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tylerdavetylerdave
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add tqdm for jul 2021
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‎README.md

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@@ -20,6 +20,10 @@ See [CONTRIBUTING](CONTRIBUTING.md).
2020

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## Modules of the Month
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### 2021
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- Jul: [tqdm](tqdm/)
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### 2020
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- Dec: [HTTPX](HTTPX/)

‎tqdm/tqdm.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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"id": "8f8f5f2f",
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"metadata": {},
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"source": [
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"# tqdm\n",
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"\n",
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"Smart progress bars for CLI / Jupyter notebooks\n",
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"\n",
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"https://github.com/tqdm/tqdm"
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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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"id": "ecb65344",
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"metadata": {},
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"outputs": [],
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"source": [
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"from time import sleep"
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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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"id": "5f436f47",
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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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"Done.\n"
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]
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}
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],
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"source": [
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"# Example long(ish) loop:\n",
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"\n",
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"for i in range(50):\n",
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" sleep(0.1)\n",
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"print(\"Done.\")"
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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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"id": "5056269a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from tqdm.notebook import tqdm"
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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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"id": "8043e888",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "cd8e4e4c132b44239aa137fb2c5bf4ab",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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" 0%| | 0/50 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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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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"Done.\n"
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]
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}
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],
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"source": [
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"# Same example with progress bar:\n",
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"\n",
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"for i in tqdm(range(50)):\n",
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" sleep(0.1)\n",
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"print(\"Done.\")"
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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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"id": "87bed23c",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "0b5a82f7a14a4bf3884e5b7183a461d0",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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" 0%| | 0/4 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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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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"abcd\n"
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]
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}
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],
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"source": [
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"# Wrap any interable:\n",
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"\n",
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"text = \"\"\n",
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"for char in tqdm([\"a\", \"b\", \"c\", \"d\"]):\n",
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" sleep(0.25)\n",
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" text = text + char\n",
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"print(text)\n"
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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": "c2ed2b0a",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "b82684b4983344778a144bfd148e2e78",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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" 0%| | 0/4 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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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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"# Customize by instantiating outside loop:\n",
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"\n",
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"pbar = tqdm([\"a\", \"b\", \"c\", \"d\"])\n",
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"for char in pbar:\n",
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" sleep(0.25)\n",
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" pbar.set_description(\"Processing %s\" % char)"
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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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"id": "0885c8fb",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "6f9e95c15fd2444ba426bbcea1bda6c6",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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" 0%| | 0/100 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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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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"# Manually control updates:\n",
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"\n",
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"with tqdm(total=100) as pbar:\n",
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" for i in range(10):\n",
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" sleep(0.1)\n",
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" pbar.update(10)"
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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": 8,
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"id": "c9588103",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "2a1f3bfd17e2448d89c2a8496578a818",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Overall: 0%| | 0/4 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Step: 0%| | 0/5 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Step: 0%| | 0/5 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Step: 0%| | 0/5 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Step: 0%| | 0/5 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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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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"from tqdm.auto import trange\n",
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"\n",
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"for i in trange(4, desc='Overall'):\n",
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" for j in trange(5, desc='Step', leave=False):\n",
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" sleep(0.2)"
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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": "8e0f8ac5",
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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 (ipykernel)",
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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": "3.9.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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