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j6k4m8/download-tweets.ipynb

Created April 22, 2021 14:20
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Download an archive of a user's tweets and render a simple HTML page (no JS required)
Display the source blob
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download-tweets.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"username = \"j6m8\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!twint -u {username} --images -o {username}_images.csv --csv"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from tqdm.auto import tqdm"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(f\"{username}_images.csv\", sep=\"\\t\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!mkdir -p images\n",
"for photorow in tqdm(df.photos):\n",
" for photo_url in eval(photorow):\n",
" fname = photo_url.split(\"/\")[-1]\n",
" !wget {photo_url} -O images/{fname}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df.columns"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def images_from_tweet(tweet):\n",
" t = \"\"\n",
" for im in eval(tweet.photos):\n",
" t += f\"<img src='images/{im.split('/')[-1]}' />\"\n",
" return t\n",
"\n",
"tweets_html = \"\\n\".join(\n",
"\n",
" f\"\"\"\n",
" <article>\n",
" <h3><a href=\"https://twitter.com/{username}/status/{tweet.id}\">@{tweet.username} on {tweet.date}</a></h3>\n",
" <p>{tweet.tweet}</p>\n",
" <div class=\"img-container\">{images_from_tweet(tweet)}</div>\n",
" </article>\n",
" \"\"\"\n",
" for i, tweet in df.iterrows()\n",
" \n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"styles = \"\"\"\n",
"\n",
"* {\n",
" box-sizing: border-box;\n",
"}\n",
"\n",
"body {\n",
" font-family: sans-serif;\n",
" background: linear-gradient(rgb(224, 231, 255), rgb(237, 233, 254));\n",
"}\n",
"\n",
".tweets {\n",
" width: 50vw;\n",
" min-width: 30em;\n",
" max-width: 100vw;\n",
" margin: auto;\n",
"}\n",
"\n",
"article {\n",
" padding: 2em;\n",
" box-shadow: rgba(0, 0, 0, 0) 0px 0px 0px 0px, rgba(0, 0, 0, 0) 0px 0px 0px 0px, rgba(0, 0, 0, 0.1) 0px 4px 6px -1px, rgba(0, 0, 0, 0.06) 0px 2px 4px -1px;\n",
" margin: 1em;\n",
" border-radius: 5px;\n",
" background: white;\n",
"}\n",
"\n",
"article .img-container {\n",
" display: grid;\n",
" flex-wrap: wrap;\n",
" justify-content: space-around;\n",
" grid-template-columns: auto auto auto;\n",
"}\n",
"\n",
"article img {\n",
" width: 95%;\n",
" margin: auto;\n",
"}\n",
"\n",
"\"\"\"\n",
"\n",
"html = f\"\"\"\n",
"\n",
"<html>\n",
"\n",
"<head>\n",
"<title>Archive: @{username}</title>\n",
"<style>{styles}</style>\n",
"</head>\n",
"\n",
"<body>\n",
"\n",
"<div class=\"tweets\">{tweets_html}</div>\n",
"\n",
"</body>\n",
"<script>\n",
"const data = {df.T.to_json()}\n",
"</script>\n",
"</html>\n",
"\n",
"\"\"\"\n",
"\n",
"with open(\"index.html\", \"w\") as fh:\n",
" fh.write(html)"
]
},
{
"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": "3.7.7"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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