5/benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a list of 100 integers\n",
    "r = [random.randrange(100) for _ in range(100000)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 1000\n",
    "x, y = random.sample(r, n), random.sample(r, n)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 loops, best of 3: 117 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "i, z = 0, []\n",
    "while i < n:\n",
    "    z.append(x[i] + y[i])\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 loops, best of 3: 86.2 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = []\n",
    "for i in range(n):\n",
    "    z.append(x[i] + y[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 loops, best of 3: 61.7 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = [x[i] + y[i] for i in range(n)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_arr = np.array(x)\n",
    "y_arr = np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 56.99 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "1000000 loops, best of 3: 784 ns per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = x_arr + y_arr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nested Loops\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "m, n = 100, 1000\n",
    "x = [random.sample(r, n) for _ in range(m)]\n",
    "y = [random.sample(r, n) for _ in range(m)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 13.5 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "i, z = 0, []\n",
    "while i < m:\n",
    "    j, z_ = 0, []\n",
    "    while j < n:\n",
    "        z_.append(x[i][j] + y[i][j])\n",
    "        j += 1\n",
    "    z.append(z_)\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 10.6 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = []\n",
    "for i in range(m):\n",
    "    z_ = []\n",
    "    for j in range(n):\n",
    "         z_.append(x[i][j] + y[i][j])\n",
    "    z.append(z_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 8.13 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = [[x[i][j] + y[i][j] for j in range(n)] for i in range(m)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_arr, y_arr = np.array(x, dtype=np.int64), np.array(y, dtype=np.int64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 11.28 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "10000 loops, best of 3: 46 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "z = x_arr + y_arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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