Show More
@@ -1,84 +1,84 b'' | |||||
1 | """ |
|
1 | """ | |
2 | Module with tests for ansi filters |
|
2 | Module with tests for ansi filters | |
3 | """ |
|
3 | """ | |
4 |
|
4 | |||
5 | #----------------------------------------------------------------------------- |
|
5 | #----------------------------------------------------------------------------- | |
6 | # Copyright (c) 2013, the IPython Development Team. |
|
6 | # Copyright (c) 2013, the IPython Development Team. | |
7 | # |
|
7 | # | |
8 | # Distributed under the terms of the Modified BSD License. |
|
8 | # Distributed under the terms of the Modified BSD License. | |
9 | # |
|
9 | # | |
10 | # The full license is in the file COPYING.txt, distributed with this software. |
|
10 | # The full license is in the file COPYING.txt, distributed with this software. | |
11 | #----------------------------------------------------------------------------- |
|
11 | #----------------------------------------------------------------------------- | |
12 |
|
12 | |||
13 | #----------------------------------------------------------------------------- |
|
13 | #----------------------------------------------------------------------------- | |
14 | # Imports |
|
14 | # Imports | |
15 | #----------------------------------------------------------------------------- |
|
15 | #----------------------------------------------------------------------------- | |
16 |
|
16 | |||
17 | from IPython.utils.coloransi import TermColors |
|
17 | from IPython.utils.coloransi import TermColors | |
18 |
|
18 | |||
19 | from ...tests.base import TestsBase |
|
19 | from ...tests.base import TestsBase | |
20 | from ..ansi import strip_ansi, ansi2html, ansi2latex |
|
20 | from ..ansi import strip_ansi, ansi2html, ansi2latex | |
21 |
|
21 | |||
22 |
|
22 | |||
23 | #----------------------------------------------------------------------------- |
|
23 | #----------------------------------------------------------------------------- | |
24 | # Class |
|
24 | # Class | |
25 | #----------------------------------------------------------------------------- |
|
25 | #----------------------------------------------------------------------------- | |
26 |
|
26 | |||
27 | class TestAnsi(TestsBase): |
|
27 | class TestAnsi(TestsBase): | |
28 | """Contains test functions for ansi.py""" |
|
28 | """Contains test functions for ansi.py""" | |
29 |
|
29 | |||
30 | def test_strip_ansi(self): |
|
30 | def test_strip_ansi(self): | |
31 | """strip_ansi test""" |
|
31 | """strip_ansi test""" | |
32 | correct_outputs = { |
|
32 | correct_outputs = { | |
33 | '%s%s%s' % (TermColors.Green, TermColors.White, TermColors.Red) : '', |
|
33 | '%s%s%s' % (TermColors.Green, TermColors.White, TermColors.Red) : '', | |
34 | 'hello%s' % TermColors.Blue: 'hello', |
|
34 | 'hello%s' % TermColors.Blue: 'hello', | |
35 | 'he%s%sllo' % (TermColors.Yellow, TermColors.Cyan) : 'hello', |
|
