08-extension-types.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extension Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Cython extension is already loaded. To reload it, use:\n",
      "  %reload_ext Cython\n"
     ]
    }
   ],
   "source": [
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Number generation\n",
    "\n",
    "We will implement one of the simplest, the [linear congruential generator (LCG)](https://en.wikipedia.org/wiki/Linear_congruential_generator):\n",
    "\n",
    "$$X_{n+1} = (aX_n + c)\\mod m$$\n",
    "\n",
    "We'll use $a=1664525$, $c=1013904223$, and $m=2^{32}$.\n",
    "\n",
    "*Caveat emptor*: Don't use these simple RNGs for anything real, especially with [much better implementations](https://docs.scipy.org/doc/numpy/reference/routines.random.html) so readily available."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pure Python version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class PyLCG(object):\n",
    "    \n",
    "    def __init__(self, a=1664525, c=1013904223, m=2**32, seed=0):\n",
    "        self.a = a\n",
    "        self.c = c\n",
    "        if m <= 0:\n",
    "            raise ValueError(\"m must be > 0, given {}\".format(m))\n",
    "        self.m = m\n",
    "        self.x = seed\n",
    "        \n",
    "    def _advance(self):\n",
    "        r = self.x\n",
    "        self.x = (self.a * self.x + self.c) % self.m\n",
    "        return r\n",
    "        \n",
    "    def randint(self, size=None):\n",
    "        if size is None:\n",
    "            return self._advance()\n",
    "        return np.asarray([self._advance() for _ in range(size)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tests and timing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56aa6d58d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = PyLCG()\n",
    "nums = rng.randint(size=10000) % 100\n",
    "sns.distplot(nums, bins=100, kde=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6.44 ms ± 102 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit rng = PyLCG()\n",
    "nums = rng.randint(size=10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cython version, extension types, and `cdef class`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div class=\"cython\"><pre class=\"cython line score-0\">&#xA0;<span class=\"\">01</span>: </pre>\n",
       "<pre class=\"cython line score-19\" onclick='toggleDiv(this)'>+<span class=\"\">02</span>: <span class=\"k\">import</span> <span class=\"nn\">numpy</span> <span class=\"k\">as</span> <span class=\"nn\">np</span></pre>\n",
       "<pre class='cython code score-19 '>  __pyx_t_1 = <span class='pyx_c_api'>__Pyx_Import</span>(__pyx_n_s_numpy, 0, 0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 2, __pyx_L1_error)\n",
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       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">03</span>: <span class=\"k\">cimport</span> <span class=\"nn\">numpy</span> <span class=\"k\">as</span> <span class=\"nn\">cnp</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">04</span>: <span class=\"k\">cimport</span> <span class=\"nn\">cython</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">05</span>: </pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">06</span>: <span class=\"c\"># Creates a new extension type: https://docs.python.org/3/extending/newtypes.html</span></pre>\n",
       "<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">07</span>: <span class=\"k\">cdef</span> <span class=\"k\">class</span> <span class=\"nf\">CyLCG</span><span class=\"p\">:</span></pre>\n",
       "<pre class='cython code score-0 '>struct __pyx_obj_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG {\n",
       "  PyObject_HEAD\n",
       "  struct __pyx_vtabstruct_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG *__pyx_vtab;\n",
       "  long a;\n",
       "  long c;\n",
       "  long m;\n",
       "  long x;\n",
       "};\n",
       "/* … */\n",
       "struct __pyx_vtabstruct_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG {\n",
       "  long (*_advance)(struct __pyx_obj_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG *, int __pyx_skip_dispatch);\n",
       "};\n",
       "static struct __pyx_vtabstruct_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG *__pyx_vtabptr_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_CyLCG;\n",
       "\n",
       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">08</span>: </pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">09</span>:     <span class=\"c\"># We declare the compile-time types of our *instance* attributes here.</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">10</span>:     <span class=\"c\"># This is similar to C++ class declaration syntax.</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">11</span>:     <span class=\"k\">cdef</span> <span class=\"kt\">long</span> <span class=\"nf\">a</span><span class=\"p\">,</span> <span class=\"nf\">c</span><span class=\"p\">,</span> <span class=\"nf\">m</span><span class=\"p\">,</span> <span class=\"nf\">x</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">12</span>: </pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">13</span>:     <span class=\"c\"># Special Cython-defined initializer.</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">14</span>:     <span class=\"c\"># Called before __init__ to initialize all C-level attributes.</span></pre>\n",
       "<pre class=\"cython line score-77\" onclick='toggleDiv(this)'>+<span class=\"\">15</span>:     <span class=\"k\">def</span> <span class=\"nf\">__cinit__</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"nb\">long</span> <span class=\"n\">a</span><span class=\"o\">=</span><span class=\"mf\">1664525</span><span class=\"p\">,</span> <span class=\"nb\">long</span> <span class=\"n\">c</span><span class=\"o\">=</span><span class=\"mf\">1013904223</span><span class=\"p\">,</span> <span class=\"nb\">long</span> <span class=\"n\">m</span><span class=\"o\">=</span><span class=\"mf\">2</span><span class=\"o\">**</span><span class=\"mf\">32</span><span class=\"p\">,</span> <span class=\"nb\">long</span> <span class=\"n\">seed</span><span class=\"o\">=</span><span class=\"mf\">0</span><span class=\"p\">):</span></pre>\n",
