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Python Create Dictionary from List with Default Values
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‎Array/Create a List of Floats.ipynb

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{
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"cells": [
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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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"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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"[0.1, 2.3, 4.5, 6.7]\n"
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]
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}
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],
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"source": [
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"a = [0.1,2.3,4.5,6.7]\n",
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"print(a)"
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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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"## Using List Comprehension"
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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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"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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"[0.0, 0.5, 1.0, 1.5, 2.0]\n"
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]
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}
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],
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"source": [
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"a: list[float] = [x * 0.5 for x in range(5)]\n",
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"print(a)"
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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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"## Using range() with map and lambda"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5]\n"
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]
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}
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],
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"source": [
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"a = list(map(lambda x: x*0.5, range(10)))\n",
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"print(a)\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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"source": [
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"## Using numpy (for large lists or more complex operations)"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0. 0.55555556 1.11111111 1.66666667 2.22222222 2.77777778\n",
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" 3.33333333 3.88888889 4.44444444 5. ]\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"a = np.linspace(0.0, 5.0,num=10)\n",
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"print(a)"
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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": "3.12.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎Array/Python Create Dictionary from List with Default Values.ipynb

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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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"## Using dict.fromkeys()"
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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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"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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"{'a': 0, 'b': 0, 'c': 0, 'd': 0}\n"
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]
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}
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],
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"source": [
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"k = ['a', 'b','c','d']\n",
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"d=0\n",
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"res = dict.fromkeys(k,d)\n",
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"print(res)"
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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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"## Using Dictionary Comprehension"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'a': 0, 'b': 0, 'c': 0}\n"
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]
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}
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],
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"source": [
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"keys = ['a', 'b', 'c']\n",
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"d = 0\n",
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"result = {key:d for key in keys}\n",
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"print(result)"
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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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"## Using a for loop"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'b': 0, 'c': 0, 'a': 0, 'd': 0}\n"
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]
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}
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],
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"source": [
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"keys: set[str] = {'a','b','c','d'}\n",
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"d = 0\n",
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"res: dict[str, int] = {\n",
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"\n",
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"}\n",
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"for key in keys:\n",
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" res[key] = 0\n",
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"print(res)"
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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": "3.12.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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