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john9631/MITx_Cython_01b_Fibs.ipynb

Created June 23, 2017 04:33
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MITx_Cython_01b Fibs
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MITx_Cython_01b_Fibs.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import sys\n",
"\n",
"def fibr(n):\n",
" if n == 1:\n",
" return 1\n",
" elif n == 2:\n",
" return 2\n",
" else:\n",
" return fibr(n-1) + fibr(n-2)\n",
"\n",
"def fib_r_dic(n):\n",
" def fib_efficient(n, d):\n",
" if n in d:\n",
" return d[n]\n",
" else:\n",
" ans = fib_efficient(n-1, d) + fib_efficient(n-2, d)\n",
" d[n] = ans\n",
" return ans\n",
" \n",
" d = {1:1, 2:2}\n",
" return fib_efficient(n, d)\n",
"\n",
"def fib(n):\n",
" e, f = 1, 2\n",
" for i in range (3, n + 1):\n",
" e, f = f, e + f\n",
" return f\n",
"\n",
"sys.setrecursionlimit(200)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fib_r outputs: 165580141\n",
"fib_efficient outputs: 165580141\n",
"fib iterative outputs: 165580141\n",
" : 9223372036854775807\n",
"fib recursive 35.52743101119995\n",
"fib_efficient 16.6 µs ± 68.7 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n",
"fib iterative 2.05 µs ± 18.8 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
]
}
],
"source": [
"from time import time\n",
"now = time()\n",
"n = 40\n",
"\n",
"print(f\"fib_r outputs: {fibr(n)}\")\n",
"fib_r_time = time() - now\n",
"print(f\"fib_efficient outputs: {fib_r_dic(n)}\")\n",
"print(f\"fib iterative outputs: {fib(n)}\")\n",
"print(f\" : {2**63 - 1}\")\n",
"print(f\"fib recursive {fib_r_time}\")\n",
"print(f\"fib_efficient \", end='')\n",
"%timeit fib_r_dic(n)\n",
"print(f\"fib iterative \", end='')\n",
"%timeit fib(n)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2,136,500 2,697,561 8\n"
]
}
],
"source": [
"print(\"{:0,.0f} {:0,.0f} {:0,.0f}\".format(35.53/0.00001663, 5.53/0.00000205, 0.0000166/0.00000205))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"%load_ext cython"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"%%cython -a\n",
"import cython\n",
"cimport cython\n",
"\n",
"def fibc(n):\n",
" e, f = 1, 2\n",
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" e, f = f, e + f\n",
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]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fibc iterative outputs: 165580141\n",
"fibc iterative 1.21 µs ± 10.6 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)\n"
]
}
],
"source": [
"n = 40\n",
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]
},
{
"cell_type": "code",
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"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"print(\"fib iterative is {:0,.2f} faster just run in Cython\".format(2.05/1.25))"
]
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"\n",
" /* function exit code */\n",
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"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">5</span>: <span class=\"k\">cdef</span> <span class=\"kt\">long</span> <span class=\"nf\">e</span> <span class=\"o\">=</span> <span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">f</span> <span class=\"o\">=</span> <span class=\"mf\">2</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_e = 1;\n",
" __pyx_v_f = 2;\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">6</span>: <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span> <span class=\"p\">(</span><span class=\"mf\">3</span><span class=\"p\">,</span> <span class=\"n\">n</span> <span class=\"o\">+</span> <span class=\"mf\">1</span><span class=\"p\">):</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_t_1 = (__pyx_v_n + 1);\n",
" for (__pyx_t_2 = 3; __pyx_t_2 &lt; __pyx_t_1; __pyx_t_2+=1) {\n",
" __pyx_v_i = __pyx_t_2;\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">7</span>: <span class=\"n\">e</span><span class=\"p\">,</span> <span class=\"n\">f</span> <span class=\"o\">=</span> <span class=\"n\">f</span><span class=\"p\">,</span> <span class=\"n\">e</span> <span class=\"o\">+</span> <span class=\"n\">f</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_t_3 = __pyx_v_f;\n",
" __pyx_t_4 = (__pyx_v_e + __pyx_v_f);\n",
" __pyx_v_e = __pyx_t_3;\n",
" __pyx_v_f = __pyx_t_4;\n",
" }\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">8</span>: <span class=\"k\">return</span> <span class=\"n\">f</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_r = __pyx_v_f;\n",
" goto __pyx_L0;\n",
"</pre></div></body></html>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%cython -a\n",
"import cython\n",
"cimport cython\n",
"\n",
"cpdef long fibc(long n):\n",
" cdef long e = 1, f = 2\n",
" for i in range (3, n + 1):\n",
" e, f = f, e + f\n",
" return f"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fibc iterative outputs: 165580141\n",
"fibc iterative 107 ns ± 3.2 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)\n"
]
}
],
"source": [
"n = 40\n",
"print(f\"fibc iterative outputs: {fibc(n)}\")\n",
"print(f\"fibc iterative \", end='')\n",
"%timeit fibc(n)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"%%cython -c=-O3 -c=-march=native\n",
"import cython\n",
"cimport cython\n",
"\n",
"@cython.boundscheck(False)\n",
"@cython.wraparound(False)\n",
"@cython.cdivision(True)\n",
"cpdef long fibc(long n):\n",
" cdef long e = 1, f = 2\n",
" for i in range (3, n + 1):\n",
" e, f = f, e + f\n",
" return f"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fibc iterative outputs: 165580141\n",
"fibc iterative 107 ns ± 2.43 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)\n"
]
}
],
"source": [
"n = 40\n",
"print(f\"fibc iterative outputs: {fibc(n)}\")\n",
"print(f\"fibc iterative \", end='')\n",
"%timeit fibc(n)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fib iterative is 19.16 faster just run in Cython\n"
]
}
],
"source": [
"print(\"fib iterative is {:0,.2f} faster just run in Cython\".format(2.05/0.107))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"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": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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