{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Dask-Documentation\" data-toc-modified-id=\"Dask-Documentation-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Dask Documentation</a></span></li><li><span><a href=\"#Dask-Example-on-merlin6\" data-toc-modified-id=\"Dask-Example-on-merlin6-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Dask Example on merlin6</a></span><ul class=\"toc-item\"><li><span><a href=\"#Creating-a-dask-cluster\" data-toc-modified-id=\"Creating-a-dask-cluster-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Creating a dask cluster</a></span></li><li><span><a href=\"#Attaching-a-client-and-connecting-to-the-dask-dashboard\" data-toc-modified-id=\"Attaching-a-client-and-connecting-to-the-dask-dashboard-2.2\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>Attaching a client and connecting to the dask dashboard</a></span></li><li><span><a href=\"#Working-with-a-dask-dataframe\" data-toc-modified-id=\"Working-with-a-dask-dataframe-2.3\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>Working with a dask dataframe</a></span></li><li><span><a href=\"#Functionality-that-is-not-working\" data-toc-modified-id=\"Functionality-that-is-not-working-2.4\"><span class=\"toc-item-num\">2.4&nbsp;&nbsp;</span>Functionality that is not working</a></span></li><li><span><a href=\"#Closing-the-client-connection-and-shutting-down-the-cluster\" data-toc-modified-id=\"Closing-the-client-connection-and-shutting-down-the-cluster-2.5\"><span class=\"toc-item-num\">2.5&nbsp;&nbsp;</span>Closing the client connection and shutting down the cluster</a></span></li></ul></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dask Documentation\n",
    "\n",
    "   * https://dask.org/\n",
    "   * https://github.com/dask/dask-tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dask Example on merlin6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python environment that we are running under"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# conda environments:\r\n",
      "#\r\n",
      "                         /data/user/feichtinger/conda-envs/my-test-env1\r\n",
      "base                     /opt/psi/Programming/anaconda/2019.07/conda\r\n",
      "dask-test                /opt/psi/Programming/anaconda/2019.07/conda/envs/dask-test\r\n",
      "datascience_py36         /opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py36\r\n",
      "datascience_py37      *  /opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37\r\n",
      "focus                    /opt/psi/Programming/anaconda/2019.07/conda/envs/focus\r\n",
      "hpce-tools               /opt/psi/Programming/anaconda/2019.07/conda/envs/hpce-tools\r\n",
      "jupyterhub-1.0.0_py36     /opt/psi/Programming/anaconda/2019.07/conda/envs/jupyterhub-1.0.0_py36\r\n",
      "jupyterhub_dev_py36      /opt/psi/Programming/anaconda/2019.07/conda/envs/jupyterhub_dev_py36\r\n",
      "mpi-test                 /opt/psi/Programming/anaconda/2019.07/conda/envs/mpi-test\r\n",
      "talos_py36               /opt/psi/Programming/anaconda/2019.07/conda/envs/talos_py36\r\n",
      "tensorflow-1.13.1_py36     /opt/psi/Programming/anaconda/2019.07/conda/envs/tensorflow-1.13.1_py36\r\n",
      "tensorflow-1.14.0_gpu_py36     /opt/psi/Programming/anaconda/2019.07/conda/envs/tensorflow-1.14.0_gpu_py36\r\n",
      "dfeich-test-env          /psi/home/feichtinger/.conda/envs/dfeich-test-env\r\n",
      "\r\n"
     ]
    }
   ],
   "source": [
    "! conda info -e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a dask cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask_jobqueue import SLURMCluster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we define the fast infiniband network `ib0` for the `interfacce` parameter. For a first functional test you may use the `eno1` ethernet network, but never for high throuput production. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster = SLURMCluster(queue=\"hourly\", processes=6, cores=24, memory=\"10GB\",\n",
    "                      interface=\"ib0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The scale command launches the jobs for the worker nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.scale(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can check in your terminal whether the worker job has been submitted and is running"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)\r\n",
      "         134909471    hourly dask-wor feichtin  R       0:32      1 merlin-c-013\r\n",
      "         134908606   general spawner- feichtin  R      50:27      1 merlin-c-017\r\n"
     ]
    }
   ],
   "source": [
    "!squeue -u $USER"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attaching a client and connecting to the dask dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask.distributed import Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://192.168.196.37:38610</li>\n",
       "  <li><b>Dashboard: </b><a href='http://192.168.196.37:8787/status' target='_blank'>http://192.168.196.37:8787/status</a>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>6</li>\n",
       "  <li><b>Cores: </b>24</li>\n",
       "  <li><b>Memory: </b>10.02 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: scheduler='tcp://192.168.196.37:38610' processes=6 cores=24>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client = Client(cluster)\n",
    "\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the dashboard address shown is on the Ib network that is private to the cluster. In order to reach the private network address of the dashboard with your browser, you can use SSH-tunneling or sshuttle, e.g.\n",
    "\n",
    "```\n",
    "sshuttle -v -r merlin-l-001 192.168.196.00/24\n",
    "```\n",
    "\n",
    "You need to have **sudo** permissions on your machine in order to run sshuttle."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Working with a dask dataframe\n",
    "\n",
    "Creation of a dask dataframe by reading in a dataset. We are hosting the **nyflights** data set from the dask tutorial centrally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.dataframe as dd\n",
    "import os\n",
    "df = dd.read_csv(os.path.join('/data/project/general/public/dask-tutorial/data', 'nycflights', '*.csv'),\n",
    "                 parse_dates={'Date': [0, 1, 2]},\n",
    "                 dtype={'TailNum': object,\n",
    "                        'CRSElapsedTime': float,\n",
