sem_6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://files.realpython.com/media/Python_Exceptions_Watermark.47f814fbeced.jpg\"> </img>\n",
    "\n",
    "# Классы, исключения, итераторы, генераторы!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Функции\n",
    "Доки: [встроенные полезности](https://docs.python.org/3.6/library/functions.html), [itertools](https://docs.python.org/3.6/library/itertools.html), [functools](https://docs.python.org/3.6/library/functools.html)\n",
    "\n",
    "Полезные посты: https://realpython.com/python-itertools/\n",
    "#### Встроенные функции"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0: cat\n",
      "1: dog\n",
      "2: parrot\n",
      "3: crocodile\n"
     ]
    }
   ],
   "source": [
    "animals = [\"cat\", \"dog\", \"parrot\", \"crocodile\"]\n",
    "\n",
    "for index, animal in enumerate(animals):\n",
    "    print(\"{idx}: {name}\".format(idx=index, name=animal))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cat likes fish\n",
      "dog likes all\n",
      "parrot likes fruits\n",
      "crocodile likes meat\n"
     ]
    }
   ],
   "source": [
    "eats = [\"fish\", \"all\", \"fruits\", \"meat\"]\n",
    "\n",
    "for food, animal in zip(eats, animals):\n",
    "    print(\"{} likes {}\".format(animal, food))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### all(iterable) и any(iterable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[False, False, False, False, True, True]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[i > 3 for i in range(6)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "any([i > 3 for i in range(6)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all([i > 3 for i in range(6)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import accumulate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 3, 6, 10, 15, 21, 28, 36, 45]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(accumulate([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 1.0,\n",
       " 1.0,\n",
       " 1.5,\n",
       " 1.6,\n",
       " 1.923076923076923,\n",
       " 2.0526315789473686,\n",
       " 2.293103448275862,\n",
       " 2.4293193717277486,\n",
       " 2.6244274809160304]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(accumulate([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], lambda x, y: y / (x + 1)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### functools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reduce(lambda x, y: x+y, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Классы"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Классы нужны для обьединения данных и способов работы с ними в единую абстракцию.\n",
    "В Питоне классы -- это объекты, которые умеют порождать другие обьекты (экземпляры данного класса).\n",
    "\n",
    "В Питоне все объекты -- это экземпляры каких-то классов.\n",
    "\n",
    "int – класс ; 1, 2, 3 – объекты этого класса"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Pet(object):\n",
    "    character = \"kind\"\n",
    "    def talk(self):\n",
    "        print(\"Mey, mey, mey\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mey, mey, mey\n"
     ]
    }
   ],
   "source": [
    "a = Pet()\n",
    "a.talk()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'kind'"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.character"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = Pet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bad\n"
     ]
    }
   ],
   "source": [
    "b.character = \"bad\"\n",
    "print(b.character)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kind\n"
     ]
    }
   ],
   "source": [
    "print(a.character)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('strange', 'bad')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Pet.character = \"strange\"\n",
    "a.character, b.character"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Pet(object):\n",
    "    def __init__(self, name, word, character=\"kind\"):\n",
    "        self.name = name\n",
    "        self.word = word.lower()\n",
    "        self.character = character\n",
    "        \n",
    "    def talk(self):\n",
    "        print(self.word.title(), self.word, self.word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gav gav gav\n"
     ]
    }
   ],
   "source": [
    "pet = Pet(\"Sharik\", \"Gav\")\n",
    "pet.talk()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Murr murr murr\n"
     ]
    }
   ],
   "source": [
    "pet = Pet(\"Murka\", \"Murr\")\n",
    "pet.talk()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Pet(object):\n",
    "    def __init__(self, name, word, character=\"kind\"):\n",
    "        self.name = name\n",
    "        self.word = word.lower()\n",
    "        self.character = character\n",
    "        \n",
    "    def talk(self):\n",
    "        print(self.word.title(), self.word, self.word)\n",
    "        \n",
    "    def __str__(self):\n",
    "        return \"Hello, I'm {} {}. {}!\".format(self.character, \n",
