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207 lines
202 KiB
Plaintext
207 lines
202 KiB
Plaintext
2 years ago
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9c82a9be",
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"metadata": {},
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"source": [
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"# 冷笑话若干"
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]
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},
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{
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"cell_type": "markdown",
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"id": "950bdcc2",
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"metadata": {},
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"source": [
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"第一则：橘猫和庆太"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d3ef63d5",
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"metadata": {},
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"source": [
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"问：有一只橘猫叫庆太，为什么？\n",
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"答：因为橘庆太。"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0a343c6d",
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"metadata": {},
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"source": [
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"Question: An orange cat's name is Keita, how so?\n",
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"Answer: Because of Tachibana Keita"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ab9b4c38",
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"metadata": {},
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"source": [
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"聞く:慶太という名前のオレンジ色の猫がいます、なぜですか？\n",
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"答え：橘慶太だから。"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6907f880",
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"metadata": {},
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"source": [
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"第一则：翻毛皮西瓜 materwelon"
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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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"id": "0f81ad8b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"image = plt.imread('materwelon.JPG')\n",
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"plt.imshow(image)\n",
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"plt.show()"
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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": 19,
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"id": "c68d96e6",
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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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"matermelon\n"
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]
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}
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],
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"source": [
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"def watermelon_shuffler(word):\n",
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" #find w in word and replace with m\n",
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" print(word.replace(\"w\",\"m\"))\n",
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" #word.replace(\"m\",\"w\")\n",
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" #TODO find the second m in word and replace with w\n",
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"watermelon_shuffler(\"watermelon\")"
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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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"id": "16fe494f",
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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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"watermelon\n"
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]
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}
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],
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"source": [
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"word = \"watermelon\"\n",
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"word.replace(\"w\",\"m\")\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": "code",
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"execution_count": null,
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"id": "01434a5f",
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"metadata": {},
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"outputs": [],
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"source": [
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"第三则：美国的坦克"
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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": 21,
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"id": "f405a7f2",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"import matplotlib.pyplot as plt\n",
|
||
|
|
"image = plt.imread('they_tank.JPG')\n",
|
||
|
|
"plt.imshow(image)\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "155584f6",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"supply a paragraph of words, use the string replace method to replace pronouns to they/them. but i am not going to do that. people should know better, and ignorance is not a bliss. "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "207162d8",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"为什么要编笑话 why is it that people are urged to joke?\n",
|
||
|
|
"编笑话是一个消解、再生产的过程。"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"id": "169f11c2",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"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": "3.9.7"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 5
|
||
|
|
}
|