35 | 'he%s%sllo' % (TermColors.Yellow, TermColors.Cyan) : 'hello', | |
36 | '%shello' % TermColors.Blue : 'hello', |
|
36 | '%shello' % TermColors.Blue : 'hello', | |
37 | '{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.Red) : 'hello', |
|
37 | '{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.Red) : 'hello', | |
38 | 'hel%slo' % TermColors.Green : 'hello', |
|
38 | 'hel%slo' % TermColors.Green : 'hello', | |
39 | 'hello' : 'hello'} |
|
39 | 'hello' : 'hello'} | |
40 |
|
40 | |||
41 | for inval, outval in correct_outputs.items(): |
|
41 | for inval, outval in correct_outputs.items(): | |
42 | self._try_strip_ansi(inval, outval) |
|
42 | self._try_strip_ansi(inval, outval) | |
43 |
|
43 | |||
44 |
|
44 | |||
45 | def _try_strip_ansi(self, inval, outval): |
|
45 | def _try_strip_ansi(self, inval, outval): | |
46 | self.assertEqual(outval, strip_ansi(inval)) |
|
46 | self.assertEqual(outval, strip_ansi(inval)) | |
47 |
|
47 | |||
48 |
|
48 | |||
49 | def test_ansi2html(self): |
|
49 | def test_ansi2html(self): | |
50 | """ansi2html test""" |
|
50 | """ansi2html test""" | |
51 | correct_outputs = { |
|
51 | correct_outputs = { | |
52 | '%s' % (TermColors.Red) : '<span class="ansired"></span>', |
|
52 | '%s' % (TermColors.Red) : '<span class="ansired"></span>', | |
53 | 'hello%s' % TermColors.Blue: 'hello<span class="ansiblue"></span>', |
|
53 | 'hello%s' % TermColors.Blue: 'hello<span class="ansiblue"></span>', | |
54 | 'he%s%sllo' % (TermColors.Green, TermColors.Cyan) : 'he<span class="ansigreen"></span><span class="ansicyan">llo</span>', |
|
54 | 'he%s%sllo' % (TermColors.Green, TermColors.Cyan) : 'he<span class="ansigreen"></span><span class="ansicyan">llo</span>', | |
55 | '%shello' % TermColors.Yellow : '<span class="ansiyellow">hello</span>', |
|
55 | '%shello' % TermColors.Yellow : '<span class="ansiyellow">hello</span>', | |
56 | '{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.White) : '<span class="ansigrey">h</span><span class="ansigrey">e</span><span class="ansigrey">l</span><span class="ansigrey">l</span><span class="ansigrey">o</span><span class="ansigrey"></span>', |
|
56 | '{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.White) : '<span class="ansigrey">h</span><span class="ansigrey">e</span><span class="ansigrey">l</span><span class="ansigrey">l</span><span class="ansigrey">o</span><span class="ansigrey"></span>', | |
57 | 'hel%slo' % TermColors.Green : 'hel<span class="ansigreen">lo</span>', |
|
57 | 'hel%slo' % TermColors.Green : 'hel<span class="ansigreen">lo</span>', | |
58 | 'hello' : 'hello'} |
|
58 | 'hello' : 'hello'} | |
59 |
|
59 | |||
60 | for inval, outval in correct_outputs.items(): |
|
60 | for inval, outval in correct_outputs.items(): | |
61 | self._try_ansi2html(inval, outval) |
|
61 | self._try_ansi2html(inval, outval) | |
62 |
|
62 | |||
63 |
|
63 | |||
64 | def _try_ansi2html(self, inval, outval): |
