object serialization for beanstalkc

serialization_speeds

{
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  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Speed Tests for Object Serialization"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pickle\n",
      "import cPickle\n",
      "import json\n",
      "\n",
      "import yaml\n",
      "import beanstalkc\n",
      "import umsgpack\n",
      "\n",
      "from uuid import uuid4\n",
      "\n",
      "from yaml import (CLoader, CDumper)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "`beanstalkc` by default uses `PyYAML` to turn strings into Python objects. `beanstalkd` allows to transmit only strings. So we have a couple of options to serialize Python objects to strings and back again. Consider that both `pickle` (through `cPickle`) and `yaml` (via `libyaml`) have `C` versions and that `JSON` is limited to basic types."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "First start a local `beanstalkd` queue:\n",
      "\n",
      "    beanstalkd -l localhost\n",
      "    \n",
      "or adjust the arguments to match in the following."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "queue = beanstalkc.Connection(host=\"127.0.0.1\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lib_q = beanstalkc.Connection(host=\"127.0.0.1\", parse_yaml=CLoader)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pure input/output using PyYAML with and without libyaml does not affect speed since the transmitted strings are not touched."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "content = \"\"\"\n",
      "- This\n",
      "- is\n",
      "- a\n",
      "- yaml\n",
      "- list\n",
      "\"\"\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "queue.put(content)\n",
      "job = queue.reserve()\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 73.9 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "lib_q.put(content)\n",
      "job = lib_q.reserve()\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 75.1 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Getting information from `beanstalkd`, however, is sped up quite a bit."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit queue.stats()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100 loops, best of 3: 6.32 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit lib_q.stats()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 64.1 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A larger job that needs to be transformed to a string."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "unique_id = str(uuid4())\n",
      "unique_id"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "'caadbd6d-9155-4809-a639-6070f0a72b53'"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "job_desc = {\n",
      "            \"name\": \"fitzroy\",\n",
      "            \"id\": unique_id,\n",
      "            \"discrete\": 2435466673,\n",
      "            \"real\": 34.23552,\n",
      "            \"tuple\": (43, 34),\n",
      "            \"dict\": {\"yes\": True, \"no\": False, \"I don't know\": None},\n",
      "            \"list\": [4, 2, None, (True, False), [234.2534, \"yay\"]]\n",
      "            }"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`pickle`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p_dump = pickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL)\n",
      "queue.put(p_dump)\n",
      "job = queue.reserve()\n",
      "p_load = pickle.loads(job.body)\n",
      "job.delete()\n",
      "p_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "{'dict': {\"I don't know\": None, 'no': False, 'yes': True},\n",
        " 'discrete': 2435466673,\n",
        " 'id': 'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " 'list': [4, 2, None, (True, False), [234.2534, 'yay']],\n",
        " 'name': 'fitzroy',\n",
        " 'real': 34.23552,\n",
        " 'tuple': (43, 34)}"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(p_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "219"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit pickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 74.1 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit pickle.loads(p_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 38.7 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit \n",
      "queue.put(pickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL))\n",
      "job = queue.reserve()\n",
      "p_load = pickle.loads(job.body)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 233 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`cPickle`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cp_dump = cPickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL)\n",
      "queue.put(cp_dump)\n",
      "job = queue.reserve()\n",
      "cp_load = cPickle.loads(job.body)\n",
      "job.delete()\n",
      "cp_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "{'dict': {\"I don't know\": None, 'no': False, 'yes': True},\n",
        " 'discrete': 2435466673,\n",
        " 'id': 'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " 'list': [4, 2, None, (True, False), [234.2534, 'yay']],\n",
        " 'name': 'fitzroy',\n",
        " 'real': 34.23552,\n",
        " 'tuple': (43, 34)}"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(cp_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "211"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit cPickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100000 loops, best of 3: 3.55 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit cPickle.loads(cp_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100000 loops, best of 3: 3.14 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit \n",
      "queue.put(cPickle.dumps(job_desc, protocol=pickle.HIGHEST_PROTOCOL))\n",
      "job = queue.reserve()\n",
