MagicMethods.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Magic Methods!\n",
    "\n",
    "[Slides](https://docs.google.com/presentation/d/13rnvQ7w2YT3WQKgDDAEd7Unlf67WcgzYVN3uGt-vJP8/edit?usp=sharing)\n",
    "\n",
    "1. You can't not use magic methods\n",
    "2. String magic\n",
    "3. Math-y magic (Infix Methods)\n",
    "4. Ordering magic\n",
    "5. Container magic\n",
    "6. Proprietary magic (IPython Notebook)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ✨ 1. There's a little magic in everything ✨"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyObj:\n",
    "    pass\n",
    "    \n",
    "obj = MyObj()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That called `object.__init__`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<__main__.MyObj at 0x7f5a995b8160>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That called `obj.__repr__`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.MyObj object at 0x7f5a995b8160>\n"
     ]
    }
   ],
   "source": [
    "print(obj)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That called `obj.__str__`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Stringy Magic\n",
    "\n",
    "Implementing [`__repr__`](https://docs.python.org/3/reference/datamodel.html#object.__repr__) and [`__str__`](https://docs.python.org/3/reference/datamodel.html#object.__str__) can often be useful when debugging or manipulating objects interactively (like via Notebooks or REPLs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Stringy:\n",
    "    def __init__(self, name):\n",
    "        self.name = name\n",
    "\n",
    "    def __repr__(self) -> str:\n",
    "        \"\"\"\n",
    "        ...If at all possible, this should look like a valid Python expression \n",
    "        that could be used to recreate an object with the same value. If this \n",
    "        is not possible, a string of the form <...some useful description...> \n",
    "        should be returned. \n",
    "        \"\"\"\n",
    "        return f\"{self.__class__.__name__}('{self.name}')\"\n",
    "    \n",
    "    def __str__(self) -> str:\n",
    "        \"\"\"        \n",
    "        This method differs from `__repr__()` in that there is no expectation \n",
    "        that `__str__()` returns a valid Python expression: a more convenient \n",
    "        or concise representation can be used.\n",
    "        \"\"\"\n",
    "        return f\"Name: {self.name}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Stringy('apple')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = Stringy('apple')\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Stringy('apple')\""
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "repr(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Stringy('apple')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# \"round-trippable\"\n",
    "eval(repr(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name: apple\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Why not something like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class StringyToo:\n",
    "    def __init__(self, name):\n",
    "        self.name = name\n",
    "        \n",
    "    def to_string(self):\n",
    "        return f\"Name: {self.name}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<__main__.StringyToo at 0x7f5a98d4b940>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = StringyToo('cheese')\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Name: cheese'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.to_string()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.StringyToo object at 0x7f5a98d4b940>\n"
     ]
    }
   ],
   "source": [
    "print(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Non-standard. Python already has a method for it\n",
    "* If you want to take formatting arguments, implement `__format__`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Container Magic\n",
    "\n",
    "`__(get|set|del)item__`, `__contains__`, `__len__`, `__iter__`, `__next__`, `__reversed__`..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "from contextlib import suppress\n",
    "\n",
    "# DIY https://docs.python.org/3/library/collections.html#collections.ChainMap\n",
    "\n",
    "class FallbackDict:\n",
    "    \"\"\"Look through a series of dicts in order\"\"\"\n",
    "    \n",
    "    def __init__(self, *dicts):\n",
    "        self.dicts = dicts\n",
    "\n",
    "    def lookup(self, key):\n",
    "        for d in self.dicts:\n",
    "            with suppress(KeyError):  \n",
    "                return d[key]\n",
    "        raise KeyError(key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'pyconie'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dicts = [\n",
    "    {\"name\": \"pyconie\", \"misc\": \"woot\"},\n",
    "    {\"misc\": \"etc\"},\n",
    "    {\"name\": \"unknown\", \"greeting\": \"hello\"},\n",
