1_batch_plotting_multicore.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Plotting multicore\n",
    "\n",
    "First of all we want to make use of all the cores in our machine, `concurrent.futures` from the Python 3.5 standard library provides a simple interface to use a pool of processes. Timing should be about half if we are using 2 workers on a 2 cores machine."
   ]
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   "cell_type": "code",
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   "metadata": {},
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   "source": [
    "import analyze_inflammation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob"
   ]
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "filenames = glob.glob(\"inflammation-*.csv\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import concurrent.futures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "executor = concurrent.futures.ProcessPoolExecutor()"
   ]
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   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "executor._max_workers"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 11.7 ms, sys: 15.4 ms, total: 27.1 ms\n",
      "Wall time: 852 ms\n"
     ]
    },
    {
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "list(executor.map(analyze_inflammation.analyze, filenames))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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