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2020-prototyping-notebooks
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Michael Murtaugh 4 years ago
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commit 99ffedeed9
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137
UrsulaFranklin.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Ursula Franklin"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![](https://upload.wikimedia.org/wikipedia/commons/thumb/3/32/Ursula_Franklin_at_book_launch_crop.jpg/220px-Ursula_Franklin_at_book_launch_crop.jpg)\n",
"\n",
"You can find the recordings of her Massey lectures on [archive.org](https://archive.org/details/the-real-world-of-technology). Note the URL: \n",
"\n",
"<https://archive.org/details/the-real-world-of-technology>\n",
"\n",
"You can also access the API of archive.org to get information in a [structured format](https://archive.org/help/json.php) that you can use in a script...\n",
"\n",
"<https://archive.org/details/the-real-world-of-technology&output=json"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"identifier = \"the-real-world-of-technology\"\n",
"url = f\"https://archive.org/details/{identifier}\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from urllib.request import urlopen\n",
"import json"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"f = urlopen(url+\"&output=json\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"feed = json.load(f)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"feed"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"len(feed['files'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"According to the [Archive.org API](https://archive.org/services/docs/api/items.html#archival-urls):\n",
"\n",
"> A particular file can always be downloaded from:\n",
">```\n",
"> https://archive.org/download/<identifier>/<filename>\n",
">```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# this is something specific to notebooks...\n",
"from IPython.display import HTML, display"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for filename, d in feed['files'].items():\n",
" if d['format'] == \"VBR MP3\":\n",
" display(HTML(f'<h2>{d[\"title\"]}</h2>'))\n",
" display(HTML(f'<audio src=\"https://archive.org/download/{identifier}{filename}\" controls></audio>'))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

81
css-tests.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# CSS Test"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div style=\"background-color:pink;padding:2em;color:red;\">Welcome :)</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<style>body{background-color:yellow;}</style>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"(above there is a \"hidden cell\", with a small CSS test)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Thinking out loud*: <div style=\"color:magenta;font-size:2em;line-height:1.4;\">If notebooks will be used as a <u>format</u> to publish through ... (next to the all the \"spatial\" layout experiments we will do), then *what* we publish is not only output, but also processes and tools (\"generators\": scripts and code, that produce structurations, systematics, etc!).</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Notes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Curious to try to understand what \"jupyter-themer\" is? How could styling become part of the workflow?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And.... \"jupyter-book\""
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

19633
etherpad_changesets.ipynb
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143
notes-in-a-network.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Notes in a Network"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is a notebook. A notebook is a sort of \"active document\" that allows you to combine *text* and *executable code*. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These notebooks are a starting point to approach re-publishing as a *practice*. A multi-dimensional attitude and methodology, which includes not only outputs but also sources, tools, process logs and more!"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"words = ['notes', 'in', 'a', 'network']"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"notes\n",
"notes\n",
"notes\n",
"notes\n",
"notes\n",
"in\n",
"in\n",
"a\n",
"network\n",
"network\n",
"network\n",
"network\n",
"network\n",
"network\n",
"network\n"
]
}
],
"source": [
"for word in words:\n",
" for letter in word:\n",
" print(word)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The programming language that we will use is *Python*. "
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"la\n",
"lala\n",
"lalala\n",
"lalalala\n",
"lalalalala\n",
"lalalalalala\n",
"lalalalalalala\n",
"lalalalalalalala\n",
"lalalalalalalalala\n"
]
}
],
"source": [
"for i in range(10):\n",
" print(i * 'la')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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