%%prun``: run cell body with profiler (cell extension of ``%prun``).
             * ``%%python3``: run cell body using Python 3.
             * ``%%ruby``: run cell body using Ruby.
             * ``%%script``: run cell body with the script specified in the first line.
             * ``%%sh``: run cell body using sh.
             * ``%%sx``: run cell with system shell and capture process output (cell
               extension of ``%sx``).
             * ``%%system``: run cell with system shell (``%%!`` is an alias to this).
             * ``%%timeit``: time the execution of the cell (extension of ``%timeit``).
             This is what some of the script-related magics look like in action:
             .. image:: ../_static/ipy_013_notebook_script_cells.png
                 :width: 460px
                 :alt: Cluster management from the notebook dashboard
                 :align: center
                 :target: ../_static/ipy_013_notebook_script_cells.png
             In addition, we have also a number of :ref:`extensions <extensions_overview>`
             that provide specialized magics.  These typically require additional software
             to run and must be manually loaded via ``%load_ext <extension name>``, but are
             extremely useful.  The following extensions are provided:
             **Cython magics** (extension :ref:`cythonmagic <extensions_cythonmagic>`)
                 This extension provides magics to automatically build and compile Python
                 extension modules using the Cython_ language. You must install Cython
                 separately, as well as a C compiler, for this to work.  The examples
                 directory in the source distribution ships with a full notebook
                 demonstrating these capabilities:
             .. image:: ../_static/ipy_013_notebook_cythonmagic.png
                 :width: 460px
                 :alt: Cython magic
                 :align: center
                 :target: ../_static/ipy_013_notebook_cythonmagic.png
             .. _cython: http://cython.org
             **Octave magics** (extension :ref:`octavemagic <extensions_octavemagic>`)
                 This extension provides several magics that support calling code written in
                 the Octave_ language for numerical computing.  You can execute single-lines
                 or whole blocks of Octave code, capture both output and figures inline
                 (just like matplotlib plots), and have variables automatically converted
                 between the two languages.  To use this extension, you must have Octave
-                installed as well as the oct2py_ and h5py_ packages.  The examples
+                installed as well as the oct2py_ package.  The examples
                 directory in the source distribution ships with a full notebook
                 demonstrating these capabilities:
             .. image:: ../_static/ipy_013_notebook_octavemagic.png
                 :width: 460px
                 :alt: Octave magic
                 :align: center
                 :target: ../_static/ipy_013_notebook_octavemagic.png
             .. _octave: http://www.gnu.org/software/octave
             .. _oct2py: http://pypi.python.org/pypi/oct2py
-            .. _h5py: http://code.google.com/p/h5py
             **R magics** (extension :ref:`rmagic <extensions_rmagic>`)
                 This extension provides several magics that support calling code written in
                 the R_ language for statistical data analysis.  You can execute
                 single-lines or whole blocks of R code, capture both output and figures
                 inline (just like matplotlib plots), and have variables automatically
                 converted between the two languages.  To use this extension, you must have
                 R installed as well as the rpy2_ package that bridges Python and R.  The
                 examples directory in the source distribution ships with a full notebook
                 demonstrating these capabilities:
             .. image:: ../_static/ipy_013_notebook_rmagic.png
                 :width: 460px
                 :alt: R magic
                 :align: center
                 :target: ../_static/ipy_013_notebook_rmagic.png
             .. _R: http://www.r-project.org
             .. _rpy2: http://rpy.sourceforge.net/rpy2.html
             Tab completer improvements
             --------------------------
             Useful tab-completion based on live inspection of objects is one of the most
             popular features of IPython. To make this process even more user-friendly, the
             completers of both the Qt console and the Notebook have been reworked.
             The Qt console comes with a new ncurses-like tab completer, activated by
             default, which lets you cycle through the available completions by pressing tab,
             or select a completion with the arrow keys (:ghpull:`1851`).
             .. figure:: ../_static/ipy_013_qtconsole_completer.png
                 :width: 460px
                 :alt: ncurses-like completer, with highlighted selection.
                 :align: center
                 :target: ../_static/ipy_013_qtconsole_completer.png
                 The new improved Qt console's ncurses-like completer allows to easily
                 navigate thought long list of completions.
             In the notebook, completions are now sourced both from object introspection and
             analysis of surrounding code, so limited completions can be offered for
             variables defined in the current cell, or while the kernel is busy
             (:ghpull:`1711`).
