multitasking_python.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor\n",
    "import numpy as np\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "from PIL import Image\n",
    "import random\n",
    "import string\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "MULTITHREADING_TITLE=\"Multithreading\"\n",
    "MULTIPROCESSING_TITLE=\"Multiprocessing\"\n",
    "\n",
    "def visualize_runtimes(results, title):\n",
    "    start,stop = np.array(results).T\n",
    "    plt.barh(range(len(start)),stop-start,left=start)\n",
    "    plt.grid(axis='x')\n",
    "    plt.ylabel(\"Tasks\")\n",
    "    plt.xlabel(\"Seconds\")\n",
    "    plt.title(title)\n",
    "    return stop[-1]-start[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def multithreading(func, args, workers):\n",
    "    begin_time = time.time()\n",
    "    with ThreadPoolExecutor(max_workers=workers) as executor:\n",
    "        res = executor.map(func, args, [begin_time for i in range(len(args))])\n",
    "    return list(res)\n",
    "        \n",
    "def multiprocessing(func, args, workers):\n",
    "    begin_time = time.time()\n",
    "    with ProcessPoolExecutor(max_workers=workers) as executor:\n",
    "        res = executor.map(func, args, [begin_time for i in range(len(args))])\n",
    "    return list(res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# API Calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from urllib.request import urlopen\n",
    "\n",
    "def download(url, base):\n",
    "    start = time.time() - base\n",
    "    try:\n",
    "        resp = urlopen(url)\n",
    "    except Exception as e:\n",
    "        print ('ERROR: %s' % e)\n",
    "    stop = time.time() - base\n",
    "    return start,stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "N = 16\n",
    "URL = 'http://scholar.princeton.edu/sites/default/files/oversize_pdf_test_0.pdf'\n",
    "urls = [URL for i in range(N)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 6.36 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [download(url, 1) for url in urls]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.8347444534301758"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Sr/TVI/gwcDrwyy3tkGRNkskkk1NTU6OrTJIaM/IgSHIssKGqrtnaflW1tqrGq2p8bGxs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\n/wP5JHqaFPzUTQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe26040ffd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(download, urls, 1), \"Single Thread\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.7525379657745361"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VgySp3RnBi4HrW+xfkkRLiSDJgcDvAv/QRv+SpF9qa0bwd8CZwC+WapBkY5K5JHPz8/OT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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1445d8278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(download, urls, 2),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0224919319152832"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DU2qpRnKbYhobu22wpbLZKE7aPI4IJGngeisESbZL8s0kn+krgySp3xHBK4Crety/JIme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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144674048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(download, urls, 4),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.8083174228668213"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe261bb83c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(download, urls, 1), \"Single Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.5206444263458252"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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km0pZHwp8s+s4JEmNvu4aeiVwSnvH0HdpnossSepBL4mgqi6ieeqZBmJbr9a16Jy07fRx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\nzkQgSQNnIpCkgTMRSNLA/X8oJy/0JP8PdgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14438de80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(download, urls, 2), MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.1228179931640625"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144296198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(download, urls, 4), MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IO Heavy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def io_heavy(text,base):\n",
    "    start = time.time() - base\n",
    "    f = open('output.txt', 'wt', encoding='utf-8')\n",
    "    f.write(text)\n",
    "    f.close()\n",
    "    stop = time.time() - base\n",
    "    return start,stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "N=12\n",
    "TEXT = ''.join(random.choice(string.ascii_lowercase) for i in range(10**7*5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 1.37 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [io_heavy(TEXT,1) for i in range(N)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading\n",
    "\n",