    "]\n",
    "fbd = FallbackDict(*dicts)\n",
    "\n",
    "fbd.lookup(\"name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'hello'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dicts[2][\"greeting\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'FallbackDict' object is not subscriptable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-42-a6abe5678990>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34mf'{fbd[\"greeting\"]}, {fbd[\"name\"]}!'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'FallbackDict' object is not subscriptable"
     ]
    }
   ],
   "source": [
    "f'{fbd[\"greeting\"]}, {fbd[\"name\"]}!'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's kinda like a dictionary, we can index into it and get items, but not much else."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "object of type 'FallbackDict' has no len()",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-38-af21837b06fb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfbd\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# probably should be 3?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: object of type 'FallbackDict' has no len()"
     ]
    }
   ],
   "source": [
    "len(fbd)  # probably should be 3?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'FallbackDict' object has no attribute 'values'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-25-54faf6786513>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfbd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m  \u001b[0;31m# should be 'woot', 'hello', 'chipy'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m: 'FallbackDict' object has no attribute 'values'"
     ]
    }
   ],
   "source": [
    "[k for k in fbd.values()]  # should be 'woot', 'hello', 'chipy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "argument of type 'FallbackDict' is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-26-ac0350f0e56b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m'name'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfbd\u001b[0m  \u001b[0;31m# is a key in it?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: argument of type 'FallbackDict' is not iterable"
     ]
    }
   ],
   "source": [
    "'name' in fbd  # is a key in it?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'FallbackDict' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-27-5fdcf5942ff9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# would be nice to convert to a normal dict if we wanted to JSON serialize it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfbd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'FallbackDict' object is not iterable"
     ]
    }
   ],
   "source": [
    "# would be nice to convert to a normal dict if we wanted to JSON serialize it\n",
    "dict(fbd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Abstract Base Classes for Containers](https://docs.python.org/3/library/collections.abc.html) (`collections.abc`)\n",
    "\n",
    "Amplify your magics! If you implement the abstract methods required by the type, it can provide additional mixin methods for free. Lets make our `FallbackDict` more `dict`-like by using the `Mapping` ABC (read-only dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import collections.abc\n",
    "\n",
    "\n",
    "# the M is for Mmmproved Mapping\n",
    "class FallbackDictM(FallbackDict, collections.abc.Mapping):\n",
    "    # __init__, __getitem__ from FallbackDict\n",
    "    \n",
    "    def _all_keys(self):\n",
    "        all_keys = set()\n",
    "        for d in self.dicts:\n",
    "            all_keys |= set(d)\n",
    "        return all_keys\n",
    "    \n",
    "    def __len__(self):\n",
    "        return len(self._all_keys())\n",
    "\n",
    "    def __iter__(self):\n",
    "        for key in self._all_keys():\n",
    "            yield key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "fbdm = FallbackDictM(*dicts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "      misc: woot\n",
      "      name: pyconie\n",
      "  greeting: hello\n"
     ]
    }
   ],
   "source": [
    "print(len(fbdm))  # directly hitting __len__\n",
    "for key in fbdm:  # hits __iter__\n",
    "    print(f\"{key:>10s}: {fbdm[key]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['woot', 'pyconie', 'hello']"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(fbdm.values())  # values method for free"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'name' in fbdm  # __contains__ for free"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'misc': 'woot', 'name': 'pyconie', 'greeting': 'hello'}"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flattened = dict(fbdm)\n",
    "flattened"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flattened == fbdm  # __eq__ for free"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from helpers import verbose_method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Math-y Magic\n",