    "                                              self.name.title(), self.word.title())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, I'm kind Sharik. Gav!\n"
     ]
    }
   ],
   "source": [
    "pet = Pet(\"Sharik\", \"Gav\")\n",
    "print(pet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Cat(Pet):\n",
    "    def __init__(self, name, color, character=\"soft\"):\n",
    "        super().__init__(name, \"mey\", character)\n",
    "        self.color = color\n",
    "        \n",
    "    def catch(self, mouse):\n",
    "        print(\"I cought a mouse {}\".format(mouse.name))\n",
    "        \n",
    "    def __len__(self):\n",
    "        return 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mey mey mey\n"
     ]
    }
   ],
   "source": [
    "cat = Cat(\"Murka\", \"white\")\n",
    "cat.talk()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I cought a mouse Harry\n"
     ]
    }
   ],
   "source": [
    "mouse = Pet(\"Harry\", \"pi\")\n",
    "cat.catch(mouse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cat)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Упражнение\n",
    "\n",
    "Реализуйте класс Matrix. Он должен содержать:\n",
    "* Конструктор от списка списков. Гарантируется, что списки состоят из чисел, не пусты и все имеют одинаковый размер. Конструктор должен копировать содержимое списка списков, т.е. при изменении списков, от которых была сконструирована матрица, содержимое матрицы изменяться не должно.\n",
    "* Метод \\_\\_str\\_\\_ переводящий матрицу в строку. При этом элементы внутри одной строки должны быть разделены знаками табуляции, а строки — переносами строк. При этом после каждой строки не должно быть символа табуляции и в конце не должно быть переноса строки.\n",
    "* Метод size без аргументов, возвращающий кортеж вида (число строк, число столбцов)\n",
    "* \\_\\_add\\_\\_ принимающий вторую матрицу того же размера и возвращающий сумму матриц\n",
    "\n",
    "На проверку вы должны сдать только файл, содержащий описание класса и одну строку вне класса (в качестве основной программы):\n",
    "\n",
    "``exec(stdin.read())``\n",
    "\n",
    "И в начале файла:\n",
    "\n",
    "``from sys import stdin``\n",
    "\n",
    "Для тестирования класса вы можете вместо строки ``exec(stdin.read())`` вставлять код из примеров или писать свой код."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Исключения"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ошибки в программах:\n",
    "\n",
    "* Синтаксические -- обнаруживаются компилятором до запуска скрипта\n",
    "* Исключения -- падают во время исполнения"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "unexpected EOF while parsing (<ipython-input-110-02d501c72305>, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-110-02d501c72305>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m    print(\"How do you do?\"\u001b[0m\n\u001b[0m                          ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unexpected EOF while parsing\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello!\")\n",
    "print(\"How do you do?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello!\n"
     ]
    },
    {
     "ename": "ZeroDivisionError",
     "evalue": "division by zero",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-112-1941caebe5c5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Hello!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"How do you do?\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
     ]
    }
   ],
   "source": [
    "print(\"Hello!\")\n",
    "print(2/0)\n",
    "print(\"How do you do?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Обработка исключений: It's easier to ask for forgiveness than permission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Oops! name 'do_smth' is not defined\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    do_smth()\n",
    "except NameError as e:\n",
    "    print(\"Oops! {}\".format(e))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You're trying to do smth wrong! division by zero\n"
     ]
    }
   ],
   "source": [
    "def foo(lst, number):\n",
    "    return lst[5] / number\n",
    "\n",
    "try:\n",
    "    foo([1, 2, 3, 4, 5, 6], 0)\n",
    "except (IndexError, ZeroDivisionError) as e:\n",
    "    print(\"You're trying to do smth wrong! {}\".format(e))\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Иерархия исключений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Exception, GeneratorExit, SystemExit, KeyboardInterrupt]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BaseException.__subclasses__()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Вот так делать нельзя!!!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OOPS\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    do_smth()\n",
    "except:\n",
    "    print(\"OOPS\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Лучше хотя бы так:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OOPS\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    do_smth()\n",
    "except Exception:\n",
    "    print(\"OOPS\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[TypeError,\n",