    "Should see good benefit from this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2725670337677002"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JapxBIEmNMwgkqXEGgSQ1btE3nbOpnCTNjysCSWqcQSBJjTMIJKlxi+IYwQ9/+uQWT0Dj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\nC0BAfqgesgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe2627a9da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(io_heavy, [TEXT for i in range(N)], 1),\"Single Thread\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.68187546730041504"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1ziCQpMYZBJLUOINAkhpnEEhS4wwCSWqcQSBJjTMIJKlxUzHp3NaPWMbVTg4nSUvCHoEk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\nCCSpcf8fo1rEZjtPHAIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14414d390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(io_heavy, [TEXT for i in range(N)], 2),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.59884214401245117"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CSWqcQSBJjZuIMYK+F6ZZCm95xiaOm7A2uUCPNJ3sEUhS4wwCSWqcQSBJjTMIJKlxBoEk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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14414d470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(io_heavy, [TEXT for i in range(N)], 4),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing\n",
    "\n",
    "Should see good benefit from this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.3357248306274414"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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U1PgLlKRGDBIESbaiC4FPVdWnh6hBktQZ4l1DAf4MuLGqPjju40uSHm+IEcFLgNcDL09y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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe2586f5a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(io_heavy, [TEXT for i in range(N)], 1),\"Single Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9419243335723877"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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yA/AF4N1V9ZP1X6+qJVU1XlXjY2Njoy9QkhrRSxAk2ZZBCJxVVef1UYMkaaCPq4YCfBK4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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1445e6f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(io_heavy, [TEXT for i in range(N)], 2),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.89698147773742676"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VqlXjLk2SmtFbECTZFvgC8O6q+snar1fVkqqarKrJiYmJ8RcoSY3oJQiSbMkgBM6oqnP6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\niM8PGQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144385390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(io_heavy, [TEXT for i in range(N)], 4),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Numpy Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Numpy Addition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Does not use parallel processing by default\n",
    "#But will see speedups if multiprocessing used\n",
    "#Because numpy sidesteps python's GIL\n",
    "def addition(i, base):\n",
    "    start = time.time() - base\n",
    "    res = a + b\n",
    "    stop = time.time() - base\n",
    "    return start,stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "DIMS = 20000\n",
    "N = 20\n",
    "DIMS_ARR = [DIMS for i in range(N)]\n",
    "a = np.random.rand(DIMS,DIMS)\n",
    "b = np.random.rand(DIMS,DIMS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 14.9 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [addition(i, time.time()) for i in range(N)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading\n",
    "\n",
    "Some benefit for numpy addition (operation avoids GIL, but not parallel by default)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.84851598739624"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vt/X1wIuAK+k9ASVJ2ku0uYfxu8AqYGvTN+OFwL+MNJUkac5pUzB+UFUPQW/wwaZPxIrR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe25807a6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(addition, [i for i in range(N)], 1),\"Single Thread\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.119851350784302"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144070940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(addition, [i for i in range(N)], 2),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16.048599004745483"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144022ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(addition, [i for i in range(N)], 4),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing\n",
    "\n",
    "Some benefit for numpy addition (operation avoids GIL, but not parallel by default)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.817286252975464"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe2580701d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(addition, [i for i in range(N)], 1),\"Single Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.861897945404053"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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M1Y3zPyt19wC+Znu+7Y3lPS8FJgFn2b55iz9hRA+MdhzF8uXLWbNobneCieiS0U4NMo2a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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14442d9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(addition, [i for i in range(N)], 1),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.71403169631958"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RfEPScVQ3zv+s1N0L+JrtObY3lfe8DJgAnGP75q3+hBE9sLXjKJYtW8aa+bO3bzARXbKl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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff144458860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(addition, [i for i in range(N)], 1),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dot Product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Automatic parallel processing built works out of the box\n",