    "\n",
    "Implementing the mathematical magic methods can let you use any of the infix operators to manipulate your objects as makes sense.\n",
    "\n",
    "    x + y     __add__             x & y   __and__\n",
    "    x - y     __sub__             x | y   __or__      \n",
    "    x * y     __mul__             x ^ y   __xor__\n",
    "    x / y     __truediv__         x << y  __lshift__\n",
    "    x // y    __floordiv__        x >> y  __rshift__\n",
    "    x ** y    __pow__           \n",
    "    x % y     __mod__           (unary prefix operators)  \n",
    "    x @ y     __matmul__          -x      __neg__\n",
    "                                  +x      __pos__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(3).__add__(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The operators can be (ab)used in other contexts. Don't go crazy with it: keep it sensible. \n",
    "\n",
    "Let's DIY `pathlib.Path`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PathyBase:\n",
    "    def __init__(self, path):\n",
    "        self.path = path\n",
    "\n",
    "    def __repr__(self):\n",
    "        return f\"{self.__class__.__name__}({self.path!r})\"\n",
    "\n",
    "\n",
    "class PathA(PathyBase):\n",
    "    @verbose_method\n",
    "    def __truediv__(self, other) -> str:\n",
    "        return self.__class__(self.path + '/' + other.path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathA('aaa').__truediv__(PathA('bbb')) => PathA('aaa/bbb')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathA('aaa/bbb')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathA('aaa') / PathA('bbb')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathA('aaa').__truediv__(PathA('bbb')) => PathA('aaa/bbb')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathA('aaa/bbb')"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# identical to above\n",
    "PathA('aaa').__truediv__(PathA('bbb'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "`PathA` shortcoming: only works when all parts are `Path` objects, can't incorporate a string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PathB(PathyBase):\n",
    "    @verbose_method\n",
    "    def __truediv__(self, other):\n",
    "        if isinstance(other, self.__class__):\n",
    "            other_value = other.path\n",
    "        else:\n",
    "            other_value = other\n",
    "\n",
    "        return self.__class__(self.path + '/' + other_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathB('ccc').__truediv__('ddd') => PathB('ccc/ddd')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathB('ccc/ddd')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathB('ccc') / 'ddd'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathB('ccc').__truediv__('ddd') => PathB('ccc/ddd')\n",
      "call: PathB('ccc/ddd').__truediv__('eee') => PathB('ccc/ddd/eee')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathB('ccc/ddd/eee')"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathB('ccc') / 'ddd' / 'eee'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "`PathB` shortcomings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for /: 'str' and 'PathB'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-75-c4f75a9b85c8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m'ccc'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mPathB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ddd'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'PathB'"
     ]
    }
   ],
   "source": [
    "'ccc' / PathB('ddd')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for /: 'str' and 'PathB'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-76-0333ba4da6e4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'usr'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mPathB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'bin'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'PathB'"
     ]
    }
   ],
   "source": [
    "result = 'usr' / PathB('bin') / 'python'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for /: 'str' and 'PathB'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-77-1c7488e70d32>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# equivalent\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0m_intermediate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'usr'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mPathB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'bin'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_intermediate\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'PathB'"
     ]
    }
   ],
   "source": [
    "# equivalent\n",
    "_intermediate = 'usr' / PathB('bin')\n",
