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420 lines
11 KiB
Plaintext
420 lines
11 KiB
Plaintext
{
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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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"# Glossary Making Tool"
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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 Work-in-progress experiment tool to make living glossaries Webpages using simple Python, Javascript, and CSS from an markdown file written in a Etherpad instance.\n",
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"\n",
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"**What makes it living?** \n",
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"\n",
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"* The glossary structure uses the idea of 'gloss' that means annottation and layer. It makes the glossary a layering of anotations rather than a list of definitions. The pad template uses each word as a card with multiple annotations. See the example.\n",
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"\n",
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"* This tool also offers the option of add properties to each word in order to find connections and multiple types of organization. \n"
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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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"tags": []
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},
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"source": [
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"## Words\n",
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"Communicating via **API** with the glossary **Pad** and translating the text written in **Markdown** format using **Pandoc** library."
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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": 1,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json, pypandoc\n",
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"from urllib.request import urlopen\n",
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"from urllib.parse import urlencode\n",
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"\n",
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"\n",
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"with open(\"/opt/etherpad/APIKEY.txt\") as f:\n",
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" api_key = f.read().strip()\n",
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"\n",
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"api_url = \"https://hub.xpub.nl/soupboat/pad/api/1.2.15/\"\n",
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"\n",
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"# wrap in a convenient function (APICALL)\n",
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"def ep (api_fn, api_url, api_key, **data):\n",
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" data['apikey'] = api_key\n",
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" return json.load(urlopen(f\"{api_url}{api_fn}\", data=urlencode(data).encode()))\n",
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"\n",
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"\n",
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"glossary = ep(\"getText\", api_url, api_key, padID=\"camilo_glossary\")\n",
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"\n",
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"text = glossary[\"data\"][\"text\"]\n",
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"\n",
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"words = pypandoc.convert_text(text, 'html', format='md')"
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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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"From a local markdown text file"
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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": "markdown",
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"metadata": {
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"tags": []
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},
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"source": [
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"## Properties"
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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 following is a word property dictionary "
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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": 2,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"properties = [\n",
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"\t{\n",
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"\t\t'title':'action',\n",
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"\t\t'symbol':'A',\n",
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" 'color': 'green'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'situation',\n",
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"\t\t'symbol':'S',\n",
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"\t\t'color': 'aqua'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'logic',\n",
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"\t\t'symbol':'C',\n",
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"\t\t'color': 'orange'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'proposition',\n",
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"\t\t'symbol':'T',\n",
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"\t\t'color': 'blue'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'hyperlink',\n",
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"\t\t'symbol':'N',\n",
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"\t\t'color': 'pink'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'process',\n",
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"\t\t'symbol':'P',\n",
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"\t\t'color': 'gray'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'language',\n",
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"\t\t'symbol':'G',\n",
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"\t\t'color': 'violet'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'agent',\n",
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"\t\t'symbol':'E',\n",
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"\t\t'color': 'purple'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'tool',\n",
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"\t\t'symbol':'T',\n",
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"\t\t'color': 'lightblue'\n",
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"\t},\n",
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"\t{\n",
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"\t\t'title':'form',\n",
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"\t\t'symbol':'Y',\n",
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"\t\t'color': 'gold'\n",
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"\t}\n",
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"]"
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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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"## Writing the Website"
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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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"Write properties legend"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"description = ''\n",
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"\n",
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"i = 0\n",
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"\n",
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"for title, symbol, color in properties:\n",
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" title = properties[i]['title']\n",
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" description += (f''' {title}s,''')\n",
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" i += 1"
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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": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"legend = ''\n",
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"\n",
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"i = 0\n",
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"\n",
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"for title, symbol, color in properties:\n",
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" title = properties[i]['title']\n",
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" symbol = properties[i]['symbol']\n",
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" legend += f'''<button id=\"{title}\" class=\"btn {title}-s\" onclick=\"filterSelection('{title}')\">{title}→ <span class='symbol {title}-s'>{symbol}</span> </button>\\n'''\n",