|
64 | def _try_ansi2html(self, inval, outval): | |
65 | self.fuzzy_compare(outval, ansi2html(inval)) |
|
65 | self.fuzzy_compare(outval, ansi2html(inval)) | |
66 |
|
66 | |||
67 |
|
67 | |||
68 | def test_ansi2latex(self): |
|
68 | def test_ansi2latex(self): | |
69 | """ansi2latex test""" |
|
69 | """ansi2latex test""" | |
70 | correct_outputs = { |
|
70 | correct_outputs = { | |
71 |
'%s' % (TermColors.Red) : r'\ |
|
71 | '%s' % (TermColors.Red) : r'{\color{red}}', | |
72 |
'hello%s' % TermColors.Blue: r'hello\ |
|
72 | 'hello%s' % TermColors.Blue: r'hello{\color{blue}}', | |
73 |
'he%s%sllo' % (TermColors.Green, TermColors.Cyan) : r'he\green{ |
|
73 | 'he%s%sllo' % (TermColors.Green, TermColors.Cyan) : r'he{\color{green}}{\color{cyan}llo}', | |
74 |
'%shello' % TermColors.Yellow : r'\yellow |
|
74 | '%shello' % TermColors.Yellow : r'{\color{yellow}hello}', | |
75 |
'{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.White) : r'\ |
|
75 | '{0}h{0}e{0}l{0}l{0}o{0}'.format(TermColors.White) : r'{\color{white}h}{\color{white}e}{\color{white}l}{\color{white}l}{\color{white}o}{\color{white}}', | |
76 |
'hel%slo' % TermColors.Green : r'hel\ |
|
76 | 'hel%slo' % TermColors.Green : r'hel{\color{green}lo}', | |
77 | 'hello' : 'hello'} |
|
77 | 'hello' : 'hello'} | |
78 |
|
78 | |||
79 | for inval, outval in correct_outputs.items(): |
|
79 | for inval, outval in correct_outputs.items(): | |
80 | self._try_ansi2latex(inval, outval) |
|
80 | self._try_ansi2latex(inval, outval) | |
81 |
|
81 | |||
82 |
|
82 | |||
83 | def _try_ansi2latex(self, inval, outval): |
|
83 | def _try_ansi2latex(self, inval, outval): | |
84 | self.fuzzy_compare(outval, ansi2latex(inval), case_sensitive=True) |
|
84 | self.fuzzy_compare(outval, ansi2latex(inval), case_sensitive=True) |
@@ -1,185 +1,188 b'' | |||||
1 | { |
|
1 | { | |
2 | "metadata": { |
|
2 | "metadata": { | |
3 |
"name": " |
|
3 | "name": "" | |
4 | }, |
|
4 | }, | |
5 | "nbformat": 3, |
|
5 | "nbformat": 3, | |
6 | "nbformat_minor": 0, |
|
6 | "nbformat_minor": 0, | |
7 | "worksheets": [ |
|
7 | "worksheets": [ | |
8 | { |
|
8 | { | |
9 | "cells": [ |
|
9 | "cells": [ | |
10 | { |
|
10 | { | |
11 | "cell_type": "heading", |
|
11 | "cell_type": "heading", | |
12 | "level": 1, |
|
12 | "level": 1, | |
13 | "metadata": {}, |
|
13 | "metadata": {}, | |
14 | "source": [ |
|
14 | "source": [ | |
15 | "NumPy and Matplotlib examples" |
|
15 | "NumPy and Matplotlib examples" | |
16 | ] |
|
16 | ] | |
17 | }, |
|
17 | }, | |
18 | { |
|
18 | { | |
19 | "cell_type": "markdown", |
|
19 | "cell_type": "markdown", | |
20 | "metadata": {}, |
|
20 | "metadata": {}, | |
21 | "source": [ |
|
21 | "source": [ | |
22 | "First import NumPy and Matplotlib:" |
|
22 | "First import NumPy and Matplotlib:" | |
23 | ] |
|
23 | ] | |
24 | }, |
|
24 | }, | |
25 | { |
|
25 | { | |
26 | "cell_type": "code", |
|
26 | "cell_type": "code", | |
