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Using Mermaid in Ipython Notebook with Presentation in NBViewer
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<!doctype html> | |
<html> | |
<head> | |
</head> | |
<body> | |
<iframe src="http://nbviewer.ipython.org/gist/bollwyvl/d5a120156216797c7132" width="600" height="800"></iframe> | |
</body> | |
</html> |
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Learn more about bidirectional Unicode characters
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 39, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"\n", | |
"<script src=\"https://cdn.rawgit.com/knsv/mermaid/bc5f73daa2769b666ccf442fa4f6d7fd4995feb0/dist/mermaid.full.js\"></script>" | |
], | |
"text/plain": [ | |
"<IPython.core.display.HTML object>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"%%html\n", | |
"<script src=\"https://cdn.rawgit.com/knsv/mermaid/bc5f73daa2769b666ccf442fa4f6d7fd4995feb0/dist/mermaid.full.js\"></script>" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# This is a Markdown Cell with some embedded [mermaid](https://github.com/knsv/mermaid)\n", | |
"\n", | |
"> Wait for the embedded mermaid...\n", | |
"\n", | |
"<div class=\"mermaid\">\n", | |
" graph LR\n", | |
" A[Square Rect] -- Link text --> B((Circle))\n", | |
" A --> C(Round Rect)\n", | |
" B --> D{Rhombus}\n", | |
" C --> D\n", | |
"</div>\n", | |
"\n", | |
"That was great!" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"This is another markdown cell.\n", | |
"<div class=\"mermaid\">\n", | |
" graph TB\n", | |
" subgraph one\n", | |
" a1-->a2\n", | |
" end\n", | |
" subgraph two\n", | |
" b1-->b2\n", | |
" end\n", | |
" subgraph three\n", | |
" c1-->c2\n", | |
" end\n", | |
" c1-->a2\n", | |
"</div>" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"This cell must be included somewhere, but the end is fine." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 42, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<script>$(function(){\n", | |
" window.mermaid && mermaid.init();\n", | |
" $(IPython.events).on(\"rendered.MarkdownCell\", function(evt, cell){\n", | |
" mermaid.init();\n", | |
" });\n", | |
"});</script>" | |
], | |
"text/plain": [ | |
"<IPython.core.display.HTML object>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"%%html\n", | |
"<script>$(function(){\n", | |
" window.mermaid && mermaid.init();\n", | |
" $(IPython.events).on(\"rendered.MarkdownCell\", function(evt, cell){\n", | |
" mermaid.init();\n", | |
" });\n", | |
"});</script>" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 2", | |
"language": "python", | |
"name": "python2" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 2 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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