Comparação dos loops do asyncio e do uvloop no cPython 3.10 e PyPy 3.9-7.3.9

analise.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Loop de Eventos\n",
    "\n",
    "Comparação dos loops do asyncio e do uvloop no cPython 3.10 e PyPy 3.9\\-7.3.9.\n",
    "\n",
    "_Obs:_ instalação do uvloop no pypy apresentou problemas e não foi possível executar essa combinação.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "dados <- read.csv('dados.csv', colClasses=c('factor', 'factor', 'numeric', 'integer'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Tempo de Execução"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “Tempos de Execução”"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boxplot(\n",
    "    tempo ~ python + loop,\n",
    "    dados,\n",
    "    main = 'Tempos de Execução',\n",
    "    xlab = '',\n",
    "    ylab = 'Tempo de Execução (em segundos)',\n",
    "    col = '#8ebed3'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value Pr(>F)    \n",
       "python       1 1004.9  1004.9   53148 <2e-16 ***\n",
       "loop         1  774.1   774.1   40944 <2e-16 ***\n",
       "Residuals   72    1.4     0.0                   \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "execution_count": 3,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(dados.aov_tempo <- aov(tempo ~ python + loop, dados))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “95% family-wise confidence level\n",
       "”"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “95% family-wise confidence level\n",
       "”"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(TukeyHSD(dados.aov_tempo))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Uso de Memória"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “Memória Usada”"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boxplot(\n",
    "    memoria / 1024 ~ python + loop,\n",
    "    dados,\n",
    "    main = 'Memória Usada',\n",
    "    xlab = '',\n",
    "    ylab = 'Total de Memória (em MB)',\n",
    "    col = '#8ebed3'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df    Sum Sq   Mean Sq F value Pr(>F)    \n",
       "python       1 7.814e+10 7.814e+10 3077238 <2e-16 ***\n",
       "loop         1 4.722e+07 4.722e+07    1859 <2e-16 ***\n",
       "Residuals   72 1.828e+06 2.539e+04                   \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "execution_count": 6,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(dados.aov_memoria <- aov(memoria ~ python + loop, dados))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “95% family-wise confidence level\n",
       "”"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Plot with title “95% family-wise confidence level\n",
       "”"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(TukeyHSD(dados.aov_memoria))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R (system-wide)",
   "language": "r",
   "metadata": {
    "cocalc": {
     "description": "R statistical programming language",
     "priority": 10,
     "url": "https://www.r-project.org/"
    }
   },
   "name": "ir",
   "resource_dir": "/ext/jupyter/kernels/ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.2.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}

dados.csv

programa.py

import asyncio

async def funcao(iteracoes):
    a = 0
    for _ in range(iteracoes):
        a += await asyncio.sleep(0, result=2)
    return a


async def main(numero_tasks, iteracoes):
    tasks = [asyncio.create_task(funcao(iteracoes)) for _ in range(numero_tasks)]
    for task in tasks:
        await task


if __name__ == '__main__':
    import sys

    if sys.argv[1] == 'uvloop':
        import uvloop
        asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())

    asyncio.run(main(10, 500_000))

run.sh

#!/bin/bash

EXECUCOES=25

(
echo 'python,loop,tempo,memoria'
for e in $(seq 1 "$EXECUCOES"); do
    for p in cpython pypy; do
        for l in asyncio uvloop; do
            if [ "$p" = "pypy" ] && [ "$l" = "uvloop" ]; then
                continue
            fi
            /usr/bin/time -f "$p,$l,%e,%M" ./env-"$p"/bin/python programa.py "$l"
        done
    done
done
) |& tee dados.csv
gzip -9 dados.csv