27 | "collapsed": false, |
|
27 | "collapsed": false, | |
28 | "input": [ |
|
28 | "input": [ | |
29 | "%pylab inline" |
|
29 | "%pylab inline" | |
30 | ], |
|
30 | ], | |
31 | "language": "python", |
|
31 | "language": "python", | |
32 | "metadata": {}, |
|
32 | "metadata": {}, | |
33 | "outputs": [ |
|
33 | "outputs": [ | |
34 | { |
|
34 | { | |
35 | "output_type": "stream", |
|
35 | "output_type": "stream", | |
36 | "stream": "stdout", |
|
36 | "stream": "stdout", | |
37 | "text": [ |
|
37 | "text": [ | |
38 | "\n", |
|
38 | "\n", | |
39 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.kernel.zmq.pylab.backend_inline].\n", |
|
39 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.kernel.zmq.pylab.backend_inline].\n", | |
40 | "For more information, type 'help(pylab)'.\n" |
|
40 | "For more information, type 'help(pylab)'.\n" | |
41 | ] |
|
41 | ] | |
42 | } |
|
42 | } | |
43 | ], |
|
43 | ], | |
44 | "prompt_number": 1 |
|
44 | "prompt_number": 1 | |
45 | }, |
|
45 | }, | |
46 | { |
|
46 | { | |
47 | "cell_type": "code", |
|
47 | "cell_type": "code", | |
48 | "collapsed": false, |
|
48 | "collapsed": false, | |
49 | "input": [ |
|
49 | "input": [ | |
50 | "import numpy as np" |
|
50 | "import numpy as np" | |
51 | ], |
|
51 | ], | |
52 | "language": "python", |
|
52 | "language": "python", | |
53 | "metadata": {}, |
|
53 | "metadata": {}, | |
54 | "outputs": [], |
|
54 | "outputs": [], | |
55 | "prompt_number": 2 |
|
55 | "prompt_number": 2 | |
56 | }, |
|
56 | }, | |
57 | { |
|
57 | { | |
58 | "cell_type": "markdown", |
|
58 | "cell_type": "markdown", | |
59 | "metadata": {}, |
|
59 | "metadata": {}, | |
60 | "source": [ |
|
60 | "source": [ | |
61 | "Now we show some very basic examples of how they can be used." |
|
61 | "Now we show some very basic examples of how they can be used." | |
62 | ] |
|
62 | ] | |
63 | }, |
|
63 | }, | |
64 | { |
|
64 | { | |
65 | "cell_type": "code", |
|
65 | "cell_type": "code", | |
66 | "collapsed": false, |
|
66 | "collapsed": false, | |
67 | "input": [ |
|
67 | "input": [ | |
68 | "a = np.random.uniform(size=(100,100))" |
|
68 | "a = np.random.uniform(size=(100,100))" | |
69 | ], |
|
69 | ], | |
70 | "language": "python", |
|
70 | "language": "python", | |
71 | "metadata": {}, |
|
71 | "metadata": {}, | |
72 | "outputs": [], |
|
72 | "outputs": [], | |
73 | "prompt_number": 6 |
|
73 | "prompt_number": 6 | |
74 | }, |
|
74 | }, | |
75 | { |
|
75 | { | |
76 | "cell_type": "code", |
|
76 | "cell_type": "code", | |
77 | "collapsed": false, |
|
77 | "collapsed": false, | |
78 | "input": [ |
|
78 | "input": [ | |
79 | "a.shape" |
|
79 | "a.shape" | |
80 | ], |
|
80 | ], | |
81 | "language": "python", |
|
81 | "language": "python", | |
82 | "metadata": {}, |
|
82 | "metadata": {}, | |
83 | "outputs": [ |
|
83 | "outputs": [ | |
84 | { |
|
84 | { | |
85 | "metadata": {}, |
|
85 | "metadata": {}, | |
86 | "output_type": "pyout", |
