mirror of
https://github.com/rasbt/python_reference.git
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623 lines
20 KiB
Plaintext
623 lines
20 KiB
Plaintext
{
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"metadata": {
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"name": "",
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"signature": "sha256:0e619f8592165b10fa0b3558de3c622629bfb7aab1e9544b5bad64478cf35848"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Sebastian Raschka](http://sebastianraschka.com) \n",
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"last updated: 06/12/2014"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<hr>\n",
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"I would be happy to hear your comments and suggestions. \n",
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"Please feel free to drop me a note via\n",
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"[twitter](https://twitter.com/rasbt), [email](mailto:bluewoodtree@gmail.com), or [google+](https://plus.google.com/118404394130788869227).\n",
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"<hr>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<a name=\"sections\"></a>\n",
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"<br>\n",
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"<br>\n"
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]
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},
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"Using Cython with and without IPython magic"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<a name=\"introduction\"></a>\n",
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"<br>\n",
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"<br>"
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]
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},
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{
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"cell_type": "heading",
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"level": 3,
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"metadata": {},
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"source": [
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"Bubblesort in regular (C)Python"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we will write a simple implementation of the bubble sort algorithm in regular (C)Python"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"def python_bubblesort(a_list):\n",
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" \"\"\" Bubblesort in Python for list objects. \"\"\"\n",
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" length = len(a_list)\n",
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" swapped = 1\n",
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" for i in range(0, length):\n",
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" if swapped: \n",
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" swapped = 0\n",
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" for ele in range(0, length-i-1):\n",
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" if a_list[ele] > a_list[ele + 1]:\n",
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" temp = a_list[ele + 1]\n",
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" a_list[ele + 1] = a_list[ele]\n",
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" a_list[ele] = temp\n",
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" swapped = 1\n",
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" return a_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 1
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"python_bubblesort([6,3,1,5,6])"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 2,
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"text": [
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"[1, 3, 5, 6, 6]"
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]
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}
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],
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"prompt_number": 2
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Implemented in Cython"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Maybe we can speed things up a little bit via [Cython's C-extensions for Python](http://cython.org). Cython is basically a hybrid between C and Python and can be pictured as compiled Python code with type declarations. \n",
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"Since we are working in an IPython notebook here, we can make use of the very convenient *IPython magic*: It will take care of the conversion to C code, the compilation, and eventually the loading of the function. "
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%load_ext cythonmagic"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 3
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we will take the initial Python code as is and use Cython for the compilation. Cython is capable of autoguessing types, however, we can make our code way more efficient by adding static types."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%%cython\n",
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"def cython_bubblesort_untyped(a_list):\n",
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" \"\"\" Bubblesort in Python for list objects. \"\"\"\n",
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" length = len(a_list)\n",
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" swapped = 1\n",
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" for i in range(0, length):\n",
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" if swapped: \n",
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" swapped = 0\n",
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" for ele in range(0, length-i-1):\n",
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" if a_list[ele] > a_list[ele + 1]:\n",
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" temp = a_list[ele + 1]\n",
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" a_list[ele + 1] = a_list[ele]\n",
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" a_list[ele] = temp\n",
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" swapped = 1\n",
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" return a_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 4
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%%cython\n",
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"import numpy as np\n",
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"cimport numpy as np\n",
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"cimport cython\n",
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"@cython.boundscheck(False) \n",
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"@cython.wraparound(False)\n",
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"cpdef cython_bubblesort_typed(inp_ary):\n",
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" \"\"\" The Cython implementation of Bubblesort with NumPy memoryview.\"\"\"\n",
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" cdef unsigned long length, i, swapped, ele, temp\n",
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" cdef long[:] np_ary = inp_ary\n",
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" length = np_ary.shape[0]\n",
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" swapped = 1\n",
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" for i in xrange(0, length):\n",
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" if swapped: \n",
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" swapped = 0\n",
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" for ele in xrange(0, length-i-1):\n",
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" if np_ary[ele] > np_ary[ele + 1]:\n",
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" temp = np_ary[ele + 1]\n",
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" np_ary[ele + 1] = np_ary[ele]\n",
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" np_ary[ele] = temp\n",
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" swapped = 1\n",
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" return inp_ary"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 5
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Speed comparison"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Below, we will do a quick speed comparison of our 3 implementations of the bubble sort algorithm by sorting a list (or numpy array) of 1000 random digits. Here, we have to make copies of the lists/numpy arrays, since our bubble sort implementation is sorting in place."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import random\n",
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"import numpy as np\n",
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"import copy\n",
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"\n",