    "#Depending on BLAS impl, MKL (default with anaconda3) does\n",
    "#Should NOT see speedups with multithreading/processing\n",
    "def dot_product(i, base):\n",
    "    start = time.time() - base\n",
    "    res = np.dot(a,b)\n",
    "    stop = time.time() - base\n",
    "    return start,stop\n",
    "\n",
    "DIMS = 3000\n",
    "N = 10\n",
    "DIMS_ARR = [DIMS for i in range(N)]\n",
    "a = np.random.rand(DIMS,DIMS)\n",
    "b = np.random.rand(DIMS,DIMS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 2.87 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [dot_product(i, time.time()) for i in range(N)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading\n",
    "\n",
    "No benefit on dot product (since already parallel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.197455883026123"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+dB3zOAC4f+gi5mFd45vGmsC6lsu6Hu/QqjpwnIZTtbQCcHtVbRm6iLmSbLOu8U1jXdNY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\nktQIA1+SGmHgS1IjDHxJasT/ByDt2BAwxEp5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe28434a9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(dot_product, [i for i in range(N)], 1),\"Single Thread\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.3708603382110596"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9w/U/vKqOGudNM7W0AnBzVW2adhErkWSHtU/ePNcO812/tU/PSut3SkeSGmHgS1IjZi3w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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1442dce48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(dot_product, [i for i in range(N)], 2),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.5823237895965576"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+C79pK0laHwa+JDViUOvhP3zfDdw0ovXVx7g/7BhrlrQ2HOFLUiMMfElqhIEvSY0w8CWp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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1444633c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(dot_product, [i for i in range(N)], 4),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing\n",
    "\n",
    "No benefit on dot product (since already parallel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.1076877117156982"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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J26q6sKrWVdW6FSufM+5yJGnZ6jPw7wEOmfb44O45SdIY9Bn4XwFemOQFSfYCTgcu67E9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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe25855e438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(dot_product, [i for i in range(N)], 1),\"Single Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.2974824905395508"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7TpI0Bn0G/peAByW5f5K9gOOBM3psT5I0RG9z6VTVnUleDZwDLAM+WFVb+mpPkjRcr5On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\nS1IjDHxJasT/ASQyIHiqj7rlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14441b160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(dot_product, [i for i in range(N)], 2),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.5308358669281006"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AR4ETe2xPkjREn4G/Drhh1uMd3XM/JMmmJNuSbLv3jtt6LEeS2jb2i7ZVtbmqNlTVhlWr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\nr7oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1441ed358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(dot_product, [i for i in range(N)], 4),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### CPU Intensive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def cpu_heavy(n,base):\n",
    "    start = time.time() - base\n",
    "    count = 0\n",
    "    for i in range(n):\n",
    "        count += i\n",
    "    stop = time.time() - base\n",
    "    return start,stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "N = 10**7\n",
    "ITERS = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 4.22 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [cpu_heavy(N, time.time()) for i in range(ITERS)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading\n",
    "\n",
    "No benefit on CPU-intensive tasks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9721176624298096"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YSJLN1rd01rc81rd8s15j3/V5SkeSGmHgS1IjZi3wzxm6gEVY3/JY3/JY3/LNeo291jdT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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe2621276d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(cpu_heavy, [N for i in range(ITERS)], 1),\"Single Thread\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.8206055164337158"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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D0EXMVZKt01g3WPtQprX2aa0brB0c0pGkZhj4ktSISQv8zUMXME/TWjdY+1CmtfZprRus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\nAT4NptrvzwJIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff14412b278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(cpu_heavy, [N for i in range(ITERS)], 2),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.4440646171569824"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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N20F5DuNh0s9h0utfqezhS1IjDHxJaoSBL0mNMPAlqREGviQ1wsCXpEYY+JLUCANfkhph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\nQnlhvAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1440666d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multithreading(cpu_heavy, [N for i in range(ITERS)], 4),MULTITHREADING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing\n",