|
86 | "output_type": "pyout", | |
87 | "prompt_number": 7, |
|
87 | "prompt_number": 7, | |
88 | "text": [ |
|
88 | "text": [ | |
89 | "(100, 100)" |
|
89 | "(100, 100)" | |
90 | ] |
|
90 | ] | |
91 | } |
|
91 | } | |
92 | ], |
|
92 | ], | |
93 | "prompt_number": 7 |
|
93 | "prompt_number": 7 | |
94 | }, |
|
94 | }, | |
95 | { |
|
95 | { | |
96 | "cell_type": "code", |
|
96 | "cell_type": "code", | |
97 | "collapsed": false, |
|
97 | "collapsed": false, | |
98 | "input": [ |
|
98 | "input": [ | |
99 | "evs = np.linalg.eigvals(a)" |
|
99 | "evs = np.linalg.eigvals(a)" | |
100 | ], |
|
100 | ], | |
101 | "language": "python", |
|
101 | "language": "python", | |
102 | "metadata": {}, |
|
102 | "metadata": {}, | |
103 | "outputs": [], |
|
103 | "outputs": [], | |
104 | "prompt_number": 8 |
|
104 | "prompt_number": 8 | |
105 | }, |
|
105 | }, | |
106 | { |
|
106 | { | |
107 | "cell_type": "code", |
|
107 | "cell_type": "code", | |
108 | "collapsed": false, |
|
108 | "collapsed": false, | |
109 | "input": [ |
|
109 | "input": [ | |
110 | "evs.shape" |
|
110 | "evs.shape" | |
111 | ], |
|
111 | ], | |
112 | "language": "python", |
|
112 | "language": "python", | |
113 | "metadata": {}, |
|
113 | "metadata": {}, | |
114 | "outputs": [ |
|
114 | "outputs": [ | |
115 | { |
|
115 | { | |
116 | "metadata": {}, |
|
116 | "metadata": {}, | |
117 | "output_type": "pyout", |
|
117 | "output_type": "pyout", | |
118 | "prompt_number": 10, |
|
118 | "prompt_number": 10, | |
119 | "text": [ |
|
119 | "text": [ | |
120 | "(100,)" |
|
120 | "(100,)" | |
121 | ] |
|
121 | ] | |
122 | } |
|
122 | } | |
123 | ], |
|
123 | ], | |
124 | "prompt_number": 10 |
|
124 | "prompt_number": 10 | |
125 | }, |
|
125 | }, | |
126 | { |
|
126 | { | |
127 | "cell_type": "heading", |
|
127 | "cell_type": "heading", | |
128 | "level": 2, |
|
128 | "level": 2, | |
129 | "metadata": {}, |
|
129 | "metadata": {}, | |
130 | "source": [ |
|
130 | "source": [ | |
131 | "Here is a very long heading that pandoc will wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap" |
|
131 | "Here is a very long heading that pandoc will wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap" | |
132 | ] |
|
132 | ] | |
133 | }, |
|
133 | }, | |
134 | { |
|
134 | { | |
135 | "cell_type": "markdown", |
|
135 | "cell_type": "markdown", | |
136 | "metadata": {}, |
|
136 | "metadata": {}, | |
137 | "source": [ |
|
137 | "source": [ | |
138 | "Here is a cell that has both text and PNG output:" |
|
138 | "Here is a cell that has both text and PNG output:" | |
139 | ] |
|
139 | ] | |
140 | }, |
|
140 | }, | |
141 | { |
|
141 | { | |
142 | "cell_type": "code", |
|
142 | "cell_type": "code", | |
143 | "collapsed": false, |
|
143 | "collapsed": false, | |
144 | "input": [ |
|
144 | "input": [ | |
145 | "hist(evs.real)" |
|
145 | "hist(evs.real)" | |
146 | ], |
|
146 | ], | |
147 | "language": "python", |
|