    "result = _intermediate / 'python'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "To support those operand type(s), we use the [*reflected* methods](https://docs.python.org/3/reference/datamodel.html?#object.__radd__), `__r*__`. When the \"forward\" direction fails, Python will attempt to call it the other way, so `'usr' + PathB('lib')` is effectively something like:\n",
    "\n",
    "```python\n",
    "try:\n",
    "    'usr'.__truediv__(PathB('lib'))   # the str type doesn't know what a Path is\n",
    "except TypeError:\n",
    "    PathB('lib').__rtruediv__('usr')  # but we have the option to do something!\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numeric Demo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(2).__rsub__(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50.0"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(2).__rtruediv__(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PathC(PathB):\n",
    "    # __truediv__ from PathB\n",
    "\n",
    "    @verbose_method\n",
    "    def __rtruediv__(self, other) -> str:\n",
    "        \"\"\"\n",
    "        Note that the order of arguments are reversed on the call; \n",
    "        so `self` will be the object *after* the infix operator, and \n",
    "        `other` the one before.\n",
    "        \n",
    "        We're also assuming that other is an integer, Path / Path\n",
    "        operations will just use __truediv__ from the first one.\n",
    "        \"\"\"\n",
    "        return self.__class__(other + '/' + self.path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathC('bash').__rtruediv__('bin') => PathC('bin/bash')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathC('bin/bash')"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'bin' / PathC('bash')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathC('home').__truediv__(PathC('nick')) => PathC('home/nick')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathC('home/nick')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathC('home') / PathC('nick')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathC('home').__truediv__('nick') => PathC('home/nick')\n",
      "call: PathC('home/nick').__truediv__(PathC('Code')) => PathC('home/nick/Code')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathC('home/nick/Code')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathC('home') / 'nick' / PathC('Code')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathC('home').__truediv__('nick') => PathC('home/nick')\n",
      "call: PathC('home/nick').__truediv__('Code') => PathC('home/nick/Code')\n",
      "call: PathC('home/nick/Code').__truediv__('talks/pyconie') => PathC('home/nick/Code/talks/pyconie')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PathC('home/nick/Code/talks/pyconie')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PathC('home') / 'nick' / 'Code' / 'talks/pyconie'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More Abstract Mixins\n",
    "\n",
    "The built-in `open()` accepts objects that are [`os.PathLike`](https://docs.python.org/3/library/os.html#os.PathLike) (new in 3.6). `PathLike` is an **abstract base class** that objects can define to specify how they are path-like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "class PathD(PathC, os.PathLike):\n",
    "    @verbose_method\n",
    "    def __fspath__(self):\n",
    "        return os.path.expanduser(self.path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "building path\n",
      "call: PathD('~').__truediv__('.gitignore_global') => PathD('~/.gitignore_global')\n",
      "opening it!\n",
      "call: PathD('~/.gitignore_global').__fspath__() => '/home/nick/.gitignore_global'\n",
      "\n",
      "File Contents:\n",
      "==============\n",
      "*.py[cod]\n",
      "__pycache__/\n",
      "_build\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('building path')\n",
    "ignore = PathD('~') / '.gitignore_global'\n",
    "\n",
    "print('opening it!')\n",
    "with open(ignore) as f:\n",
    "    print('\\nFile Contents:\\n==============')\n",
    "    for line in f:\n",
    "        print(line, end=\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've created a hacky version of [`pathlib`](https://docs.python.org/3/library/pathlib.html), a standard library package.  Use that one instead, but be inspired to create something else."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Ordering Magic\n",
    "\n",
    "The Methods: `__eq__`, `__ne__`, `__lt__`, `__le__`, `__gt__`, `__ge__`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "versions = [\n",
    "    '0.9.4',\n",
    "    '0.95.3',\n",
    "    '0.10.5',\n",
    "    '0.9.34',\n",
    "    '0.10.42',\n",
