mirror of https://github.com/tqdm/tqdm.git
513 lines
12 KiB
Plaintext
513 lines
12 KiB
Plaintext
{
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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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"This file is part of the [test suite](./tests) and will be moved there when [nbval#116](https://github.com/computationalmodelling/nbval/issues/116#issuecomment-793148404) is fixed.\n",
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"\n",
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"See [DEMO.ipynb](DEMO.ipynb) instead for notebook examples."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from functools import partial\n",
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"from time import sleep\n",
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"\n",
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"from tqdm.notebook import tqdm_notebook\n",
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"from tqdm.notebook import tnrange\n",
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"\n",
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"# avoid displaying widgets by default (pollutes output cells)\n",
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"tqdm = partial(tqdm_notebook, display=False)\n",
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"trange = partial(tnrange, display=False)"
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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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"Help on function display in module tqdm.notebook:\n",
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"\n",
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"display(self, msg=None, pos=None, close=False, bar_style=None, check_delay=True)\n",
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" Use `self.sp` to display `msg` in the specified `pos`.\n",
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" \n",
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" Consider overloading this function when inheriting to use e.g.:\n",
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" `self.some_frontend(**self.format_dict)` instead of `self.sp`.\n",
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" \n",
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" Parameters\n",
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" ----------\n",
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" msg : str, optional. What to display (default: `repr(self)`).\n",
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" pos : int, optional. Position to `moveto`\n",
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" (default: `abs(self.pos)`).\n",
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"\n"
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]
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}
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],
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"source": [
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"help(tqdm_notebook.display)"
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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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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "7c18c038bf964b55941e228503292506",
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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%| | 0/9 [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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"0\n",
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"6\n",
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"7\n",
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"8\n"
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]
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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": "e29668be41ca4e40b16fb98572b333a5",
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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%| | 0/9 [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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"text/plain": [
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"True"
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]
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},
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"execution_count": 3,
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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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"# NBVAL_TEST_NAME: basic use\n",
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"with tqdm_notebook(range(9)) as t:\n",
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" for i in t:\n",
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" print(i)\n",
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"assert t.container.children[1].bar_style == 'success'\n",
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"\n",
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"t = tqdm_notebook(total=9)\n",
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"t.update()\n",
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"t.refresh()"
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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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"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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" 11%|█ | 1/9 [00:00<00:00, 17.73it/s]\n",
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" 20%|██ | 1/5 [00:00<00:00, 341.50it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: reset\n",
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"print(t)\n",
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"t.reset(total=5)\n",
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"t.update(1)\n",
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"print(t)"
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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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"source": [
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"# NBVAL_TEST_NAME: bar_style\n",
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"assert t.container.children[1].bar_style != 'danger'\n",
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"t.close()\n",
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"assert t.container.children[1].bar_style == 'danger'"
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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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"1\n",
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: repr\n",
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"with trange(1, 9) as t:\n",
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" print(t)\n",
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" print(t.container)\n",
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" it = iter(t)\n",
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" print(next(it))\n",
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" print(t)\n",
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" print(t.container)"
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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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"source": [
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"t = trange(9)"
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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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"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%| | 0/9 [00:00<?, ?it/s]\n",
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" 0%| | 0/9 [00:00<?, ?it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: display pre\n",
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"print(t)\n",
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"print(t.container)"
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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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"source": [
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"for i in t:\n",
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" pass"
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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": 10,
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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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"100%|██████████| 9/9 [00:00<00:00, 132.23it/s]\n",
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"100%|##########| 9/9 [00:00<00:00, 131.02it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: display post\n",
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"print(t)\n",
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"print(t.container)"
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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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"no total: 0it [00:00, ?it/s]\n",
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"no total: 1it [00:00, 47.83it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: no total\n",
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"with tqdm(desc=\"no total\") as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)"
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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": 12,
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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%| | 0/9 [00:00<?, ?it/s]\n",
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" 11%|███▍ | 1/9 [00:00<00:00, 45.06it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: ncols\n",
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"with trange(9, ncols=66) as t:\n",
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" print(t)\n",
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" for i in t:\n",
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" if i == 1:\n",
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" break\n",
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" print(t)"
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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": 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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" 0%| | 0/1 [00:00<?, ?it/s]\n",
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"100%|██████████| 1/1 [00:00<00:00, 54.60it/s]\n",
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" 0%| | 0/9 [00:00<?, ?it/s]\n",
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" 11%|█ | 1/9 [00:00<00:00, 57.43it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: leave\n",
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"assert (False, None) != (getattr(t.container, \"visible\", False), getattr(t.container, \"_ipython_display_\", None))\n",
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"for total in (1, 9):\n",
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" with tqdm(total=total, leave=False) as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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" assert total != 1 or (False, None) == (\n",
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" getattr(t.container, \"visible\", False), getattr(t.container, \"_ipython_display_\", None)\n",
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" )"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0it [00:00, ?it/s]\n",
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"1it [00:00, 47.87it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: no total\n",
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"with tqdm() as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)"
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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": 15,
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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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"disable: None\n",
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"100%|██████████| 1/1 [00:00<00:00, 53.24it/s]\n",
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"100%|██████████| 1/1 [00:00<00:00, 1880.85it/s]\n",
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"disable: True\n",
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: reset and disable\n",
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"for disable in (None, True):\n",
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" print(\"disable:\", disable)\n",
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" with tqdm(total=1, disable=disable) as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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"\n",
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" t.reset(total=9)\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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" with tqdm(disable=disable) as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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"\n",
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" t.reset(total=1)\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)"
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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": 16,
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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%|| 0/1 [00:00<?, ?it/s]\n",
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"100%|| 1/1 [00:00<00:00, 32.57it/s]\n",
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" 0%| \n",
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"100%|██████████\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: bar_format\n",
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"with tqdm(total=1, bar_format='{l_bar}{r_bar}') as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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"\n",
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"with tqdm(total=1, bar_format='{l_bar}{bar}') as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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" 0%|\u001b[33m \u001b[0m| 0/1 [00:00<?, ?it/s]\n",
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"100%|\u001b[33m██████████\u001b[0m| 1/1 [00:00<00:00, 47.14it/s]\n"
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]
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}
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],
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"source": [
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"# NBVAL_TEST_NAME: colour\n",
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"assert t.colour != 'yellow'\n",
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"with tqdm(total=1, colour='yellow') as t:\n",
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" print(t)\n",
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" t.update()\n",
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" print(t)\n",
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" assert t.colour == 'yellow'"
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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": 18,
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"metadata": {},
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"outputs": [],
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"source": [
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"# NBVAL_TEST_NAME: delay no trigger\n",
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"with tqdm_notebook(total=1, delay=10) as t:\n",
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" t.update()"
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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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"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": "fe102eedbb4f437783fbd0cff32f6613",
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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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"100%|##########| 1/1 [00:00<00:00, 7.68it/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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"# NBVAL_TEST_NAME: delay trigger\n",
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"with tqdm_notebook(total=1, delay=0.1) as t:\n",
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" sleep(0.1)\n",
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" t.update()"
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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 [conda env:tqdm]",
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"language": "python",
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"name": "conda-env-tqdm-py"
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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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},
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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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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
|