147 | "language": "python", | |
148 | "metadata": {}, |
|
148 | "metadata": {}, | |
149 | "outputs": [ |
|
149 | "outputs": [ | |
150 | { |
|
150 | { | |
151 | "metadata": {}, |
|
151 | "metadata": {}, | |
152 | "output_type": "pyout", |
|
152 | "output_type": "pyout", | |
153 | "prompt_number": 14, |
|
153 | "prompt_number": 14, | |
154 | "text": [ |
|
154 | "text": [ | |
155 | "(array([95, 4, 0, 0, 0, 0, 0, 0, 0, 1]),\n", |
|
155 | "(array([95, 4, 0, 0, 0, 0, 0, 0, 0, 1]),\n", | |
156 | " array([ -2.93566063, 2.35937011, 7.65440086, 12.9494316 ,\n", |
|
156 | " array([ -2.93566063, 2.35937011, 7.65440086, 12.9494316 ,\n", | |
157 | " 18.24446235, 23.53949309, 28.83452384, 34.12955458,\n", |
|
157 | " 18.24446235, 23.53949309, 28.83452384, 34.12955458,\n", | |
158 | " 39.42458533, 44.71961607, 50.01464682]),\n", |
|
158 | " 39.42458533, 44.71961607, 50.01464682]),\n", | |
159 | " <a list of 10 Patch objects>)" |
|
159 | " <a list of 10 Patch objects>)" | |
160 | ] |
|
160 | ] | |
161 | }, |
|
161 | }, | |
162 | { |
|
162 | { | |
163 | "metadata": {}, |
|
163 | "metadata": {}, | |
164 | "output_type": "display_data", |
|
164 | "output_type": "display_data", | |
165 | "png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD9CAYAAAC2l2x5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", |
|
165 | "png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD9CAYAAAC2l2x5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAEhdJREFUeJzt3X1olfX/x/HXtVbT8CZDmsK6KmrubEu3U2xnZOpxLBnG\nOqsIE7RoE3QRZkT/yEAjcIh/LIs6i/BEGSU1CkxT0+pkFp1zMmsxZ5uUTIXoxm95lmdlef3+8Nep\ndbtz7exs16fnAw7sXNs5n/c14nmurl3naDmO4wgAYJy8sR4AADA6CDwAGIrAA4ChCDwAGIrAA4Ch\nCDwAGOofA9/U1KTCwkLNnj07vS2ZTCoUCsm2bTU2NmpgYCD9vccee0zFxcUqKyvTgQMHRm9qAMC/\n+sfA33PPPdq9e/eQbeFwWLZtq6+vT0VFRero6JAkffXVV3ryySf15ptvKhwOa/Xq1aM3NQDgX/1j\n4OfNm6dp06YN2RaPx9Xc3KyCggI1NTUpFotJkmKxmOrr62XbthYsWCDHcZRMJkdvcgDAP8r4HHwi\nkZDP55Mk+Xw+xeNxSecDX1pamv65kpKS9PcAALmXn+kDMvlkA8uyhrUNAPDvMv1kmYyP4KuqqtTT\n0yNJ6unpUVVVlSQpEAjo8OHD6Z87cuRI+nt/NaRXb+vWrRvzGZh/7Odgfu/dvDy747j7yLCMAx8I\nBBSJRJRKpRSJRFRTUyNJqq6u1p49e9Tf369oNKq8vDxNnjzZ1VAAgJH7x8AvXbpUN9xwg3p7e3X5\n5ZfrmWeeUUtLi/r7+1VSUqKTJ09q1apVkqTCwkK1tLSotrZW9957rzZv3pyTHQAA/DXLcXvs73ZB\ny3L9vxvjQTQaVTAYHOsxXGP+scX8Y8fLs0vu2kngAcAD3LSTjyoAAEMReAAwFIEHAEMReAAwFIEH\nAEP9ZwM/Zcqlsixr1G9Tplw61rsK4D/qP3uZ5PnPxMnFHONjfwF4G5dJAgDSCDwAGIrAA4ChCDwA\nGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrA\nA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChXAf+6aef1g03\n3KDrr79ea9askSQlk0mFQiHZtq3GxkYNDAxkbVAAQGZcBf7UqVPasGGD9u7dq0Qiod7eXu3Zs0fh\ncFi2bauvr09FRUXq6OjI9rwAgGFyFfiJEyfKcRx9//33SqVSOnPmjC655BLF43E1NzeroKBATU1N\nisVi2Z4XADBMrgMfDod15ZVXasaMGZo7d64CgYASiYR8Pp8kyefzKR6PZ3VYAMDw5bt50Ndff62W\nlhYdPnxY06ZN0x133KEdO3bIcZxhPX79+vXpr4PBoILBoJsxAMBY0WhU0Wh0RM9hOcOt8u/s3LlT\nW7du1bZt2yRJ4XBYx44d09GjR9Xa2iq/36+DBw+qra1NnZ2dQxe0rGG/EIwmy7Ik5WKO8bG/ALzN\nTTtdnaKZN2+ePvzwQ506dUo//vijdu3