{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Multi processing\n\nThis is a modified example from the python documentation.\nThe only difference is the ``set_executable`` section at the start.\nPlease notice that you cannot use methods from the itom module\nin any worker thread.\nAlternative approaches for multiprocessing are \npython ``threading`` module and ``asyncio``. Or use ``subprocess``.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from multiprocessing import Pool, TimeoutError\nimport multiprocessing\nimport time\nimport os"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Demo function for parallelization. \n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def func(x):\n    print(\"return x*x with x = \", x)\n    return x * x"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Python executable is required \n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "pythonPath = ui.getOpenFileName(\n    \"Set path of python.exe\",\n    \"C:/itom/3rdParty/Python/python.exe\",\n    \"Python Executable (*.exe)\",\n)\n\nif pythonPath and os.path.exists(pythonPath):\n    # set the path of the python executable (embedded python is required)\n    multiprocessing.set_executable(pythonPath)\n\n    with Pool(processes=4) as pool:\n\n        # print \"[0, 1, 4,..., 81]\"\n        print(pool.map(func, range(10)))\n\n        # print same numbers in arbitrary order\n        for i in pool.imap_unordered(func, range(10)):\n            print(i)\n\n        # evaluate \"f(20)\" asynchronously\n        res = pool.apply_async(func, (20,))  # runs in *only* one process\n        print(res.get(timeout=1))  # prints \"400\"\n\n        # evaluate \"os.getpid()\" asynchronously\n        res = pool.apply_async(os.getpid, ())  # runs in *only* one process\n        print(res.get(timeout=1))  # prints the PID of that process\n\n        # launching multiple evaluations asynchronously *may* use more processes\n        multiple_results = [pool.apply_async(os.getpid, ()) for i in range(4)]\n        print([res.get(timeout=1) for res in multiple_results])\n\n        # make a single worker sleep for 10 secs\n        res = pool.apply_async(time.sleep, (10,))\n        try:\n            print(res.get(timeout=1))\n        except TimeoutError:\n            print(\"We lacked patience and got a multiprocessing.TimeoutError\")\n\n        print(\"For the moment, the pool remains available for more work\")\n\n    # exiting the 'with'-block has stopped the pool\n    print(\"Now the pool is closed and no longer available\")"
      ]
    }
  ],
  "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": "3.8.10"
    }
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  "nbformat": 4,
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