ipython/tqdm_config.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting tqdm\n",
      "  Downloading tqdm-4.64.1-py2.py3-none-any.whl (78 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m78.5/78.5 kB\u001b[0m \u001b[31m4.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hInstalling collected packages: tqdm\n",
      "Successfully installed tqdm-4.64.1\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "BAR_FORMAT = \"{desc:<5.5}{percentage:3.0f}%|{bar:50}{r_bar}\"\n",
    "DISABLE = False"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regular usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     100%|██████████████████████████████████████████████████| 100/100 [00:05<00:00, 19.52it/s]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Bad pipe message: %s [b'\\x98\\xd1\\xc9\\x8d\\x08\\r\\xb7\\xa9\\x10g\\x10\\x9d\\x8d\\\\\\xaa\\xae\\xf8\\xd7 i\\x9a[\\x9b\\n\\xab\\xac\\x1eL\\x87#!\\x1e\\xafHW{']\n",
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      "Bad pipe message: %s [b\"\\x05\\x04\\xf7\\xfa\\xea\\xad\\x0e\\x05\\x1d\\xba\\xbcn\\x0ev\\x8e\\x8bu\\xee\\x00\\x00\\xa6\\xc0,\\xc00\\x00\\xa3\\x00\\x9f\\xcc\\xa9\\xcc\\xa8\\xcc\\xaa\\xc0\\xaf\\xc0\\xad\\xc0\\xa3\\xc0\\x9f\\xc0]\\xc0a\\xc0W\\xc0S\\xc0+\\xc0/\\x00\\xa2\\x00\\x9e\\xc0\\xae\\xc0\\xac\\xc0\\xa2\\xc0\\x9e\\xc0\\\\\\xc0`\\xc0V\\xc0R\\xc0$\\xc0(\\x00k\\x00j\\xc0s\\xc0w\\x00\\xc4\\x00\\xc3\\xc0#\\xc0'\\x00g\\x00@\\xc0r\\xc0v\\x00\\xbe\\x00\\xbd\\xc0\\n\\xc0\\x14\\x009\\x008\\x00\\x88\\x00\\x87\\xc0\\t\\xc0\\x13\\x003\\x002\\x00\\x9a\\x00\\x99\\x00E\\x00D\\xc0\\x07\\xc0\\x11\\xc0\\x08\\xc0\\x12\\x00\\x16\\x00\\x13\\x00\\x9d\\xc0\\xa1\\xc0\\x9d\\xc0Q\\x00\\x9c\\xc0\\xa0\\xc0\\x9c\\xc0P\\x00=\\x00\\xc0\\x00<\\x00\\xba\\x005\\x00\\x84\\x00/\\x00\\x96\\x00A\\x00\\x05\\x00\\n\\x00\\xff\\x01\\x00\\x00j\\x00\\x00\\x00\\x0e\"]\n",
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      "Bad pipe message: %s [b\"64h0]\\xee\\x95\\x17z\\xeb\\xa2\\xaan\\x06'\\xb2\\xa2\\xb1\\x00\\x00\\xa2\\xc0\\x14\\xc0\\n\\x009\\x008\\x007\\x006\\x00\\x88\\x00\\x87\\x00\\x86\\x00\\x85\\xc0\\x19\\x00:\\x00\\x89\\xc0\\x0f\\xc0\\x05\\x005\\x00\\x84\\xc0\\x13\\xc0\", b'3\\x002\\x001\\x000\\x00']\n",
      "Bad pipe message: %s [b\"g\\xe4>\\xf6\\xc9\\xfcS\\x02\\xa2\\xafD\\xce\\x18\\xabth\\xd59\\x00\\x00\\x86\\xc00\\xc0,\\xc0(\\xc0$\\xc0\\x14\\xc0\\n\\x00\\xa5\\x00\\xa3\\x00\\xa1\\x00\\x9f\\x00k\\x00j\\x00i\\x00h\\x009\\x008\\x007\\x006\\xc02\\xc0.\\xc0*\\xc0&\\xc0\\x0f\\xc0\\x05\\x00\\x9d\\x00=\\x005\\xc0/\\xc0+\\xc0'\\xc0#\\xc0\\x13\\xc0\\t\\x00\\xa4\\x00\\xa2\\x00\\xa0\\x00\\x9e\\x00g\\x00@\\x00?