    "    '1.4.2',\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0.10.42', '0.10.5', '0.9.34', '0.9.4', '0.95.3', '1.4.2']"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(versions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How can we sort these? We could pass a `key` argument into `sorted()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0.9.4', '0.9.34', '0.10.5', '0.10.42', '0.95.3', '1.4.2']"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(versions, key=lambda i: [int(p) for p in i.split('.')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Version:\n",
    "    def __init__(self, version):\n",
    "        self.version = version\n",
    "        self.major, self.minor, self.patch = (int(x) for x in version.split('.'))\n",
    "    \n",
    "    def __repr__(self):\n",
    "        return f'{self.__class__.__name__}({self.version!r})'\n",
    "\n",
    "    @verbose_method\n",
    "    def __lt__(self, other):\n",
    "        return (\n",
    "            (self.major, self.minor, self.patch) \n",
    "            < (other.major, other.minor, other.patch)\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.32.52').__lt__(Version('0.93.2')) => True\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Version('0.32.52') < Version('0.93.2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('10.0.0').__lt__(Version('9.99.999')) => False\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Version('10.0.0') < Version('9.99.999')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<=' not supported between instances of 'Version' and 'Version'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-296-422fc2c052f8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mVersion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'10.0.0'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mVersion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'9.99.999'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: '<=' not supported between instances of 'Version' and 'Version'"
     ]
    }
   ],
   "source": [
    "Version('10.0.0') <= Version('9.99.999')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [],
   "source": [
    "import functools\n",
    "\n",
    "@functools.total_ordering\n",
    "class Version2(Version):\n",
    "    # __lt__ from Version\n",
    "    \n",
    "    @verbose_method\n",
    "    def __eq__(self, other):\n",
    "        return (\n",
    "            (self.major, self.minor, self.patch) \n",
    "            == (other.major, other.minor, other.patch)\n",
    "        )\n",
    "    \n",
    "    # __gt__, __ge__, __le__ from total_ordering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version2('1.23.42').__lt__(Version2('1.5.99')) => False\n",
      "call: Version2('1.23.42').__eq__(Version2('1.5.99')) => False\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Version2(\"1.23.42\") > Version2(\"1.5.99\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Version('0.9.4'),\n",
       " Version('0.95.3'),\n",
       " Version('0.10.5'),\n",
       " Version('0.9.34'),\n",
       " Version('0.10.42'),\n",
       " Version('1.4.2')]"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "version_objs = [Version(v) for v in versions]\n",
    "version_objs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.95.3').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.10.5').__lt__(Version('0.95.3')) => True\n",
      "call: Version('0.10.5').__lt__(Version('0.95.3')) => True\n",
      "call: Version('0.10.5').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.9.34').__lt__(Version('0.10.5')) => True\n",
      "call: Version('0.9.34').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.10.42').__lt__(Version('0.10.5')) => False\n",
      "call: Version('0.10.42').__lt__(Version('0.95.3')) => True\n",
      "call: Version('1.4.2').__lt__(Version('0.10.5')) => False\n",
      "call: Version('1.4.2').__lt__(Version('0.95.3')) => False\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Version('0.9.4'),\n",
       " Version('0.9.34'),\n",
       " Version('0.10.5'),\n",
       " Version('0.10.42'),\n",
       " Version('0.95.3'),\n",
       " Version('1.4.2')]"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(version_objs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.9.4').__lt__(Version('0.95.3')) => True\n",
      "call: Version('0.95.3').__lt__(Version('0.10.5')) => False\n",
      "call: Version('0.95.3').__lt__(Version('0.9.34')) => False\n",
      "call: Version('0.95.3').__lt__(Version('0.10.42')) => False\n",
      "call: Version('0.95.3').__lt__(Version('1.4.2')) => True\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Version('1.4.2')"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(version_objs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.95.3').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.10.5').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.9.34').__lt__(Version('0.9.4')) => False\n",
      "call: Version('0.10.42').__lt__(Version('0.9.4')) => False\n",