             We have implemented a new configurable flag to control tab completion on
             modules that provide the ``__all__`` attribute::
               IPCompleter.limit_to__all__= Boolean
             This instructs the completer to honor ``__all__`` for the completion.
             Specifically, when completing on ``object.<tab>``, if True: only those names
             in ``obj.__all__`` will be included.  When False [default]: the ``__all__``
             attribute is ignored. :ghpull:`1529`.
             Improvements to the Qt console
             ------------------------------
             The Qt console continues to receive improvements and refinements, despite the
             fact that it is by now a fairly mature and robust component.  Lots of small
             polish has gone into it, here are a few highlights:
             * A number of changes were made to the underlying code for easier integration
               into other projects such as Spyder_ (:ghpull:`2007`, :ghpull:`2024`).
             * Improved menus with a new Magic menu that is organized by magic groups (this
               was made possible by the reorganization of the magic system
               internals). :ghpull:`1782`.
             * Allow for restarting kernels without clearing the qtconsole, while leaving a
               visible indication that the kernel has restarted. :ghpull:`1681`.
             * Allow the native display of jpeg images in the qtconsole. :ghpull:`1643`.
             .. _spyder: https://code.google.com/p/spyderlib
             Parallel
             --------
             The parallel tools have been improved and fine-tuned on multiple fronts.  Now,
             the creation of an :class:`IPython.parallel.Client` object automatically
             activates a line and cell magic function ``px`` that sends its code to all the
             engines. Further magics can be easily created with the :meth:`.Client.activate`
             method, to conveniently execute code on any subset of engines. :ghpull:`1893`.
             The ``%%px`` cell magic can also be given an optional targets argument, as well
             as a ``--out`` argument for storing its output.
             A new magic has also been added, ``%pxconfig``, that lets you configure various
             defaults of the parallel magics.  As usual, type  ``%pxconfig?`` for details.
             The exception reporting in parallel contexts has been improved to be easier to
             read.  Now, IPython directly reports the remote exceptions without showing any
             of the internal execution parts:
             .. image::  ../_static/ipy_013_par_tb.png
                 :width: 460px
                 :alt: Improved parallel exceptions.
                 :align: center
                 :target: ../_static/ipy_013_par_tb.png
             The parallel tools now default to using ``NoDB`` as the storage backend for
             intermediate results.  This means that the default usage case will have a
             significantly reduced memory footprint, though certain advanced features are
             not available with this backend.  For more details, see :ref:`parallel_db`.
             The parallel magics now display all output, so you can do parallel plotting or
             other actions with complex display.  The ``px`` magic has now both line and cell
             modes, and in cell mode finer control has been added about how to collate
             output from multiple engines. :ghpull:`1768`.
             There have also been incremental improvements to the SSH launchers:
             * add to_send/fetch steps for moving connection files around.
             * add SSHProxyEngineSetLauncher, for invoking to `ipcluster engines` on a
               remote host. This can be used to start a set of engines via PBS/SGE/MPI
               *remotely*.
             This makes the SSHLauncher usable on machines without shared filesystems.
             A number of 'sugar' methods/properties were added to AsyncResult that are
             quite useful (:ghpull:`1548`) for everday work:
                 * ``ar.wall_time`` = received - submitted
                 * ``ar.serial_time`` = sum of serial computation time
                 * ``ar.elapsed`` = time since submission (wall_time if done)
                 * ``ar.progress`` = (int) number of sub-tasks that have completed
                 * ``len(ar)`` = # of tasks
                 * ``ar.wait_interactive()``: prints progress
             Added :meth:`.Client.spin_thread` / :meth:`~.Client.stop_spin_thread` for
             running spin in a background thread, to keep zmq queue clear.  This can be used
             to ensure that timing information is as accurate as possible (at the cost of
             having a background thread active).
             Set TaskScheduler.hwm default to 1 instead of 0.  1 has more
             predictable/intuitive behavior, if often slower, and thus a more logical
             default.  Users whose workloads require maximum throughput and are largely
             homogeneous in time per task can make the optimization themselves, but now the
             behavior will be less surprising to new users. :ghpull:`1294`.