\\x00>\\x003\\x002\\x001\\x000\\xc01\\xc0-\\xc0)\\xc0%\\xc0\\x0e\\xc0\\x04\\x00\\x9c\\x00<\\x00/\\x00\\x9a\\x00\\x99\\x00\\x98\\x00\\x97\\x00\\x96\\x00\\x07\\xc0\\x11\\xc0\\x07\\xc0\\x0c\\xc0\\x02\\x00\\x05\\x00\\x04\\x00\\xff\\x02\\x01\\x00\\x00g\\x00\\x00\\x00\\x0e\\x00\\x0c\\x00\\x00\\t127.0.0.1\\x00\\x0b\\x00\\x04\\x03\\x00\\x01\\x02\\x00\\n\\x00\\x1c\\x00\\x1a\\x00\\x17\\x00\\x19\\x00\\x1c\\x00\\x1b\\x00\\x18\\x00\\x1a\\x00\\x16\\x00\\x0e\\x00\\r\\x00\\x0b\\x00\\x0c\\x00\\t\\x00\\n\\x00#\\x00\\x00\\x00\\r\\x00 \\x00\\x1e\\x06\\x01\\x06\\x02\\x06\\x03\\x05\\x01\\x05\\x02\\x05\\x03\\x04\\x01\\x04\\x02\\x04\\x03\\x03\\x01\\x03\\x02\\x03\\x03\\x02\", b'']\n",
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      "Bad pipe message: %s [b'\\xd8\\x0f\\x02\\n\\xb9\\xb87G\\xab\\xd8\\x8f\\xa5)%Q\\xa0\\x0f;\\x00\\x00>\\xc0\\x14\\xc0\\n\\x009\\x008\\x007\\x006\\xc0\\x0f\\xc0\\x05\\x005\\xc0\\x13\\xc0\\t\\x003\\x002\\x001\\x000\\xc0\\x0e\\xc0\\x04\\x00/\\x00\\x9a\\x00\\x99\\x00\\x98\\x00\\x97\\x00']\n",
      "Bad pipe message: %s [b'\\x05']\n",
      "Bad pipe message: %s [b'\\x03']\n",
      "Bad pipe message: %s [b'\\x99\\x00\\x98\\x00\\x97\\x00E\\x00D\\x00C\\x00B\\xc0\\x18\\x004\\x00\\x9b\\x00F\\xc0\\x0e\\xc0\\x04\\x00/\\x00\\x96\\x00A\\x00\\x07\\xc0\\x11\\xc0\\x07\\xc0\\x16\\x00\\x18\\xc0\\x0c\\xc0\\x02\\x00\\x05\\x00\\x04\\xc0\\x12\\xc0\\x08\\x00\\x16\\x00\\x13\\x00\\x10\\x00\\r\\xc0\\x17\\x00\\x1b\\xc0\\r\\xc0\\x03\\x00\\n\\x00\\x15\\x00\\x12\\x00\\x0f\\x00\\x0c\\x00\\x1a\\x00\\t\\x00\\x14\\x00\\x11\\x00\\x19\\x00\\x08\\x00\\x06\\x00\\x17\\x00\\x03\\xc0\\x10\\xc0\\x06\\xc0\\x15\\xc0\\x0b\\xc0\\x01\\x00\\x02\\x00\\x01\\x00\\xff\\x02\\x01\\x00\\x00C\\x00\\x00\\x00\\x0e\\x00\\x0c\\x00\\x00\\t127.0.0.1\\x00\\x0b\\x00\\x04\\x03\\x00\\x01\\x02\\x00\\n\\x00\\x1c\\x00\\x1a\\x00\\x17\\x00']\n",
      "Bad pipe message: %s [b'F']\n",
      "Bad pipe message: %s [b'\\x1c\\x00\\x1b\\x00\\x18\\x00\\x1a\\x00\\x16\\x00\\x0e\\x00\\r\\x00\\x0b\\x00\\x0c\\x00\\t\\x00\\n\\x00#\\x00']\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(100), bar_format=BAR_FORMAT, disable=DISABLE):\n",
    "    time.sleep(0.05)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Progress_apply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"group\": [\"a\", \"a\", \"b\", \"b\", \"c\"],\n",
    "    \"values\": [1, 2, 3, 4, 2]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group</th>\n",
       "      <th>values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>b</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  group  values\n",
       "0     a       1\n",
       "1     a       2\n",
       "2     b       3\n",
       "3     b       4\n",
       "4     c       2"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3/3 [00:03<00:00,  1.00s/it]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: []"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"group\").progress_apply(lambda group: time.sleep(1))"
   ]
  }
 ],
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