      "call: Version('1.4.2').__lt__(Version('0.9.4')) => False\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Version('0.9.4')"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(version_objs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also, not everything can take a `key` argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.10.5').__lt__(Version('1.4.2')) => True\n",
      "call: Version('0.9.34').__lt__(Version('0.10.42')) => True\n",
      "call: Version('0.95.3').__lt__(Version('0.9.34')) => False\n",
      "call: Version('0.9.34').__lt__(Version('0.10.5')) => True\n",
      "call: Version('0.95.3').__lt__(Version('0.10.42')) => False\n",
      "call: Version('0.9.4').__lt__(Version('0.10.42')) => True\n",
      "call: Version('0.9.4').__lt__(Version('0.9.34')) => True\n"
     ]
    }
   ],
   "source": [
    "import heapq\n",
    "\n",
    "version_heap = version_objs[:]\n",
    "heapq.heapify(version_heap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: Version('0.9.34').__lt__(Version('0.10.5')) => True\n",
      "call: Version('0.95.3').__lt__(Version('0.10.42')) => False\n",
      "call: Version('1.4.2').__lt__(Version('0.10.42')) => False\n",
      "Version('0.9.4')\n",
      "call: Version('0.10.42').__lt__(Version('0.10.5')) => False\n",
      "call: Version('1.4.2').__lt__(Version('0.10.5')) => False\n",
      "Version('0.9.34')\n",
      "call: Version('0.10.42').__lt__(Version('1.4.2')) => True\n",
      "call: Version('0.95.3').__lt__(Version('0.10.42')) => False\n",
      "Version('0.10.5')\n",
      "call: Version('1.4.2').__lt__(Version('0.95.3')) => False\n",
      "Version('0.10.42')\n",
      "Version('0.95.3')\n",
      "Version('1.4.2')\n"
     ]
    }
   ],
   "source": [
    "while version_heap:\n",
    "    print(heapq.heappop(version_heap))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Proprietary Magic\n",
    "\n",
    "https://ipython.readthedocs.io/en/stable/config/integrating.html#rich-display\n",
    "\n",
    "IPython notebook can display richer representations of objects. To use this, you can define any of a number of `_repr_*_()` methods. Note that these are surrounded by single, not double underscores.\n",
    "\n",
    "The notebook can display `svg`, `png`, `jpeg`, `html`, `javascript`, `markdown` and `latex`. If the methods don’t exist, or return `None`, it falls back to a standard `repr()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://imgs.xkcd.com/comics/aaaaaa.png'"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from helpers import get_xkcd_hotlink\n",
    "get_xkcd_hotlink(1001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "import functools\n",
    "import requests\n",
    "\n",
    "class XKCDComic:\n",
    "    def __init__(self, url):\n",
    "        self.url = url\n",
    "        self.png = None\n",
    "        \n",
    "    def load(self):\n",
    "        response = requests.get(self.url)\n",
    "        response.raise_for_status()\n",
    "        self.png = response.content\n",
    "        \n",
    "    def _repr_png_(self):\n",
    "        if self.png is None:\n",
    "            self.load()\n",
    "        return self.png\n",
    "\n",
    "class XKCDViewer:\n",
    "    @functools.lru_cache()\n",
    "    def __getitem__(self, key):\n",
    "        url = get_xkcd_hotlink(key)\n",
    "        if url is None:\n",
    "            raise KeyError(\"couldn't find XKCD comic with that number\")\n",
    "        return XKCDComic(url)\n",
    "\n",
    "xkcd = XKCDViewer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<__main__.XKCDComic at 0x7f5a83577518>"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ANTIGRAVITY = 353\n",
    "BOBBY_TABLES = 327\n",
    "PYTHON_ENV = 1987\n",
    "SANDWICH = 149\n",
    "PARENS = 297\n",
    "\n",
    "xkcd[PARENS]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br><br><hr><br><br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bonus: Context Managers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Suppressor:\n",
    "    \"\"\"\n",
    "    https://docs.python.org/3/reference/datamodel.html#with-statement-context-managers\n",
    "    \"\"\"\n",
    "    def __init__(self, exc_ignore):\n",
    "        self.exc_ignore = exc_ignore\n",
    "\n",
    "    def __enter__(self):\n",
    "        return self\n",
    "    \n",
    "    def __exit__(self, exc_type, exc_value, traceback):\n",
    "        \"\"\"\n",
    "        ... If an exception is supplied, and the method wishes to suppress the \n",
    "        exception, it should return a true value. ...\n",
    "        \"\"\"\n",
    "        return (\n",
    "            exc_type is not None \n",
    "            and issubclass(exc_type, self.exc_ignore)\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "abc\n",
      "mmmkay\n"
     ]
    }
   ],
   "source": [
    "with Suppressor(IndexError):\n",
    "    print('abcde'[:3])  # works normally\n",
    "\n",
    "with Suppressor(IndexError):\n",