       "<pre class='cython code score-77 '>/* Python wrapper */\n",
       "static int __pyx_pw_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_5CyLCG_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/\n",
       "static int __pyx_pw_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_5CyLCG_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n",
       "  long __pyx_v_a;\n",
       "  long __pyx_v_c;\n",
       "  long __pyx_v_m;\n",
       "  long __pyx_v_seed;\n",
       "  int __pyx_r;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"__cinit__ (wrapper)\", 0);\n",
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       "    PyObject* values[4] = {0,0,0,0};\n",
       "    if (unlikely(__pyx_kwds)) {\n",
       "      Py_ssize_t kw_args;\n",
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       "      switch (pos_args) {\n",
       "        case  4: values[3] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 3);\n",
       "        case  3: values[2] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 2);\n",
       "        case  2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n",
       "        case  1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n",
       "        case  0: break;\n",
       "        default: goto __pyx_L5_argtuple_error;\n",
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       "      kw_args = <span class='py_c_api'>PyDict_Size</span>(__pyx_kwds);\n",
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       "          PyObject* value = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_a);\n",
       "          if (value) { values[0] = value; kw_args--; }\n",
       "        }\n",
       "        case  1:\n",
       "        if (kw_args &gt; 0) {\n",
       "          PyObject* value = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_c);\n",
       "          if (value) { values[1] = value; kw_args--; }\n",
       "        }\n",
       "        case  2:\n",
       "        if (kw_args &gt; 0) {\n",
       "          PyObject* value = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_m);\n",
       "          if (value) { values[2] = value; kw_args--; }\n",
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       "          PyObject* value = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_seed);\n",
       "          if (value) { values[3] = value; kw_args--; }\n",
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       "      if (unlikely(kw_args &gt; 0)) {\n",
       "        if (unlikely(<span class='pyx_c_api'>__Pyx_ParseOptionalKeywords</span>(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, \"__cinit__\") &lt; 0)) __PYX_ERR(0, 15, __pyx_L3_error)\n",
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       "        case  2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n",
       "        case  1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n",
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       "<pre class='cython code score-0 '>  __pyx_v_self-&gt;c = __pyx_v_c;\n",
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       "<pre class='cython code score-0 '>  __pyx_v_self-&gt;m = __pyx_v_m;\n",
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       "<pre class='cython code score-0 '>  __pyx_v_self-&gt;x = __pyx_v_seed;\n",
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       "  goto __pyx_L0;\n",
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       "  <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_t_1);\n",
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       "  __pyx_r = NULL;\n",
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       "<pre class='cython code score-0 '>  __pyx_t_5 = __pyx_v_self-&gt;x;\n",
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       "<pre class='cython code score-0 '>  __pyx_v_self-&gt;x = (((__pyx_v_self-&gt;a * __pyx_v_self-&gt;x) + __pyx_v_self-&gt;c) % __pyx_v_self-&gt;m);\n",
       "</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">28</span>:         <span class=\"k\">return</span> <span class=\"n\">r</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_r = __pyx_v_r;\n",
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       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">31</span>:     <span class=\"nd\">@cython</span><span class=\"o\">.</span><span class=\"n\">boundscheck</span><span class=\"p\">(</span><span class=\"bp\">False</span><span class=\"p\">)</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">32</span>:     <span class=\"nd\">@cython</span><span class=\"o\">.</span><span class=\"n\">wraparound</span><span class=\"p\">(</span><span class=\"bp\">False</span><span class=\"p\">)</span></pre>\n",
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       "<pre class='cython code score-28 '>/* Python wrapper */\n",
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       "static PyObject *__pyx_pw_46_cython_magic_e30aa023d90afd72080fd940db08d5ae_5CyLCG_5randint(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n",
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       "<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">35</span>:         <span class=\"k\">if</span> <span class=\"n\">size</span> <span class=\"ow\">is</span> <span class=\"bp\">None</span><span class=\"p\">:</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_t_1 = (__pyx_v_size == Py_None);\n",
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "%%cython -a\n",
    "\n",
    "import numpy as np\n",
    "cimport numpy as cnp\n",
    "cimport cython\n",
    "\n",
    "# Creates a new extension type: https://docs.python.org/3/extending/newtypes.html\n",
    "cdef class CyLCG:\n",
    "    \n",
    "    # We declare the compile-time types of our *instance* attributes here.\n",
    "    # This is similar to C++ class declaration syntax.\n",