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" i += 1"
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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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"Write Script that will add properties to each word"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"script = ''\n",
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"\n",
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"i = 0 \n",
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"\n",
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"for title, symbol, color in properties:\n",
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" title = properties[i]['title']\n",
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" symbol = properties[i]['symbol']\n",
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" script += (f\"\"\"const {title} = document.getElementsByClassName(\"{title}\");\n",
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" for (let i = 0; i < {title}.length; i++)\"\"\"'{\\n' \n",
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" f\"\"\"{title}[i].innerHTML += \"<span class='symbol {title}-s'>{symbol}</span>\";\"\"\" \n",
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" '\\n}\\n\\n')\n",
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" i += 1"
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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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"Assign a different color for each property "
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"style = ''\n",
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"\n",
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"i = 0 \n",
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"\n",
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"for title, symbol, color in properties:\n",
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" title = properties[i]['title']\n",
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" color = properties[i]['color']\n",
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" style += f'''.{title}-s:hover''' + '{' + f'''color:{color};''''}'\n",
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" i += 1"
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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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"tags": []
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},
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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": 7,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"body = f'''<!DOCTYPE html>\n",
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" <html>\n",
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" <head>\n",
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" <meta charset=\"utf-8\">\n",
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" <meta name=\"viewport\" content=\"width=device-width, initial-scale=1\">\n",
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" <link rel=\"stylesheet\" href=\"style.css\"> \n",
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" <title>Glossary</title>\n",
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" </head>\n",
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" <style> {style} </style>\n",
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" <body id=\"glo_body\">\n",
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" <div class=\"head\">\n",
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" <h1 id=\"title\"> Permeable Glossary for a Living Publishing Practice </h1>\n",
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" <div class=\"question\">\n",
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" <input id=\"search\" type=\"text\" ><span onclick=\"document.getElementById('search').value= ''\">X</span>\n",
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" </div>\n",
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" <a href=\"rss.xml\">\n",
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" <p>follow what is new (rss)</p>\n",
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" </a>\n",
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" </div>\n",
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" <div class='diffraction'>\n",
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" <img src='images/pattern-01.svg'>\n",
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" <img src='images/pattern-02.svg'>\n",
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" <img src='images/pattern-03.svg'>\n",
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" <img src='images/pattern-04.svg'>\n",
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" <img src='images/pattern-05.svg'>\n",
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" <img src='images/pattern-06.svg'>\n",
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" <img src='images/pattern-07.svg'>\n",
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" <img src='images/pattern-08.svg'>\n",
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" </div>\n",
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" <div class=\"description\">\n",
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" <p>From creating, designing and conceptualising to filtering, circulating and amplifying, publishing practices involve different processes and matters. Even though there are multiple theories and authors that approach each of them in a particular way, I propose to make a pause on defining them individually and focus on possible entanglements. Not to find a generalized idea of publishing but to see it as a complex and interwoven materiality. </p> \n",
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" <p>The current state of the glossary was made during different workshop sessions were practitioners are invited to question, reflect and diffract on the current publishing practice. Based on the previous state of the glossary, this sessions are called Rumination Sessions as a performance of multiple digestion. The participants added new entries, annotated on previous ones, highlighted snippets of it, bring up questions. The process aims to re-think and create collectively every word definition as a layering of annotations. Unlike traditional glossaries, in this glossary words are open to interpretation, expansion and mostly transformation. </p>\n",
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" </div>\n",
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" <div class;\n",
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" <div id=\"legend\" class=\"legend\"> \n",
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" <button class=\"btn active\" onclick=\"filterSelection('all')\">properties</button> {legend}\n",
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" </div>\n",
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" <div class=\"words\">\n",
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" {words} \n",
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" </div>\n",
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" </body>\n",
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" <script>\n",
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" {script}\n",
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" </script>\n",
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" <script src=\"main.js\"></script>\n",
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" </html>'''\n",
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"\n",
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"website = open('index.html','w')\n",
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"\n",
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"website.write(body)\n",
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"website.close()"
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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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"print(words)"
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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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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from time import sleep\n",
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"\n",
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"while True:\n",
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" print('hey')\n",
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" sleep(5)"
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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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"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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"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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