apUWLFikQCCgSiSiVSikSiaimpsbN0wMAssBV4KdMmaLW\n1lbdeuutuvHGG1VRUaGFCxeqpaVF/f39Kikp0cmTJ7Vq1apszwsAGCZXp2hGtCCnaAAgYzk7RQMA\nGP8IPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEI\nPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAY\nisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYisADgKEIPAAYynXgf/jhB919992a\nNWuWysrKFIvFlEwmFQqFZNu2GhsbNTAwkM1ZAQAZcB34devWybZtdXV1qaurSz6fT+FwWLZtq6+v\nT0VFRero6MjmrACADLgO/L59+7R27VpNmDBB+fn5mjp1quLxuJqbm1VQUKCmpibFYrFszgoAyICr\nwJ84cUKDg4NqaWlRIBDQxo0blUqllEgk5PP5JEk+n0/xeDyrwwIAhi/fzYMGBwfV29urTZs2qa6u\nTitXrtRLL70kx3GG9fj169envw4GgwoGg27GAABjRaNRRaPRET2H5Qy3yn9QWlqqnp4eSdKuXbv0\n3HPP6aefflJra6v8fr8OHjyotrY2dXZ2Dl3Qsob9QjCaLMuSlIs5xsf+AvA2N+10fQ6+uLhYsVhM\n586d086dO1VXV6dAIKBIJKJUKqVIJKKamhq3Tw8AGCHXR/C9vb266667NDg4qLq6Oj388MM6d+6c\nli1bpkOHDum6667T888/r0mTJg1dkCN4AMiYm3a6DrxbBB4AMpfTUzQAgPGNwAOAoQg8ABiKwAOA\noQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8\nABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiK\nwAOAoQg8ABiKwAOAoQg8ABiKwAOAoQg8ABiKwAOAoVwH/pdffpHf71dDQ4MkKZlMKhQKybZtNTY2\namBgIGtDAgAy5zrwmzdvVllZmSzLkiSFw2HZtq2+vj4VFRWpo6Mja0MCADLnKvAnTpzQ66+/rhUr\nVshxHElSPB5Xc3OzCgoK1NTUpFgsltVBAQCZcRX4Bx54QJs2bVJe3m8PTyQS8vl8kiSfz6d4PJ6d\nCQEAruRn+oAdO3bosssuk9/vVzQaTW//9Uh+ONavX5/+OhgMKhgMZjoGABgtGo0OaawblpNJmSWt\nXbtWW7duVX5+vgYHB3X69GnddtttOnPmjFpbW+X3+3Xw4EG1tbWps7PzzwtaVkYvBqPl/N8OcjHH\n+NhfAN7mpp0Zn6LZsGGDjh8/ri+++ELbtm1TbW2ttm7dqkAgoEgkolQqpUgkopqamkyfGgCQRSO+\nDv7Xq2haWlrU39+vkpISnTx5UqtWrRrxcAAA9zI+RTPiBTlFAwAZy8kpGgCANxB4ADAUgQcAQxF4\nADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAU\ngQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcA\nQxF4ADAUgQcAQxF4ADAUgQcAQxF4ADAUgQcAQ7kK/PHjx7Vw4UKVl5crGAzqhRdekCQlk0mFQiHZ\ntq3GxkYNDAxkdVgAwPC5CvyFF16o9vZ2dXd3q7OzU62trUomkwqHw7JtW319fSoqKlJHR0e25wUA\nDJOrwM+YMUOVlZWSpOnTp6u8vFyJRELxeFzNzc0qKChQU1OTYrFYVocFAAzfiM/BHz16VN3d3aqu\nrlYikZDP55Mk+Xw+xePxEQ8IAHAnfyQPTiaTWrJkidrb2zVp0iQ5jjOsx61fvz79dTAYVDAYHMkY\nAGCcaDSqaDQ6ouewnOFW+Q/Onj2rm2++WYsXL9aaNWskSbfffrtaW1vl9/t18OBBtbW1qbOzc+iC\nljXsF4LRZFmWpFzMMT72F4C3uWmnq1M0juOoublZ1157bTrukhQIBBSJRJRKpRSJRFRTU+Pm6QEA\nWeDqCP7AgQOaP3++5syZ8/9HwlJbW5vmzp2rZcuW6dChQ7ruuuv0/PPPa9KkSUMX5AgeADLmpp2u\nT9G4ReABIHM5O0UDABj/CDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrA\nA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4Ch\nCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4ChCDwAGIrAA4Ch8sd6APPly7KsUV1h8uRpOn361Kiu\nAcB7LMdxnJwuaFnK8ZJ/O4eUizlysc74+J0CGD1u2skpGgAwFIEHAEMReAAwVNYDv3//fpWWlqq4\nuFiPP/54tp9+HIiO9QAjEo1Gx3qEEWH+seXl+b08u1tZD/z999+vp556Svv27dMTTzyhb775JttL\njLHoWA8wIl7/j5z5x5aX5/fy7G5lNfDff/+9JGn+/Pm64oortGjRIsVisWwuAcBAU6ZcKsuyRvXW\n1rZxrHcz57Ia+EQiIZ/Pl75fVlamDz74IJtLADBQMvk/nb+cePRuP/00mLsdGieyeh38vn37tGXL\nFr344ouSpI6ODp08eVKPPPLIbwuO8pt+AMBUmeY6q+9kraqq0kMPPZS+393drfr6+iE/wxtyACA3\nsnqKZurUqZLOX0lz7Ngx7d27V4FAIJtLAACGKeufRfPoo49q5cqVOnv2rFavXq3p06dnewkAwDBk