      "cp_load = cPickle.loads(job.body)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 160 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`json`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "j_dump = json.dumps(job_desc)\n",
      "queue.put(j_dump)\n",
      "job = queue.reserve()\n",
      "j_load = json.loads(job.body)\n",
      "job.delete()\n",
      "j_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "{u'dict': {u\"I don't know\": None, u'no': False, u'yes': True},\n",
        " u'discrete': 2435466673,\n",
        " u'id': u'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " u'list': [4, 2, None, [True, False], [234.2534, u'yay']],\n",
        " u'name': u'fitzroy',\n",
        " u'real': 34.23552,\n",
        " u'tuple': [43, 34]}"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(j_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "240"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit json.dumps(job_desc)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100000 loops, best of 3: 8.44 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit json.loads(j_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100000 loops, best of 3: 9.69 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit \n",
      "queue.put(json.dumps(job_desc))\n",
      "job = queue.reserve()\n",
      "j_load = json.loads(job.body)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 231 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`umsgpack`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "u_dump = umsgpack.dumps(job_desc)\n",
      "queue.put(u_dump)\n",
      "job = queue.reserve()\n",
      "u_load = umsgpack.loads(job.body)\n",
      "job.delete()\n",
      "u_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "{'dict': {\"I don't know\": None, 'no': False, 'yes': True},\n",
        " 'discrete': 2435466673,\n",
        " 'id': 'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " 'list': [4, 2, None, [True, False], [234.2534, 'yay']],\n",
        " 'name': 'fitzroy',\n",
        " 'real': 34.23552,\n",
        " 'tuple': [43, 34]}"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(u_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "159"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit umsgpack.dumps(job_desc)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 42.7 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit umsgpack.loads(u_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 51.1 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit \n",
      "queue.put(umsgpack.dumps(job_desc))\n",
      "job = queue.reserve()\n",
      "u_load = umsgpack.loads(job.body)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 178 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`yaml` (without `libyaml`)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "y_dump = yaml.dump(job_desc)\n",
      "queue.put(y_dump)\n",
      "job = queue.reserve()\n",
      "y_load = yaml.load(job.body)\n",
      "job.delete()\n",
      "y_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "{'dict': {\"I don't know\": None, 'no': False, 'yes': True},\n",
        " 'discrete': 2435466673,\n",
        " 'id': 'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " 'list': [4, 2, None, (True, False), [234.2534, 'yay']],\n",
        " 'name': 'fitzroy',\n",
        " 'real': 34.23552,\n",
        " 'tuple': (43, 34)}"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(y_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "245"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit yaml.dump(job_desc)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 1.13 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit yaml.load(y_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100 loops, best of 3: 1.95 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "queue.put(yaml.dump(job_desc))\n",
      "job = queue.reserve()\n",
      "y_load = yaml.load(job.body)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100 loops, best of 3: 3.48 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "`yaml` (with `libyaml`)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cy_dump = yaml.dump(job_desc, Dumper=CDumper)\n",
      "queue.put(cy_dump)\n",
      "job = queue.reserve()\n",
      "cy_load = yaml.load(job.body, Loader=CLoader)\n",
      "job.delete()\n",
      "cy_load"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "{'dict': {\"I don't know\": None, 'no': False, 'yes': True},\n",
        " 'discrete': 2435466673,\n",
        " 'id': 'caadbd6d-9155-4809-a639-6070f0a72b53',\n",
        " 'list': [4, 2, None, (True, False), [234.2534, 'yay']],\n",
        " 'name': 'fitzroy',\n",
        " 'real': 34.23552,\n",
        " 'tuple': (43, 34)}"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(cy_dump)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "245"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit yaml.dump(job_desc, Dumper=CDumper)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 315 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit yaml.load(job.body, Loader=CLoader)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 284 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "queue.put(yaml.dump(job_desc, Dumper=CDumper))\n",
      "job = queue.reserve()\n",
      "cy_load = yaml.load(job.body, Loader=CLoader)\n",
      "job.delete()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000 loops, best of 3: 997 \u00b5s per loop\n"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Conclusion"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Speed-wise, `cPickle` seems the clear winner with `JSON` surprisingly as a close second. `cPickle` also allows serialization of any kind of Python object unlike `JSON`. Size-wise `umsgpack` wins but due to its pure Python implementation (as of today) it cannot compete in speed."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}