    "    print('abcde'[1000])  # raises an error, but it gets suppressed\n",
    "    \n",
    "print('mmmkay')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "string index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-154-237bc03c9b44>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mSuppressor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mRuntimeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0;34m'abcde'\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1000\u001b[0m\u001b[0;34m]\u001b[0m  \u001b[0;31m# raises the wrong error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: string index out of range"
     ]
    }
   ],
   "source": [
    "with Suppressor(RuntimeError):\n",
    "    'abcde'[1000]  # raises the wrong error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We basically re-implemented [`contextlib.suppress`](https://docs.python.org/3/library/contextlib.html#contextlib.suppress) [(source)](https://github.com/python/cpython/blob/cca4eec3c0/Lib/contextlib.py#L342) from the standard lib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "import traceback\n",
    "\n",
    "class expect_exception:\n",
    "    \"\"\"\n",
    "    Expect an exception and trap it. Helps run all of a notebook\n",
    "    that may have intentional errors for pedagogical reasons\n",
    "    \"\"\"\n",
    "    def __init__(self, *exc_types):\n",
    "        self.exc_types = exc_types\n",
    "        \n",
    "    def __enter__(self):\n",
    "        return self\n",
    "    \n",
    "    def __exit__(self, exc_type, exc_value, tb):\n",
    "        if exc_type is None:\n",
    "            raise RuntimeError('expected exception did not occur!')\n",
    "        if issubclass(exc_type, self.exc_types):\n",
    "            traceback.print_exception(exc_type, exc_value, tb)\n",
    "            return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call: PathA('a').__truediv__('b') =X 'AttributeError(\"\\'str\\' object has no attribute \\'path\\'\")'\n",
      "I'm not dead yet\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"<ipython-input-131-607bf4cd8fd0>\", line 2, in <module>\n",
      "    PathA('a') / 'b'\n",
      "  File \"/home/nick/Code/talks-magicmethods/helpers.py\", line 11, in _method\n",
      "    result = method(self, *args)\n",
      "  File \"<ipython-input-69-78ced35de376>\", line 12, in __truediv__\n",
      "    return self.__class__(self.path + '/' + other.path)\n",
      "AttributeError: 'str' object has no attribute 'path'\n"
     ]
    }
   ],
   "source": [
    "with expect_exception(AttributeError):\n",
    "    PathA('a') / 'b'\n",
    "\n",
    "print(\"I'm not dead yet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Penalty Time: Pad time with audience questions\n",
    "\n",
    "* Punt: Name your favorite bit of syntax! (maybe magic methods are involved)\n",
    "* Live Coding/Comedy: Have me implement the magic method of your choice!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyObj:\n",
    "    def __x__(self, xyz):\n",
    "        ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br><br><hr><br><br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wow, that went fast, still need more content?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IPv4('10.23.42.2')\n",
      "IPv4Range('10.23.32.0')\n"
     ]
    }
   ],
   "source": [
    "class IPv4:\n",
    "    def __init__(self, address):\n",
    "        self.address = address\n",
    "        self.bits = bytes(int(p) for p in address.split(\".\"))\n",
    "        \n",
    "    def __repr__(self):\n",
    "        return f\"{self.__class__.__name__}({self.address!r})\"\n",
    "        \n",
    "    def __truediv__(self, bits):\n",
    "        return IPv4Range(self.address, bits)\n",
    "    \n",
    "class IPv4Range:\n",
    "    def __init__(self, address, mask_bits):\n",
    "        bits = bytes(int(p) for p in address.split(\".\"))\n",
    "        num = int.from_bytes(bits, \"big\")\n",
    "        num = num & ~((1 << (32 - mask_bits)) - 1)\n",
    "        self.bits = num.to_bytes(4, \"big\")\n",
    "        self.address = \".\".join(str(n) for n in self.bits)\n",
    "        \n",
    "    def __repr__(self):\n",
    "        return f\"{self.__class__.__name__}({self.address!r})\"\n",
    "    \n",
    "addr = IPv4(\"10.23.42.2\")\n",
    "addr_range = addr / 20\n",
    "print(addr)\n",
    "print(addr_range)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CSS hacks for more efficient space use "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "div.prompt {\n",
       "    min-width: 11ex;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<style>\n",
    "div.prompt {\n",
    "    min-width: 11ex;\n",
    "}\n",
    "</style>"
   ]
  }
 ],
 "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",
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