       " StopAsyncIteration,\n",
       " StopIteration,\n",
       " ImportError,\n",
       " OSError,\n",
       " EOFError,\n",
       " RuntimeError,\n",
       " NameError,\n",
       " AttributeError,\n",
       " SyntaxError,\n",
       " LookupError,\n",
       " ValueError,\n",
       " AssertionError,\n",
       " ArithmeticError,\n",
       " SystemError,\n",
       " ReferenceError,\n",
       " BufferError,\n",
       " MemoryError,\n",
       " Warning,\n",
       " locale.Error,\n",
       " sre_constants.error,\n",
       " sre_parse.Verbose,\n",
       " warnings._OptionError,\n",
       " runpy._Error,\n",
       " subprocess.SubprocessError,\n",
       " tokenize.TokenError,\n",
       " tokenize.StopTokenizing,\n",
       " copy.Error,\n",
       " zlib.error,\n",
       " _lzma.LZMAError,\n",
       " shutil.RegistryError,\n",
       " inspect.EndOfBlock,\n",
       " struct.error,\n",
       " traitlets.traitlets.TraitError,\n",
       " argparse.ArgumentError,\n",
       " argparse.ArgumentTypeError,\n",
       " traitlets.config.loader.ConfigError,\n",
       " traitlets.config.configurable.ConfigurableError,\n",
       " traitlets.config.application.ApplicationError,\n",
       " pydoc.ErrorDuringImport,\n",
       " bdb.BdbQuit,\n",
       " pygments.util.OptionError,\n",
       " pdb.Restart,\n",
       " pexpect.exceptions.ExceptionPexpect,\n",
       " termios.error,\n",
       " ptyprocess.ptyprocess.PtyProcessError,\n",
       " IPython.utils.process.FindCmdError,\n",
       " IPython.utils.path.HomeDirError,\n",
       " IPython.core.profiledir.ProfileDirError,\n",
       " IPython.core.error.IPythonCoreError,\n",
       " IPython.core.error.InputRejected,\n",
       " getopt.GetoptError,\n",
       " binascii.Incomplete,\n",
       " pygments.filters.ErrorToken,\n",
       " IPython.utils.tokenize2.TokenError,\n",
       " IPython.utils.tokenize2.StopTokenizing,\n",
       " pickle._Stop,\n",
       " _pickle.PickleError,\n",
       " IPython.core.prefilter.PrefilterError,\n",
       " IPython.core.alias.AliasError,\n",
       " sqlite3.Error,\n",
       " sqlite3.Warning,\n",
       " IPython.core.interactiveshell.SpaceInInput,\n",
       " prompt_toolkit.validation.ValidationError,\n",
       " prompt_toolkit.buffer.EditReadOnlyBuffer,\n",
       " prompt_toolkit.renderer.HeightIsUnknownError,\n",
       " parso.pgen2.parse.InternalParseError,\n",
       " parso.parser.ParserSyntaxError,\n",
       " parso.python.diff._PositionUpdatingFinished,\n",
       " queue.Empty,\n",
       " queue.Full,\n",
       " ctypes.ArgumentError,\n",
       " jedi.evaluate.utils.UncaughtAttributeError,\n",
       " jedi.evaluate.compiled.fake.FakeDoesNotExist,\n",
       " jedi.api.helpers.OnErrorLeaf,\n",
       " distutils.errors.DistutilsError,\n",
       " distutils.errors.CCompilerError,\n",
       " socket._GiveupOnSendfile,\n",
       " jedi.api.exceptions._JediError,\n",
       " jedi.api.environment.InvalidPythonEnvironment,\n",
       " IPython.core.magics.code.InteractivelyDefined,\n",
       " optparse.OptParseError,\n",
       " IPython.terminal.embed.KillEmbedded,\n",
       " zmq.error.ZMQBaseError,\n",
       " jupyter_client.localinterfaces.NoIPAddresses,\n",
       " jupyter_client.channels.InvalidPortNumber,\n",
       " jupyter_client.multikernelmanager.DuplicateKernelError,\n",
       " tornado.util.TimeoutError,\n",
       " _curses.error,\n",
       " tornado.stack_context.StackContextInconsistentError,\n",
       " concurrent.futures._base.Error,\n",
       " multiprocessing.context.ProcessError,\n",
       " concurrent.futures.process._RemoteTraceback,\n",
       " asyncio.queues.QueueEmpty,\n",
       " asyncio.queues.QueueFull,\n",
       " asyncio.streams.LimitOverrunError,\n",
       " tornado.concurrent.ReturnValueIgnoredError,\n",
       " tornado.gen.KeyReuseError,\n",
       " tornado.gen.UnknownKeyError,\n",
       " tornado.gen.LeakedCallbackError,\n",
       " tornado.gen.BadYieldError,\n",
       " tornado.gen.ReturnValueIgnoredError,\n",
       " tornado.gen.Return]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Exception.__subclasses__()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Подняние исключений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "ename": "AssertionError",
     "evalue": "Math still works!",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-138-c593302c52cc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0;36m10\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Math still works!\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m: Math still works!"
     ]
    }
   ],
   "source": [
    "assert 10 == 3, \"Math still works!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "ename": "Exception",
     "evalue": "Hello, exception world!",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-133-7992cb3bd660>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Hello, exception world!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mException\u001b[0m: Hello, exception world!"