    "    cdef long a, c, m, x\n",
    "    \n",
    "    # Special Cython-defined initializer.\n",
    "    # Called before __init__ to initialize all C-level attributes.\n",
    "    def __cinit__(self, long a=1664525, long c=1013904223, long m=2**32, long seed=0):\n",
    "        self.a = a\n",
    "        self.c = c\n",
    "        if m <= 0:\n",
    "            raise ValueError(\"m must be > 0, given {}\".format(m))\n",
    "        self.m = m\n",
    "        self.x = seed\n",
    "    \n",
    "    # cdef / cpdef methods are supported\n",
    "    @cython.cdivision(True)        \n",
    "    cpdef long _advance(self):\n",
    "        cdef long r = self.x\n",
    "        self.x = (self.a * self.x + self.c) % self.m\n",
    "        return r\n",
    "    \n",
    "    # Regular def method\n",
    "    @cython.boundscheck(False)\n",
    "    @cython.wraparound(False)\n",
    "    def randint(self, size=None):\n",
    "        cdef long r\n",
    "        if size is None:\n",
    "            # Call to self._advance() here is efficient and at the C level.\n",
    "            r = self._advance()\n",
    "            return r\n",
    "        cdef long[::1] a = np.empty((size,), dtype='i8')\n",
    "        cdef int i\n",
    "        cdef int n = int(size)\n",
    "        for i in range(n):\n",
    "            a[i] = self._advance()\n",
    "        return np.asarray(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tests and timing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EMgAABiCQAQAwAIEMAIABCGQAAAxAIAMAYAACGQAAAyQVyGNjYwqFQvrLX/6iy5cva/36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\nAAAMQCADAGCA/wOFhszz9XE/tQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56aa6d5828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = CyLCG()\n",
    "nums = rng.randint(size=10000) % 100\n",
    "sns.distplot(nums, bins=100, kde=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%timeit rng = CyLCG()\n",
    "nums = rng.randint(size=10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pure-python memory footprint\n",
    "The sum of the number of bytes in:\n",
    "* the `PyLCG()` object itself\n",
    "* the instance `__dict__`\n",
    "* and each key / value in the instance `__dict__`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pyrng = PyLCG()\n",
    "(sys.getsizeof(pyrng) # the object itself\n",
    " + sys.getsizeof(pyrng.__dict__)  # the instance __dict__\n",
    " + sum(sys.getsizeof(k) + sys.getsizeof(v) for k, v in pyrng.__dict__.items())) # k/v memory use"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could improve this by using a `__slots__` attribute, but won't go down that road."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cython memory footprint\n",
    "The sum of the number of bytes in:\n",
    "* The `CyLCG()` object itself\n",
    "* each instance `long`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(sys.getsizeof(CyLCG()) # the object itself\n",
    " + 4 * 8) # The 4 8-byte longs (a, c, m, x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Public / private instance attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extension type instance attributes are not visibile to Python by default"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cyrng = CyLCG(seed=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cyrng.a, cyrng.c, cyrng.m, cyrng.x\n",
    "# => all give `AttributeError`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extension type instances aren't open to new attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cyrng.z = 15"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### But we can control that with `public` and `readonly` declarations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%cython -a\n",
    "\n",
    "import numpy as np\n",
    "cimport cython\n",
    "\n",
    "cdef class CyLCGOpen:\n",
    "    \n",
    "    cdef public long x\n",
    "    cdef readonly long a, c, m\n",
    "    \n",
    "    def __cinit__(self, long a=1664525, long c=1013904223, long m=2**32, long seed=0):\n",
    "        self.a = a\n",
    "        self.c = c\n",
    "        if m <= 0:\n",
    "            raise ValueError(\"m must be > 0, given {}\".format(m))\n",
    "        self.m = m\n",
    "        self.x = seed\n",
    "        \n",
    "    # cdef / cpdef methods are supported\n",
    "    @cython.cdivision(True)        \n",
    "    cpdef long _advance(self):\n",
    "        cdef long r = self.x\n",
    "        self.x = (self.a * self.x + self.c) % self.m\n",
    "        return r\n",
    "    \n",
    "    # Regular def method\n",
    "    @cython.boundscheck(False)\n",
    "    @cython.wraparound(False)\n",
    "    def randint(self, size=None):\n",
    "        cdef long r\n",
    "        if size is None:\n",
    "            # Call to self._advance() here is efficient and at the C level.\n",
    "            r = self._advance()\n",
    "            return r\n",
    "        cdef long[::1] a = np.empty((size,), dtype='i8')\n",
    "        cdef int i\n",
    "        cdef int n = int(size)\n",
    "        for i in range(n):\n",
    "            a[i] = self._advance()\n",
    "        return np.asarray(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lcg_open = CyLCGOpen()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# now we can see all the instance attributes\n",
    "lcg_open.a, lcg_open.c, lcg_open.m, lcg_open.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# and we can modify `x`\n",
    "lcg_open.x = 42\n",
    "lcg_open.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# but we can't modify `readonly` attributes\n",
    "lcg_open.a = -1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cython extension types in more depth\n",
    "* [cython.org docs](http://cython.readthedocs.io/en/latest/src/userguide/extension_types.html)\n",
    "* [_Cython_ Book, chapter 5](http://shop.oreilly.com/product/0636920033431.do)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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