Displaying Progress Bar for Concurrent Tasks

concurrent_task_progress_bar.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Displaying Progress Bar for Concurrent Tasks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pip install tqdm`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def foo(a):\n",
    "    time.sleep(0.2)\n",
    "    return a**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "version_major": 2,
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      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = []\n",
    "for i in tqdm(range(N)):\n",
    "    x.append(foo(i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = [foo(i) for i in tqdm(range(N))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = list(tqdm(map(foo, range(N)), total=N))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## multiprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from multiprocessing.pool import Pool\n",
    "from concurrent.futures import ProcessPoolExecutor\n",
    "from tqdm.contrib.concurrent import process_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "with Pool() as p:\n",
    "    x = list(tqdm(p.imap(foo, range(N)), total=N))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "model_id": "9f7f21ce1ace415bb4f22a23d42420ee",
       "version_major": 2,
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "with ProcessPoolExecutor() as executor:\n",
    "    x = list(tqdm(executor.map(foo, range(N)), total=N))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "771ee2ccf73341729607cef5fcac8af9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = process_map(foo, range(N))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## multithreading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from multiprocessing.pool import ThreadPool\n",
    "from concurrent.futures import ThreadPoolExecutor\n",
    "from tqdm.contrib.concurrent import thread_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "with ThreadPool(processes=10) as p:\n",
    "    x = list(tqdm(p.imap(foo, range(N)), total=N))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1db27a276cc64b478003d767b70edb4c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "with ThreadPoolExecutor(max_workers=10) as executor:\n",
    "    x = list(tqdm(executor.map(foo, range(N)), total=N))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67acf598d5304074934ad4d686649be4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = thread_map(foo, range(N), max_workers=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## asyncio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pip install asyncio`\n",
    "\n",
    "`pip install nest_asyncio`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import asyncio\n",
    "import nest_asyncio\n",
    "nest_asyncio.apply()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "async def afoo(a):\n",
    "    await asyncio.sleep(0.2)\n",
    "    return a**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "asyncio.run(afoo(2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "tasks = list(map(afoo, range(N)))\n",
    "x = asyncio.run(asyncio.gather(*tasks))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "async def do1():\n",
    "    tasks = list(map(afoo, range(N)))\n",
    "    return [await t for t in tqdm(asyncio.as_completed(tasks), total=N)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = asyncio.run(do1())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "async def do2():\n",
    "    tasks = list(map(asyncio.create_task, map(afoo, range(N))))\n",
    "    for t in tqdm(asyncio.as_completed(tasks), total=N):\n",
    "        await t\n",
    "    return [t.result() for t in tasks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       "version_major": 2,
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=30.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "x = asyncio.run(do2())"
   ]
  }
 ],
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if you use the auto version:

-from tqdm.notebook import tqdm
+from tqdm.auto import tqdm

you can simplify this:

-tqdm(asyncio.as_completed(tasks), total=N)
+tqdm.as_completed(tasks)

You also may as well use a list comprehension in do2() as in do1():

-    for t in tqdm(asyncio.as_completed(tasks), total=N):
-        await t
+    [await t for t in tqdm.as_completed(tasks)]