             Kernel/Engine unification
             -------------------------
             This is mostly work 'under the hood', but it is actually a *major* achievement
             for the project that has deep implications in the long term: at last, we have
             unified the main object that executes as the user's interactive shell (which we
             refer to as the *IPython kernel*) with the objects that run in all the worker
             nodes of the parallel computing facilities (the *IPython engines*).  Ever since
             the first implementation of IPython's parallel code back in 2006, we had wanted
             to have these two roles be played by the same machinery, but a number of
             technical reasons had prevented that from being true.
             In this release we have now merged them, and this has a number of important
             consequences:
             * It is now possible to connect any of our clients (qtconsole or terminal
               console) to any individual parallel engine, with the *exact* behavior of
               working at a 'regular' IPython console/qtconsole.  This makes debugging,
               plotting, etc. in parallel scenarios vastly easier.
             * Parallel engines can always execute arbitrary 'IPython code', that is, code
               that has magics, shell extensions, etc.  In combination with the ``%%px``
               magics, it is thus extremely natural for example to send to all engines a
               block of Cython or R code to be executed via the new Cython and R magics. For
               example, this snippet would send the R block to all active engines in a
               cluster::
                 %%px
                 %%R
                 ... R code goes here
             * It is possible to embed not only an interactive shell with the
               :func:`IPython.embed` call as always, but now you can also embed a *kernel*
               with :func:`IPython.embed_kernel()`.  Embedding an IPython kernel in an
               application is useful when you want to use :func:`IPython.embed` but don't
               have a terminal attached on stdin and stdout.
             * The new :func:`IPython.parallel.bind_kernel` allows you to promote Engines to
               listening Kernels, and connect QtConsoles to an Engine and debug it
               directly.
             In addition, having a single core object through our entire architecture also
             makes the project conceptually cleaner, easier to maintain and more robust.
             This took a lot of work to get in place, but we are thrilled to have this major
             piece of architecture finally where we'd always wanted it to be.
             Official Public API
             -------------------
             We have begun organizing our API for easier public use, with an eye towards an
             official IPython 1.0 release which will firmly maintain this API compatible for
             its entire lifecycle.  There is now an :mod:`IPython.display` module that
             aggregates all display routines, and the :mod:`IPython.config` namespace has
             all public configuration tools.  We will continue improving our public API
             layout so that users only need to import names one level deeper than the main
             ``IPython`` package to access all public namespaces.
             IPython notebook file icons
             ---------------------------
             The directory ``docs/resources`` in the source distribution contains SVG and
             PNG versions of our file icons, as well as an ``Info.plist.example`` file with
             instructions to install them on Mac OSX.  This is a first draft of our icons,
             and we encourage contributions from users with graphic talent to improve them
             in the future:
             .. image:: ../../resources/ipynb_icon_128x128.png
                :alt:  IPython notebook file icon.
             New top-level `locate` command
             ------------------------------
             Add `locate` entry points; these would be useful for quickly locating IPython
             directories and profiles from other (non-Python) applications. :ghpull:`1762`.
             Examples::
                 $> ipython locate
                 /Users/me/.ipython
                 $> ipython locate profile foo
                 /Users/me/.ipython/profile_foo
                 $> ipython locate profile
                 /Users/me/.ipython/profile_default
                 $> ipython locate profile dne
                 [ProfileLocate] Profile u'dne' not found.
             Other new features and improvements
             -----------------------------------
             * **%install_ext**: A new magic function to install an IPython extension from
               a URL. E.g. ``%install_ext
               https://bitbucket.org/birkenfeld/ipython-physics/raw/default/physics.py``.
             * The ``%loadpy`` magic is no longer restricted to Python files, and has been
               renamed ``%load``. The old name remains as an alias.
             * New command line arguments will help external programs find IPython folders:
               ``ipython locate`` finds the user's IPython directory, and ``ipython locate
               profile foo`` finds the folder for the 'foo' profile (if it exists).
             * The :envvar:`IPYTHON_DIR` environment variable, introduced in the Great
               Reorganization of 0.11 and existing only in versions 0.11-0.13, has been
               deprecated. As described in :ghpull:`1167`, the complexity and confusion of
               migrating to this variable is not worth the aesthetic improvement. Please use
               the historical :envvar:`IPYTHONDIR` environment variable instead.
             * The default value of *interactivity* passed from
               :meth:`~IPython.core.interactiveshell.InteractiveShell.run_cell` to
               :meth:`~IPython.core.interactiveshell.InteractiveShell.run_ast_nodes`
               is now configurable.
