##// END OF EJS Templates
add test notebook for confined output
Min RK -
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@@ -0,0 +1,273 b''
1 {
2 "cells": [
3 {
4 "cell_type": "markdown",
5 "metadata": {},
6 "source": [
7 "# Test notebook for overflowing content"
8 ]
9 },
10 {
11 "cell_type": "markdown",
12 "metadata": {},
13 "source": [
14 "markdown image:\n",
15 "\n",
16 "<img src=\"http://placehold.it/800x200.png\">\n",
17 "\n",
18 "unconfined markdown image:\n",
19 "\n",
20 "<img src=\"http://placehold.it/800x200.png\" class=\"unconfined\">"
21 ]
22 },
23 {
24 "cell_type": "code",
25 "execution_count": 13,
26 "metadata": {
27 "collapsed": true
28 },
29 "outputs": [],
30 "source": [
31 "from IPython.display import Image, IFrame"
32 ]
33 },
34 {
35 "cell_type": "markdown",
36 "metadata": {},
37 "source": [
38 "Overflow image in HTML (non-embedded)"
39 ]
40 },
41 {
42 "cell_type": "code",
43 "execution_count": 22,
44 "metadata": {
45 "collapsed": false
46 },
47 "outputs": [
48 {
49 "data": {
50 "text/html": [
51 "<img src=\"http://placehold.it/800x200.png\"/>"
52 ],
53 "text/plain": [
54 "<IPython.core.display.Image object>"
55 ]
56 },
57 "execution_count": 22,
58 "metadata": {},
59 "output_type": "execute_result"
60 }
61 ],
62 "source": [
63 "Image(url=\"http://placehold.it/800x200.png\", embed=False)"
64 ]
65 },
66 {
67 "cell_type": "markdown",
68 "metadata": {},
69 "source": [
70 "Overflow image:"
71 ]
72 },
73 {
74 "cell_type": "code",
75 "execution_count": 4,
76 "metadata": {
77 "collapsed": false
78 },
79 "outputs": [
80 {
81 "data": {
82 "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAADIBAMAAADioZgpAAAAG1BMVEXMzMyWlpbFxcWxsbGjo6Oc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\nLzkAAAAASUVORK5CYII=\n",
83 "text/plain": [
84 "<IPython.core.display.Image object>"
85 ]
86 },
87 "execution_count": 4,
88 "metadata": {},
89 "output_type": "execute_result"
90 }
91 ],
92 "source": [
93 "Image(url=\"http://placehold.it/800x200.png\", embed=True)"
94 ]
95 },
96 {
97 "cell_type": "markdown",
98 "metadata": {},
99 "source": [
100 "Overflow with explicit height, width (retina):"
101 ]
102 },
103 {
104 "cell_type": "code",
105 "execution_count": 23,
106 "metadata": {
107 "collapsed": false
108 },
109 "outputs": [
110 {
111 "data": {
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113 "text/plain": [
114 "<IPython.core.display.Image object>"
115 ]
116 },
117 "execution_count": 23,
118 "metadata": {
119 "image/jpeg": {
120 "height": 100,
121 "width": 900
122 }
123 },
124 "output_type": "execute_result"
125 }
126 ],
127 "source": [
128 "Image(url=\"http://placehold.it/1800x200.jpg\", embed=True, retina=True)"
129 ]
130 },
131 {
132 "cell_type": "markdown",
133 "metadata": {},
134 "source": [
135 "Overflowing IFrame:"
136 ]
137 },
138 {
139 "cell_type": "code",
140 "execution_count": 27,
141 "metadata": {
142 "collapsed": false
143 },
144 "outputs": [
145 {
146 "data": {
147 "text/html": [
148 "\n",
149 " <iframe\n",
150 " width=\"900\"\n",
151 " height=\"400\"\n",
152 " src=\"http://ipython.org\"\n",
153 " frameborder=\"0\"\n",
154 " allowfullscreen\n",
155 " ></iframe>\n",
156 " "
157 ],
158 "text/plain": [
159 "<IPython.lib.display.IFrame at 0x108cdbe48>"
160 ]
161 },
162 "execution_count": 27,
163 "metadata": {},
164 "output_type": "execute_result"
165 }
166 ],
167 "source": [
168 "IFrame(src=\"http://ipython.org\", width=900, height=400)"
169 ]
170 },
171 {
172 "cell_type": "markdown",
173 "metadata": {},
174 "source": [
175 "Overflowing table:"
176 ]
177 },
178 {
179 "cell_type": "code",
180 "execution_count": 21,
181 "metadata": {
182 "collapsed": false
183 },
184 "outputs": [
185 {
186 "data": {
187 "text/html": [
188 "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
189 "<table border=\"1\" class=\"dataframe\">\n",
190 " <thead>\n",
191 " <tr style=\"text-align: right;\">\n",
192 " <th></th>\n",
193 " <th>0</th>\n",
194 " <th>1</th>\n",
195 " <th>2</th>\n",
196 " <th>3</th>\n",
197 " <th>4</th>\n",
198 " <th>5</th>\n",
199 " <th>6</th>\n",
200 " <th>7</th>\n",
201 " <th>8</th>\n",
202 " <th>9</th>\n",
203 " <th>10</th>\n",
204 " <th>11</th>\n",
205 " <th>12</th>\n",
206 " <th>13</th>\n",
207 " <th>14</th>\n",
208 " </tr>\n",
209 " </thead>\n",
210 " <tbody>\n",
211 " <tr>\n",
212 " <th>0</th>\n",
213 " <td> column</td>\n",
214 " <td> column</td>\n",
215 " <td> column</td>\n",
216 " <td> column</td>\n",
217 " <td> column</td>\n",
218 " <td> column</td>\n",
219 " <td> column</td>\n",
220 " <td> column</td>\n",
221 " <td> column</td>\n",
222 " <td> column</td>\n",
223 " <td> column</td>\n",
224 " <td> column</td>\n",
225 " <td> column</td>\n",
226 " <td> column</td>\n",
227 " <td> column</td>\n",
228 " </tr>\n",
229 " </tbody>\n",
230 "</table>\n",
231 "</div>"
232 ],
233 "text/plain": [
234 " 0 1 2 3 4 5 6 7 8 \\\n",
235 "0 column column column column column column column column column \n",
236 "\n",
237 " 9 10 11 12 13 14 \n",
238 "0 column column column column column column "
239 ]
240 },
241 "execution_count": 21,
242 "metadata": {},
243 "output_type": "execute_result"
244 }
245 ],
246 "source": [
247 "import pandas as pd\n",
248 "pd.DataFrame([['column'] * 15])"
249 ]
250 }
251 ],
252 "metadata": {
253 "kernelspec": {
254 "display_name": "Python 3",
255 "language": "python",
256 "name": "python3"
257 },
258 "language_info": {
259 "codemirror_mode": {
260 "name": "ipython",
261 "version": 3
262 },
263 "file_extension": ".py",
264 "mimetype": "text/x-python",
265 "name": "python",
266 "nbconvert_exporter": "python",
267 "pygments_lexer": "ipython3",
268 "version": "3.4.3"
269 }
270 },
271 "nbformat": 4,
272 "nbformat_minor": 0
273 }
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