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RYAN R MCCOPPIN
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04/05 jupyter
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‎04-text-byte/UnicodeText.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": 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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"('en_US', 'cp1252')\n",
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"pt_BR.UTF-8\n"
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]
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}
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],
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"source": [
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"import locale\n",
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"\n",
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"my_loc = locale.setlocale(locale.LC_COLLATE, 'pt_BR.UTF-8')\n",
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"\n",
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"print(locale.getdefaultlocale() )\n",
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"print(my_loc)"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'LATIN CAPITAL LETTER A'"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from unicodedata import name\n",
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"\n",
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"name('A')"
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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": 9,
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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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"café 5\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"('café', 4)"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from unicodedata import normalize\n",
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"\n",
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"cafe = 'cafe\\N{COMBINING ACUTE ACCENT}'\n",
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"print(cafe, len(cafe))\n",
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"\n",
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"# NFC creates shortest equivalent string\n",
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"ncafe = normalize('NFC', cafe)\n",
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"ncafe, len(ncafe)"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Ω OHM SIGN\n",
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"Ω False\n"
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]
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}
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],
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"source": [
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"from unicodedata import normalize, name\n",
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"ohm = '\\u2126'\n",
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"print(ohm, name(ohm) )\n",
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"\n",
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"ohm_c = normalize('NFC', ohm)\n",
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"print(ohm_c, ohm==ohm_c)"
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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": 20,
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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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"♕\n",
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"½ VULGAR FRACTION ONE HALF\n"
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]
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}
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],
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"source": [
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"print(\"\\N{BLACK CHESS QUEEN}\")\n",
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"print(\"\\N{WHITE CHESS QUEEN}\")\n",
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"\n",
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"# SyntaxError: (unicode error) 'unicodeescape' codec can't decode bytes in position 0-29: unknown Unicode character name\n",
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"# print(\"\\N{CAT FACE WITH SMILING EYES}\")\n",
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"\n",
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"HALF = \"\\N{VULGAR FRACTION ONE HALF}\"\n",
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"print( HALF, name(HALF))"
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]
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "a42ccb73e7d9bfdf27e036f1d2b8b681e55fc0743cc5586bc2474d4a60f4b886"
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},
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"kernelspec": {
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"display_name": "Python 3.10.4 64-bit",
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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": "3.10.4"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎05-data-classes/DataClassBuilder.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": 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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"{'a': <class 'int'>, 'b': <class 'float'>}\n",
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"DemoNTClass(a, b)\n",
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"DemoNTClass(a=8, b=1.1)\n",
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"spam\n"
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]
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}
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],
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"source": [
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"from meaning.demo_nt import DemoNTClass\n",
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"print(DemoNTClass.__annotations__)\n",
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"print(DemoNTClass.__doc__)\n",
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"nt = DemoNTClass(8)\n",
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"print(nt)\n",
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"print(nt.c)\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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"Trying to assign values gives **AttributeError** exceptions with different error messages"
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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": 14,
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"metadata": {},
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"outputs": [
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{
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"ename": "AttributeError",
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"evalue": "can't set attribute",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32mc:\\Users\\Admin\\Documents\\GitHub\\Fluent-Python\\05-data-classes\\DataClassBuilder.ipynb Cell 2'\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/Admin/Documents/GitHub/Fluent-Python/05-data-classes/DataClassBuilder.ipynb#ch0000001?line=0'>1</a>\u001b[0m nt\u001b[39m.\u001b[39ma \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mnew\u001b[39m\u001b[39m\"\u001b[39m\n",
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"\u001b[1;31mAttributeError\u001b[0m: can't set attribute"
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]
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}
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],
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"source": [
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"nt.a = \"new\""
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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": 17,
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"metadata": {},
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"outputs": [
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{
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"ename": "AttributeError",
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"evalue": "'DemoNTClass' object attribute 'c' is read-only",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32mc:\\Users\\Admin\\Documents\\GitHub\\Fluent-Python\\05-data-classes\\DataClassBuilder.ipynb Cell 3'\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/Admin/Documents/GitHub/Fluent-Python/05-data-classes/DataClassBuilder.ipynb#ch0000002?line=0'>1</a>\u001b[0m nt\u001b[39m.\u001b[39mc \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mnew\u001b[39m\u001b[39m\"\u001b[39m\n",
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"\u001b[1;31mAttributeError\u001b[0m: 'DemoNTClass' object attribute 'c' is read-only"
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]
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}
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],
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"source": [
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"nt.c = \"new\""
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]
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "a42ccb73e7d9bfdf27e036f1d2b8b681e55fc0743cc5586bc2474d4a60f4b886"
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},
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"kernelspec": {
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"display_name": "Python 3.10.4 64-bit",
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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": "3.10.4"
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},
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"orig_nbformat": 4
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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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