    "                        'Cancelled': bool})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Date</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>...</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>Diverted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1621.0</td>\n",
       "      <td>1540</td>\n",
       "      <td>1747.0</td>\n",
       "      <td>1701</td>\n",
       "      <td>US</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>PIT</td>\n",
       "      <td>319.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1990-01-02</td>\n",
       "      <td>2</td>\n",
       "      <td>1547.0</td>\n",
       "      <td>1540</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>1701</td>\n",
       "      <td>US</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>PIT</td>\n",
       "      <td>319.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1990-01-03</td>\n",
       "      <td>3</td>\n",
       "      <td>1546.0</td>\n",
       "      <td>1540</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>1701</td>\n",
       "      <td>US</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>PIT</td>\n",
       "      <td>319.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1990-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>1542.0</td>\n",
       "      <td>1540</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>1701</td>\n",
       "      <td>US</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>PIT</td>\n",
       "      <td>319.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1990-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>1549.0</td>\n",
       "      <td>1540</td>\n",
       "      <td>1706.0</td>\n",
       "      <td>1701</td>\n",
       "      <td>US</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>PIT</td>\n",
       "      <td>319.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  DayOfWeek  DepTime  CRSDepTime  ArrTime  CRSArrTime  \\\n",
       "0 1990-01-01          1   1621.0        1540   1747.0        1701   \n",
       "1 1990-01-02          2   1547.0        1540   1700.0        1701   \n",
       "2 1990-01-03          3   1546.0        1540   1710.0        1701   \n",
       "3 1990-01-04          4   1542.0        1540   1710.0        1701   \n",
       "4 1990-01-05          5   1549.0        1540   1706.0        1701   \n",
       "\n",
       "  UniqueCarrier  FlightNum TailNum  ActualElapsedTime  ...  AirTime  ArrDelay  \\\n",
       "0            US         33     NaN               86.0  ...      NaN      46.0   \n",
       "1            US         33     NaN               73.0  ...      NaN      -1.0   \n",
       "2            US         33     NaN               84.0  ...      NaN       9.0   \n",
       "3            US         33     NaN               88.0  ...      NaN       9.0   \n",
       "4            US         33     NaN               77.0  ...      NaN       5.0   \n",
       "\n",
       "   DepDelay  Origin Dest Distance  TaxiIn  TaxiOut  Cancelled  Diverted  \n",
       "0      41.0     EWR  PIT    319.0     NaN      NaN      False         0  \n",
       "1       7.0     EWR  PIT    319.0     NaN      NaN      False         0  \n",
       "2       6.0     EWR  PIT    319.0     NaN      NaN      False         0  \n",
       "3       2.0     EWR  PIT    319.0     NaN      NaN      False         0  \n",
       "4       9.0     EWR  PIT    319.0     NaN      NaN      False         0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's find the maximal departure delay time of all flights that were not cancelled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dd.Scalar<series-..., dtype=float64>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Maximum non-cancelled delay\n",
    "largest_delay = df[~df.Cancelled].DepDelay.max()\n",
    "largest_delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "largest_delay.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1435.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "largest_delay.compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Functionality that is not working"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Starting ipython workers does not work, currently"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.core - ERROR - IPython didn't start in a reasonable amount of time.\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\", line 416, in handle_comm\n",
      "    result = await result\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/scheduler.py\", line 2663, in broadcast\n",
      "    [send_message(address) for address in addresses if address is not None]\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/utils.py\", line 228, in All\n",
      "    result = await tasks.next()\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/scheduler.py\", line 2659, in send_message\n",
      "    resp = await send_recv(comm, close=True, serializers=serializers, **msg)\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\", line 561, in send_recv\n",
      "    raise Exception(response[\"text\"])\n",
      "Exception: IPython didn't start in a reasonable amount of time.\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=Exception(\"IPython didn't start in a reasonable amount of time.\")>\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/tornado/gen.py\", line 742, in run\n",
      "    yielded = self.gen.throw(*exc_info)  # type: ignore\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/utils.py\", line 241, in quiet\n",
      "    yield task\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/tornado/gen.py\", line 735, in run\n",
      "    value = future.result()\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/scheduler.py\", line 2659, in send_message\n",
      "    resp = await send_recv(comm, close=True, serializers=serializers, **msg)\n",
      "  File \"/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\", line 561, in send_recv\n",
      "    raise Exception(response[\"text\"])\n",
      "Exception: IPython didn't start in a reasonable amount of time.\n"
     ]
    },
    {
     "ename": "Exception",