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"list_a = [random.randint(0,1000) for num in range(1000)]\n",
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"list_b = copy.deepcopy(a_list)\n",
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"\n",
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"ary_a = np.asarray(list_a)\n",
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"ary_b = copy.deepcopy(ary_a)\n",
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"ary_c = copy.deepcopy(ary_a)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 11
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"print('\\n(C)Python on list:')\n",
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"%timeit python_bubblesort(list_a)\n",
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"\n",
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"print('\\n(C)Python on numpy array:')\n",
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"%timeit python_bubblesort(ary_a)\n",
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"\n",
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"print('\\nuntyped Cython on list:')\n",
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"%timeit cython_bubblesort_untyped(list_b)\n",
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"\n",
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"print('\\nuntyped Cython on numpy array:')\n",
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"%timeit cython_bubblesort_untyped(ary_b)\n",
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"\n",
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"print('\\ntyped Cython with memoryview on numpy array:')\n",
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"%timeit cython_bubblesort_typed(ary_c)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"\n",
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"(C)Python on list:\n",
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"1 loops, best of 3: 332 \u00b5s per loop"
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]
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},
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"\n",
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"\n",
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"(C)Python on numpy array:\n",
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"1 loops, best of 3: 839 \u00b5s per loop"
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]
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},
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"\n",
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"\n",
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"untyped Cython on list:\n",
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"10000 loops, best of 3: 183 \u00b5s per loop"
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]
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},
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"\n",
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"\n",
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"untyped Cython on numpy array:\n",
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"1 loops, best of 3: 666 \u00b5s per loop"
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]
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},
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"\n",
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"\n",
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"typed Cython with memoryview on numpy array:\n",
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"100000 loops, best of 3: 4.05 \u00b5s per loop"
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]
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},
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|
{
|
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"output_type": "stream",
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"stream": "stdout",
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"text": [
|
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"\n"
|
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]
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}
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],
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"prompt_number": 12
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<br>\n",
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"<br>\n",
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"As we can see from the results above, we are already able to make our Python code run almost as twice as fast if we compile it via Cython (Python on list: 332 \u00b5s, untyped Cython on list: 183 \u00b5s). \n",
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"However, although it is more \"work\" to adjust the Python code, the \"typed Cython with memoryview on numpy array\" is significantly as expected."
|
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"<a name=\"cython_bonus\"></a>\n",
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"<br>\n",
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"<br>"
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]
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},
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"How to use Cython without the IPython magic"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[[back to top](#sections)]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"IPython's notebook is really great for explanatory analysis and documentation, but what if we want to compile our Python code via Cython without letting IPython's magic doing all the work? \n",
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"These are the steps you would need."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<br>\n",
|
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"<br>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 1. Creating a .pyx file containing the the desired code or function."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%%file cython_bubblesort_nomagic.pyx\n",
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"\n",
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"cpdef cython_bubblesort_nomagic(inp_ary):\n",
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" \"\"\" The Cython implementation of Bubblesort with NumPy memoryview.\"\"\"\n",
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" cdef unsigned long length, i, swapped, ele, temp\n",
|
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" cdef long[:] np_ary = inp_ary\n",
|
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" length = np_ary.shape[0]\n",
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" swapped = 1\n",
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" for i in xrange(0, length):\n",
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" if swapped: \n",
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" swapped = 0\n",
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" for ele in xrange(0, length-i-1):\n",
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" if np_ary[ele] > np_ary[ele + 1]:\n",
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" temp = np_ary[ele + 1]\n",
|
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" np_ary[ele + 1] = np_ary[ele]\n",
|
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" np_ary[ele] = temp\n",
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" swapped = 1\n",
|
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" return inp_ary"
|
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],
|
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"language": "python",
|
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"metadata": {},
|
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"outputs": [
|
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
|
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"Overwriting cython_bubblesort_nomagic.pyx\n"
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]
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}
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],
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"prompt_number": 16
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<br>\n",
|
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"<br>"
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]
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},
|
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"#### 2. Creating a simple setup file"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%%file setup.py\n",
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"\n",
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"from distutils.core import setup\n",
|
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"from distutils.extension import Extension\n",
|