             * New ``%alias_magic`` function to conveniently create aliases of existing
               magics, if you prefer to have shorter names for personal use.
             * We ship unminified versions of the JavaScript libraries we use, to better
               comply with Debian's packaging policies.
             * Simplify the information presented by ``obj?/obj??`` to eliminate a few
               redundant fields when possible.  :ghpull:`2038`.
             * Improved continuous integration for IPython.  We now have automated test runs
               on `Shining Panda <https://jenkins.shiningpanda.com/ipython>`_ and `Travis-CI
               <http://travis-ci.org/#!/ipython/ipython>`_, as well as `Tox support
               <http://tox.testrun.org>`_.
             * The `vim-ipython`_ functionality (externally developed) has been updated to
               the latest version.
             .. _vim-ipython: https://github.com/ivanov/vim-ipython
             * The ``%save`` magic now has a ``-f`` flag to force overwriting, which makes
               it much more usable in the notebook where it is not possible to reply to
               interactive questions from the kernel. :ghpull:`1937`.
             * Use dvipng to format sympy.Matrix, enabling display of matrices in the Qt
               console with the sympy printing extension. :ghpull:`1861`.
             * Our messaging protocol now has a reasonable test suite, helping ensure that
               we don't accidentally deviate from the spec and possibly break third-party
               applications that may have been using it.  We encourage users to contribute
               more stringent tests to this part of the test suite.  :ghpull:`1627`.
             * Use LaTeX to display, on output, various built-in types with the SymPy
               printing extension. :ghpull:`1399`.
             * Add Gtk3 event loop integration and example. :ghpull:`1588`.
             * ``clear_output`` improvements, which allow things like progress bars and other
               simple animations to work well in the notebook (:ghpull:`1563`):
                 * `clear_output()` clears the line, even in terminal IPython, the QtConsole
                   and plain Python as well, by printing `\r` to streams.
                 * `clear_output()` avoids the flicker in the notebook by adding a delay,
                   and firing immediately upon the next actual display message.
                 * `display_javascript` hides its `output_area` element, so using display to
                   run a bunch of javascript doesn't result in ever-growing vertical space.
             * Add simple support for running inside a virtualenv.  While this doesn't
               supplant proper installation (as users should do), it helps ad-hoc calling of
               IPython from inside a virtualenv. :ghpull:`1388`.
             Major Bugs fixed
             ----------------
             In this cycle, we have :ref:`closed over 740 issues <issues_list_013>`, but a
             few major ones merit special mention:
             * The ``%pastebin`` magic has been updated to point to gist.github.com, since
               unfortunately http://paste.pocoo.org has closed down. We also added a -d flag
               for the user to provide a gist description string. :ghpull:`1670`.
             * Fix ``%paste`` that would reject certain valid inputs. :ghpull:`1258`.
             * Fix sending and receiving of Numpy structured arrays (those with composite
               dtypes, often used as recarrays). :ghpull:`2034`.
             * Reconnect when the websocket connection closes unexpectedly. :ghpull:`1577`.
             * Fix truncated representation of objects in the debugger by showing at least
 characters' worth of information.  :ghpull:`1793`.
             * Fix logger to be Unicode-aware: logging could crash ipython if there was
               unicode in the input. :ghpull:`1792`.
             * Fix images missing from XML/SVG export in the Qt console. :ghpull:`1449`.
             * Fix deepreload on Python 3. :ghpull:`1625`, as well as having a much cleaner
               and more robust implementation of deepreload in general. :ghpull:`1457`.
             Backwards incompatible changes
             ------------------------------
             * The exception :exc:`IPython.core.error.TryNext` previously accepted
               arguments and keyword arguments to be passed to the next implementation
               of the hook. This feature was removed as it made error message propagation
               difficult and violated the principle of loose coupling.

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	Site-wide shortcuts
/	Use quick search box
g h	Goto home page
g g	Goto my private gists page
g G	Goto my public gists page
g 0-9	Goto bookmarked items from 0-9
n r	New repository page
n g	New gist page

	Repositories
g s	Goto summary page
g c	Goto changelog page
g f	Goto files page
g F	Goto files page with file search activated
g p	Goto pull requests page
g o	Goto repository settings
g O	Goto repository access permissions settings
t s	Toggle sidebar on some pages