     "evalue": "IPython didn't start in a reasonable amount of time.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-15-10110b374480>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_ipython_workers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/client.py\u001b[0m in \u001b[0;36mstart_ipython_workers\u001b[0;34m(self, workers, magic_names, qtconsole, qtconsole_args)\u001b[0m\n\u001b[1;32m   3559\u001b[0m             \u001b[0mworkers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mworkers\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3560\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3561\u001b[0;31m         \u001b[0;34m(\u001b[0m\u001b[0mworkers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minfo_dict\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msync\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_start_ipython_workers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mworkers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3562\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3563\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmagic_names\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmagic_names\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36msync\u001b[0;34m(loop, func, callback_timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m    335\u001b[0m             \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    336\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 337\u001b[0;31m         \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    338\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    339\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m    691\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    692\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 693\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    694\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    695\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36mf\u001b[0;34m()\u001b[0m\n\u001b[1;32m    320\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mcallback_timeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    321\u001b[0m                 \u001b[0mfuture\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgen\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_timeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimedelta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mseconds\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback_timeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 322\u001b[0;31m             \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32myield\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    323\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    324\u001b[0m             \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/tornado/gen.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    733\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    734\u001b[0m                     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 735\u001b[0;31m                         \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    736\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    737\u001b[0m                         \u001b[0mexc_info\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/client.py\u001b[0m in \u001b[0;36m_start_ipython_workers\u001b[0;34m(self, workers)\u001b[0m\n\u001b[1;32m   3501\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3502\u001b[0m         responses = await self.scheduler.broadcast(\n\u001b[0;32m-> 3503\u001b[0;31m             \u001b[0mmsg\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"start_ipython\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mworkers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mworkers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3504\u001b[0m         )\n\u001b[1;32m   3505\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mworkers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponses\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\u001b[0m in \u001b[0;36msend_recv_from_rpc\u001b[0;34m(**kwargs)\u001b[0m\n\u001b[1;32m    748\u001b[0m             \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcomm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcomm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"ConnectionPool.\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    749\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 750\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mawait\u001b[0m \u001b[0msend_recv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcomm\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    751\u001b[0m             \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    752\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpool\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreuse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maddr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcomm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\u001b[0m in \u001b[0;36msend_recv\u001b[0;34m(comm, reply, serializers, deserializers, **kwargs)\u001b[0m\n\u001b[1;32m    557\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"status\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"uncaught-error\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    558\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcomm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeserialize\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 559\u001b[0;31m             \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mclean_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    560\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    561\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"text\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m    690\u001b[0m                 \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    691\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 692\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    693\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    694\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\u001b[0m in \u001b[0;36mhandle_comm\u001b[0;34m()\u001b[0m\n\u001b[1;32m    414\u001b[0m                             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0masyncio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mensure_future\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    415\u001b[0m                             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_ongoing_coroutines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 416\u001b[0;31m                             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mawait\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    417\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mCommClosedError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCancelledError\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    