more collected notebooks
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Ursula Franklin"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"![](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",
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"\n",
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"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",
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"\n",
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"<https://archive.org/details/the-real-world-of-technology>\n",
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"\n",
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"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",
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"\n",
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"<https://archive.org/details/the-real-world-of-technology&output=json"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 46,
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"metadata": {},
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"outputs": [],
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"source": [
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"identifier = \"the-real-world-of-technology\"\n",
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"url = f\"https://archive.org/details/{identifier}\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from urllib.request import urlopen\n",
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"import json"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"f = urlopen(url+\"&output=json\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"feed = json.load(f)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"feed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"len(feed['files'])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"According to the [Archive.org API](https://archive.org/services/docs/api/items.html#archival-urls):\n",
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"\n",
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"> A particular file can always be downloaded from:\n",
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">```\n",
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"> https://archive.org/download/<identifier>/<filename>\n",
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">```"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# this is something specific to notebooks...\n",
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"from IPython.display import HTML, display"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"for filename, d in feed['files'].items():\n",
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" if d['format'] == \"VBR MP3\":\n",
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" display(HTML(f'<h2>{d[\"title\"]}</h2>'))\n",
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" display(HTML(f'<audio src=\"https://archive.org/download/{identifier}{filename}\" controls></audio>'))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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@ -0,0 +1,81 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# CSS Test"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<div style=\"background-color:pink;padding:2em;color:red;\">Welcome :)</div>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<style>body{background-color:yellow;}</style>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"(above there is a \"hidden cell\", with a small CSS test)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"*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>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Notes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Curious to try to understand what \"jupyter-themer\" is? How could styling become part of the workflow?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"And.... \"jupyter-book\""
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Notes in a Network"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This is a notebook. A notebook is a sort of \"active document\" that allows you to combine *text* and *executable code*. "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"words = ['notes', 'in', 'a', 'network']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"notes\n",
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"notes\n",
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"notes\n",
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"notes\n",
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"notes\n",
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"in\n",
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"in\n",
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"a\n",
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"network\n",
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"network\n",
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"network\n",
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"network\n",
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"network\n",
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"network\n",
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"network\n"
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]
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}
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],
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"source": [
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"for word in words:\n",
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" for letter in word:\n",
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" print(word)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Python"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The programming language that we will use is *Python*. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"la\n",
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"lala\n",
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"lalala\n",
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"lalalala\n",
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"lalalalala\n",
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"lalalalalala\n",
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"lalalalalalala\n",
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"lalalalalalalala\n",
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"lalalalalalalalala\n"
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]
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}
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],
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"source": [
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"for i in range(10):\n",
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" print(i * 'la')\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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