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"from Cython.Distutils import build_ext\n",
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"\n",
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"setup(\n",
|
|
" cmdclass = {'build_ext': build_ext},\n",
|
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" ext_modules = [Extension(\"cython_bubblesort_nomagic\", [\"cython_bubblesort_nomagic.pyx\"])]\n",
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")"
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],
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"language": "python",
|
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"metadata": {},
|
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"outputs": [
|
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{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
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"text": [
|
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"Overwriting setup.py\n"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 17
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|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"<br>\n",
|
|
"<br>\n"
|
|
]
|
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},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
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"####3. Building and Compiling"
|
|
]
|
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},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"!python3 setup.py build_ext --inplace"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"running build_ext\r\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"cythoning cython_bubblesort_nomagic.pyx to cython_bubblesort_nomagic.c\r\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"building 'cython_bubblesort_nomagic' extension\r\n",
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|
"/usr/bin/clang -fno-strict-aliasing -Werror=declaration-after-statement -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/sebastian/miniconda3/envs/py34/include -arch x86_64 -I/Users/sebastian/miniconda3/envs/py34/include/python3.4m -c cython_bubblesort_nomagic.c -o build/temp.macosx-10.5-x86_64-3.4/cython_bubblesort_nomagic.o\r\n"
|
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]
|
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},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\u001b[1mcython_bubblesort_nomagic.c:16276:32: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_PyUnicode_FromString' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(char* c_str) {\r\n",
|
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:16427:33: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_PyInt_FromSize_t' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {\r\n",
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"\u001b[0;1;32m ^\r\n",
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14058:26: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_GetBufferAndValidate' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE int __Pyx_GetBufferAndValidate(\r\n",
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14092:27: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_SafeReleaseBuffer' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {\r\n",
|
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14165:1: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__pyx_add_acquisition_count_locked' [-Wunused-function]\u001b[0m\r\n",
|
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"__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,\r\n",
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"\u001b[0;1;32m^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14175:1: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__pyx_sub_acquisition_count_locked' [-Wunused-function]\u001b[0m\r\n",
|
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"__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,\r\n",
|
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"\u001b[0;1;32m^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14643:26: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_PyBytes_Equals' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2...\r\n",
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"\u001b[0;1;32m ^\r\n",
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14920:32: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_GetItemInt_List_Fast' [-Wunused-function]\u001b[0m\r\n"
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]
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},
|
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{
|
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"output_type": "stream",
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"stream": "stdout",
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"text": [
|
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"static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, P...\r\n",
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"\u001b[0;1;32m ^\r\n",
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:14934:32: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_GetItemInt_Tuple_Fast' [-Wunused-function]\u001b[0m\r\n",
|
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"static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, ...\r\n",
|
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"\u001b[0;1;32m ^\r\n",
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:15111:38: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1munused function\r\n",
|
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" '__Pyx_PyInt_From_unsigned_long' [-Wunused-function]\u001b[0m\r\n",
|
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" static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_long(unsi...\r\n",
|
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:15158:36: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1mfunction\r\n",
|
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" '__Pyx_PyInt_As_unsigned_long' is not needed and will not be emitted\r\n",
|
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" [-Wunneeded-internal-declaration]\u001b[0m\r\n",
|
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"static CYTHON_INLINE unsigned long __Pyx_PyInt_As_unsigned_long(PyObject *x) {\r\n",
|
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:15627:27: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1mfunction '__Pyx_PyInt_As_char' is\r\n",
|
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" not needed and will not be emitted [-Wunneeded-internal-declaration]\u001b[0m\r\n",
|
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"static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {\r\n",
|
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"\u001b[0;1;32m ^\r\n",
|
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"\u001b[0m\u001b[1mcython_bubblesort_nomagic.c:15727:27: \u001b[0m\u001b[0;1;35mwarning: \u001b[0m\u001b[1mfunction '__Pyx_PyInt_As_long' is\r\n",
|
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" not needed and will not be emitted [-Wunneeded-internal-declaration]\u001b[0m\r\n",
|
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"static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {\r\n",
|
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"\u001b[0;1;32m ^\r\n",
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"\u001b[0m"
|
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]
|
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},
|
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{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
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"text": [
|
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"13 warnings generated.\r\n",
|
|
"/usr/bin/clang -bundle -undefined dynamic_lookup -L/Users/sebastian/miniconda3/envs/py34/lib -arch x86_64 build/temp.macosx-10.5-x86_64-3.4/cython_bubblesort_nomagic.o -L/Users/sebastian/miniconda3/envs/py34/lib -o /Users/sebastian/Desktop/cython_bubblesort_nomagic.so\r\n"
|
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]
|
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}
|
|
],
|
|
"prompt_number": 18
|
|
},
|
|
{
|
|
"cell_type": "markdown",
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|
"metadata": {},
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|
"source": [
|
|
"#### 4. Importing and running the code"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"import cython_bubblesort_nomagic\n",
|
|
"\n",
|
|
"cython_bubblesort_nomagic.cython_bubblesort_nomagic(np.array([4,6,2,1,6]))"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 20,
|
|
"text": [
|
|
"array([1, 2, 4, 6, 6])"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 20
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"<a name=\"numba\"></a>\n",
|
|
"<br>\n",
|
|
"<br>"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {}
|
|
}
|
|
]
|
|
} |