418\u001b[0m                         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"running\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/scheduler.py\u001b[0m in \u001b[0;36mbroadcast\u001b[0;34m()\u001b[0m\n\u001b[1;32m   2661\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2662\u001b[0m         results = await All(\n\u001b[0;32m-> 2663\u001b[0;31m             \u001b[0;34m[\u001b[0m\u001b[0msend_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maddress\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0maddress\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maddresses\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0maddress\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2664\u001b[0m         )\n\u001b[1;32m   2665\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36mAll\u001b[0;34m()\u001b[0m\n\u001b[1;32m    226\u001b[0m     \u001b[0;32mwhile\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtasks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdone\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 228\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mawait\u001b[0m \u001b[0mtasks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    229\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    230\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/scheduler.py\u001b[0m in \u001b[0;36msend_message\u001b[0;34m()\u001b[0m\n\u001b[1;32m   2657\u001b[0m             )\n\u001b[1;32m   2658\u001b[0m             \u001b[0mcomm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Scheduler Broadcast\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2659\u001b[0;31m             \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mawait\u001b[0m \u001b[0msend_recv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomm\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mserializers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mserializers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2660\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2661\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/psi/Programming/anaconda/2019.07/conda/envs/datascience_py37/lib/python3.7/site-packages/distributed/core.py\u001b[0m in \u001b[0;36msend_recv\u001b[0;34m()\u001b[0m\n\u001b[1;32m    559\u001b[0m             \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mclean_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    560\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 561\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"text\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    562\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    563\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mException\u001b[0m: IPython didn't start in a reasonable amount of time."
     ]
    }
   ],
   "source": [
    "client.start_ipython_workers()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method start_ipython_workers in module distributed.client:\n",
      "\n",
      "start_ipython_workers(workers=None, magic_names=False, qtconsole=False, qtconsole_args=None) method of distributed.client.Client instance\n",
      "    Start IPython kernels on workers\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    workers: list (optional)\n",
      "        A list of worker addresses, defaults to all\n",
      "    \n",
      "    magic_names: str or list(str) (optional)\n",
      "        If defined, register IPython magics with these names for\n",
      "        executing code on the workers.  If string has asterix then expand\n",
      "        asterix into 0, 1, ..., n for n workers\n",
      "    \n",
      "    qtconsole: bool (optional)\n",
      "        If True, launch a Jupyter QtConsole connected to the worker(s).\n",
      "    \n",
      "    qtconsole_args: list(str) (optional)\n",
      "        Additional arguments to pass to the qtconsole on startup.\n",
      "    \n",
      "    Examples\n",
      "    --------\n",
      "    >>> info = c.start_ipython_workers() # doctest: +SKIP\n",
      "    >>> %remote info['192.168.1.101:5752'] worker.data  # doctest: +SKIP\n",
      "    {'x': 1, 'y': 100}\n",
      "    \n",
      "    >>> c.start_ipython_workers('192.168.1.101:5752', magic_names='w') # doctest: +SKIP\n",
      "    >>> %w worker.data  # doctest: +SKIP\n",
      "    {'x': 1, 'y': 100}\n",
      "    \n",
      "    >>> c.start_ipython_workers('192.168.1.101:5752', qtconsole=True) # doctest: +SKIP\n",
      "    \n",
      "    Add asterix * in magic names to add one magic per worker\n",
      "    \n",
      "    >>> c.start_ipython_workers(magic_names='w_*') # doctest: +SKIP\n",
      "    >>> %w_0 worker.data  # doctest: +SKIP\n",
      "    {'x': 1, 'y': 100}\n",
      "    >>> %w_1 worker.data  # doctest: +SKIP\n",
      "    {'z': 5}\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    iter_connection_info: list\n",
      "        List of connection_info dicts containing info necessary\n",
      "        to connect Jupyter clients to the workers.\n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    Client.start_ipython_scheduler: start ipython on the scheduler\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(client.start_ipython_workers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Closing the client connection and shutting down the cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "client.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After a close() of a client, one can connect a new client to the existing cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://192.168.196.37:38610</li>\n",
       "  <li><b>Dashboard: </b><a href='http://192.168.196.37:8787/status' target='_blank'>http://192.168.196.37:8787/status</a>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>6</li>\n",
       "  <li><b>Cores: </b>24</li>\n",
       "  <li><b>Memory: </b>10.02 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: scheduler='tcp://192.168.196.37:38610' processes=6 cores=24>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client2 = Client(cluster)\n",
    "\n",
    "client2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "client2.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Closing the Cluster** shuts the dask workers down. Please **always shut down the cluster** when you are finished. Else the cores will not be released and you will continue to block the resources for others!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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