    "\n",
    "Shows benefits on CPU-intensive tasks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9965052604675293"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YJGkAfQb+V4EXJ3lRkj2A04BLe2xPkjRGb2vpVNXmJGcCVwKLgE9U1fq+2pMkjdfr4mlV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\nFwiKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe26205e400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(cpu_heavy, [N for i in range(ITERS)], 1),\"Single Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.5963289737701416"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SNIA+A/+7wIOSPCDJ3YHDgC/22J4kaYze5tKpqpuTvAr4KrAA+EhVre2rPUnSeL1OnlZV\nJwEn9dmGJGlmBr9oK0maGwa+JDVioubDd03b23NNW0mzyR6+JDXCwJekRhj4ktQIA1+SGmHgS1Ij\nDHxJaoSBL0mNMPAlqREGviQ1IlU1dA23SbIeuGToOibIIuCqoYuYMJ6TzfO8bKqVc3L/qlo8kx0n\nKvB1e0nWVNXyoeuYJJ6TzfO8bMpzsimHdCSpEQa+JDXCwJ9sq4YuYAJ5TjbP87Ipz8lGHMOXpEbY\nw5ekRhj4ktQIA38CJflIkiuTfG/oWiZFkt2SnJLk+0nWJjly6JqGlmS7JGckObc7J38zdE2TIsmC\nJGcn+fLQtUwSA38yfRQ4YOgiJszNwBuqak9gX+CVSfYcuKah3QjsX1UPAx4OHJBk34FrmhRHAhcM\nXcSkMfAnUFX9D3D10HVMkqq6oqrO6h7/mtF/5iXDVjWsGrmue7pt99P8XRhJlgIHAR8aupZJY+Br\nq5NkGfAI4PRhKxleN3RxDnAlcHJVNX9OgPcBRwG3Dl3IpDHwtVVJsiPwWeC1VfWroesZWlXdUlUP\nB5YCj06y19A1DSnJwcCVVXXm0LVMIgNfW40k2zIK++Oq6oSh65kkVXUNcApe+3kccEiSi4FPAfsn\n+cSwJU0OA19bhSQBPgxcUFXHDF3PJEiyOMnO3ePtgacAFw5b1bCq6i1VtbSqlgGHAd+oqiMGLmti\nGPgTKMkngW8DeyRZl+SlQ9c0AR4HPJ9Rj+2c7ufAoYsa2C7AKUnOA77LaAzf2xA1LadWkKRG2MOX\npEYY+JLUCANfkhph4EtSIwx8SWqEga95K8nbulkkz+tu43zMHLe/wtkaNUm2GboAqQ9J9gMOBh5Z\nVTcmWQTcfeCypEHZw9d8tQtwVVXdCFBVV1XV5Un2SfLNJGcm+WqSXQCSPDDJ17u55c9KsntG3pPk\ne0nOT/Lcbt8VSVYnOT7JhUmO674JTJIDum1nAc/aUEySJ075wtjZSe4596dErfOLV5qXuknWTgUW\nAl8HPg18C/gmcGhVre8C/GlV9ZIkpwNHV9XnkmzHqDP0dOAVjOanWcTo26yPAfYAvgA8BLgcOA14\nE7AG+CGwP3BR1+bCqjo4yZe645/W1XZDVd08F+dC2sAevualbp74fYCVwHpG4ftyYC/g5G5K4b8E\nlna97SVV9bnud2+oqt8Ajwc+2c1I+XNGHxaP6po4o6rWVdWtwDnAMuDBwE+q6oc16klNnbTrNOCY\nJK8BdjbsNQTH8DVvVdUtwGpgdZLzgVcCa6tqv6n73cnhlRunPL6FO/i/VFVHJzkROBA4LcnTqqrp\nic409+zha15KskeSB03Z9HBGq2Qt7i7okmTbJA/pVtBal+SZ3fZ7JFkI/C/w3G6RkcXAE4AzxjR7\nIbAsye7d88On1LN7VZ1fVe9iNDT04Fl6q9KMGfiar3YEPtYten4esCfw18CzgXclOZfRUMxju/2f\nD7ym2/dbwH2BzwHnAecC3wCOqqqfTddgVd3AaAjpxO6i7ZVTXn5td/H3POB3wFdm761KM+NFW0lq\nhD18SWqEgS9JjTDwJakRBr4kNcLAl6RGGPiS1AgDX5Ia8X+a5xziTUpb/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff13404a6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(cpu_heavy, [N for i in range(ITERS)], 2),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8979084491729736"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SsKkPAlfVmVW1pqrWLFt+wLTLkaRm9BkANwGHDt0+pNsmSZoBfQbAV4HHJ3lskocDJwOf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\napQBIEmNMgAkqVEGgCQ16v8DmhwLE2OBtyoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff134045a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_runtimes(multiprocessing(cpu_heavy, [N for i in range(ITERS)], 4),MULTIPROCESSING_TITLE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Resize Images\n",
    "\n",
    "* https://github.com/python-pillow/Pillow/blob/c9f54c98a5dc18685a9bf8c8822f770492a796d6/_imagingtk.c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#This one takes IO so multithreading might be better?\n",
    "def resize_img(fpath, base):\n",
    "    img = Image.open(fpath)\n",
    "    rimg = img.resize((224,224))\n",
    "    img.close()\n",
    "    return rimg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "DATA_PATH='/home/bfortuner/workplace/data/imagenet_sample/'\n",
    "fnames = list(glob.iglob(DATA_PATH+'*/*.JPEG'))\n",
    "N = 5000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Serial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 14.1 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 [resize_img(f,1) for f in fnames[:N]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multithreading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 7.57 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multithreading(resize_img, fnames[:N], 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 4.01 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multithreading(resize_img, fnames[:N], 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 3.26 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multithreading(resize_img, fnames[:N], 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 7.93 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multiprocessing(resize_img, fnames[:N], 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 5.02 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multiprocessing(resize_img, fnames[:N], 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 4.21 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 1 multiprocessing(resize_img, fnames[:N], 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}