ParallelExample.ipynb

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    "# Parallel processing example\n",
    "\n",
    "This notebook accompanies [this blog post][1], and includes an example of parallel code created with the `multiprocessing` module.\n",
    "\n",
    "First import the required functions from the standard library:\n",
    "\n",
    "[1]: https://mindriot101.github.io/blog/2017/01/10/python-parallelism-cheat-sheet/"
   ]
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   "source": [
    "# Bake in constant arguments to a function\n",
    "from functools import partial\n",
    "\n",
    "# Package for running code in parallel \n",
    "from multiprocessing import Pool"
   ]
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   "source": [
    "Then we define our \"worker\" function, which performs the work of a single loop iteration."
   ]
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    "def worker_fn(changing_stuff, const_value):\n",
    "    '''A function that takes as it's first parameter\n",
    "    the values that change for each loop iteration, and\n",
    "    the remaining parameters do not change with each\n",
    "    loop iteration\n",
    "    '''\n",
    "    a, b = changing_stuff\n",
    "    return (a + b) * const_value"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up an example problem to work with"
   ]
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   "source": [
    "avalues = range(20)\n",
    "bvalues = range(100, 120)\n",
    "const = 100"
   ]
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   "source": [
    "\"Bake in\" our constant arguments to create our partially applied function, which takes a single parameter."
   ]
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    "fn = partial(worker_fn, const_value=const)"
   ]
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   "cell_type": "markdown",
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    "Create an iterable of everything that changes for every loop iteration"
   ]
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   "source": [
    "# this must be an `iterable`, so a list or generator\n",
    "zipped_args = zip(avalues, bvalues)"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally run the code in parallel, using all of the processors on the machine"
   ]
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   "source": [
    "# Python 3\n",
    "with Pool() as pool:  # 3\n",
    "    results = pool.map(fn, zipped_args)  # 4\n",
    "\n",
    "# or if you're stuck with Python 2:\n",
    "# pool = Pool()\n",
    "# results = pool.map(fn, zipped_args)  # 4"
   ]
  }
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