\n/TLJBQsWqKenR0ePHtXq1aslSS+//LLKy8t1wQUX6KOPPhry84899piKi4tVVlamAwcOZHucrPHa\n9f1NTU0qLCzU7Nmz09uSyaRCoZBs21ZjY6MGBgbGcMJ/dvz4cS1cuFDl5eUKBoN64YUXJHlnHwYH\nBxUIBFRZWamamhq1t7dL8s78kvTLL7/I7/eroaFBkrdmv/LKKzVnzhz5/X5VV1dL8tb8P/zwg+6+\n+27NmjVLZWVlisVirubPyTtZZ8+erVdffVXz588fsv2rr77Sk08+qTfffFPhcDj9gjAeee36/nvu\nuUe7d+8esi0cDsu2bfX19amoqEgdHR1jNN2/u/DCC9Xe3q7u7m51dnaqtbVVyWTSM/swYcIEvf32\n2/r444/1zjvvaMuWLerr6/PM/JK0efNmlZWVpS+M8NLslmUpGo3q0KFDisfjkrw1/7p162Tbtrq6\nutTV1SWfz+dq/pwE3ufzadasWX/aHovFVF9fL9u2tWDBAjmOo2QymYuRMuLF6/vnzZunadOmDdkW\nj8fV3NysgoICNTU1jet9mDFjhiorKyVJ06dPV3l5uRKJhKf24eKLL5YkDQwM6Oeff1ZBQYFn5j9x\n4oRef/11rVixIn1hhFdm/9UfL+jw0vz79u3T2rVrNWHCBOXn52vq1Kmu5h/Tz6KJx+MqLS1N3y8p\nKUm/2o4nplzf//v98Pl84/J3/VeOHj2q7u5uVVdXe2ofzp07p4qKChUWFuq+++6Tbduemf+BBx7Q\npk2blJf3WyK8Mrt0/gi+trZWjY2N2r59uyTvzH/ixAkNDg6qpaVFgUBAGzduVCqVcjV/1v7IetNN\nN+nLL7/80/YNGzakz+H90V9dMsl18qPHi5eoJpNJLVmyRO3t7Zo0aZKn9iEvL0+ffPKJjh07psWL\nF2vu3LmemH/Hjh267LLL5Pf7h7y93wuz/+q9997TzJkz1dPTo4aGBlVXV3tm/sHBQfX29mrTpk2q\nq6vTypUr9dJLL7maP2tH8Hv37tWnn376p9vfxV2SAoGADh8+nL5/5MgRVVVVZWukrKmqqtKRI0fS\n97u7u1VTUzOGE7lTVVWlnp4eSVJPT8+4/F3/3tmzZ3X77bdr+fLlCoVCkry3D9L5P/gtXrxYsVjM\nE/O///772r59u6666iotXbpUb731lpYvX+6J2X81c+ZMSVJpaaluueUWvfbaa56Z/5prrlFJSYka\nGho0ceJELV26VLt373Y1f85P0fz+Vai6ulp79uxRf3+/otGo8vLyNHny5FyP9K9Mub4/EAgoEoko\nlUopEomM6xcpx3HU3Nysa6+9VmvWrElv98o+fPPNN/ruu+8kSd9++63eeOMNhUIhT8y/YcMGHT9+\nXF988YW2bdum2tpabd261ROzS9KZM2fSf8v7+uuvtWfPHtXX13tmfkkqLi5WLBbTuXPntHPnTtXV\n1bmb38mBV155xSkqKnImTJjgFBYWOvX19envPfroo87VV1/tlJaWOvv378/FOK5Eo1HH5/M5V199\ntbN58+axHudf3Xnnnc7MmTOdiy66yCkqKnIikYhz+vRp55ZbbnEuv/xyJxQKOclkcqzH/Fvvvvuu\nY1mWU1FR4VRWVjqVlZXOrl27PLMPXV1djt/vd+bMmeMsWrTIefbZZx3HcTwz/6+i0ajT0NDgOI53\nZv/888+diooKp6KiwqmtrXW2bNniOI535nccx/nss8+cQCDgVFRUOA8++KAzMDDgav6c/5usAIDc\n4F90AgBDEXgAMBSBBwBDEXgAMBSBBwBDEXgAMNT/AQKseNIf7mhWAAAAAElFTkSuQmCC\n", | |
166 | "text": [ |
|
166 | "text": [ | |
167 | "<matplotlib.figure.Figure at 0x108c8f1d0>" |
|
167 | "<matplotlib.figure.Figure at 0x108c8f1d0>" | |
168 | ] |
|
168 | ] | |
169 | } |
|
169 | } | |
170 | ], |
|
170 | ], | |
171 | "prompt_number": 14 |
|
171 | "prompt_number": 14 | |
172 | }, |
|
172 | }, | |
173 | { |
|
173 | { | |
174 |
"cell_type": " |
|
174 | "cell_type": "markdown", | |
175 | "collapsed": false, |
|
|||
176 | "input": [], |
|
|||
177 | "language": "python", |
|
|||
178 | "metadata": {}, |
|
175 | "metadata": {}, | |
179 |
" |
|
176 | "source": [ | |
|
177 | "```python\n", | |||
|
178 | "def foo(bar=1):\n", | |||
|
179 | " \"\"\"docstring\"\"\"\n", | |||
|
180 | " raise Exception(\"message\")\n", | |||
|
181 | "```" | |||
|
182 | ] | |||
180 | } |
|
183 | } | |
181 | ], |
|
184 | ], | |
182 | "metadata": {} |
|
185 | "metadata": {} | |
183 | } |
|
186 | } | |
184 | ] |
|
187 | ] | |
185 | } No newline at end of file |
|
188 | } |
General Comments 0
You need to be logged in to leave comments.
Login now