     ]
    }
   ],
   "source": [
    "raise Exception(\"Hello, exception world!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Hello, exception world!",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-134-3feb81af3f06>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Hello, exception world!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: Hello, exception world!"
     ]
    }
   ],
   "source": [
    "raise ValueError(\"Hello, exception world!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "exceptions must derive from BaseException",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-135-ac58a890884f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mCat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: exceptions must derive from BaseException"
     ]
    }
   ],
   "source": [
    "raise Cat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Пользовательские исключения"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "ename": "PetError",
     "evalue": "Pets must be kind",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mPetError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-139-67a68c4112c2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0;34m\"Pets must be kind\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mPetError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mPetError\u001b[0m: Pets must be kind"
     ]
    }
   ],
   "source": [
    "class PetError(Exception):\n",
    "    def __str__(self):\n",
    "        return \"Pets must be kind\"\n",
    "        \n",
    "raise PetError()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Pet(object):\n",
    "    def __init__(self, name, word, character=\"kind\"):\n",
    "        if character != \"kind\":\n",
    "            raise PetError\n",
    "        self.name = name\n",
    "        self.word = word.lower()\n",
    "        self.character = character\n",
    "        \n",
    "    def talk(self):\n",
    "        print(self.word.title(), self.word, self.word)\n",
    "        \n",
    "    def __str__(self):\n",
    "        return \"Hello, I'm {} {}. {}!\".format(self.character, \n",
    "                                              self.name.title(), self.word.title())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "ename": "PetError",
     "evalue": "Pets must be kind",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mPetError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-141-50b5176941c7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Harry\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Gav\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"bad\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-140-db308b75e719>\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, name, word, character)\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcharacter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"kind\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcharacter\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"kind\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mPetError\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mword\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mPetError\u001b[0m: Pets must be kind"
     ]
    }
   ],
   "source": [
    "pet = Pet(\"Harry\", \"Gav\", \"bad\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AdvancedPetError(Exception):\n",
    "    def __init__(self, name, *args):\n",
    "        super().__init__(*args)\n",
    "        self.name = name\n",
    "        \n",
    "    def __str__(self):\n",
    "        return '{} must be kind.'.format(self.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Pet(object):\n",
    "    def __init__(self, name, word, character=\"kind\"):\n",
    "        if character != \"kind\":\n",
    "            raise AdvancedPetError(name)\n",
    "        self.name = name\n",
    "        self.word = word.lower()\n",
    "        self.character = character\n",
    "        \n",
    "    def talk(self):\n",
    "        print(self.word.title(), self.word, self.word)\n",
    "        \n",
    "    def __str__(self):\n",
    "        return \"Hello, I'm {} {}. {}!\".format(self.character, \n",
    "                                              self.name.title(), self.word.title())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "ename": "AdvancedPetError",
     "evalue": "Harry must be kind.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAdvancedPetError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-165-50b5176941c7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Harry\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Gav\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"bad\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-164-a8b61cfb8ecd>\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, name, word, character)\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcharacter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"kind\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcharacter\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"kind\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mAdvancedPetError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mword\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAdvancedPetError\u001b[0m: Harry must be kind."
     ]
    }
   ],
   "source": [
    "pet = Pet(\"Harry\", \"Gav\", \"bad\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Упражнение\n",
    "\n",
    "Добавьте в программу из задачи B класс MatrixError, содержащий внутри self поля matrix1 и matrix2 (ссылки на матрицы).\n",
    "\n",
    "В класс Matrix внесите следующие изменения:\n",
    "* Добавьте в метод \\_\\_add\\_\\_ проверку на ошибки в размере входных данных чтобы при попытке сложить матрицы разных размеров было выброшено исключение MatrixError таким образом, чтобы matrix1 поле MatrixError стало первым аргументом \\_\\_add\\_\\_ (просто self), а matrix2 — вторым (второй операнд для сложения).\n",
    "* Реализуйте метод transpose, транспонирующий матрицу и возвращающую результат (данный метод модифицирует экземпляр класса Matrix)\n",
    "* Реализуйте статический метод transposed, принимающий Matrix и возвращающий транспонированную матрицу. [Пример статического метода](https://ru.wikipedia.org/wiki/Объектно-ориентированное_программирование_на_Python#.D0.A1.D1.82.D0.B0.D1.82.D0.B8.D1.87.D0.B5.D1.81.D0.BA.D0.B8.D0.B9_.D0.BC.D0.B5.D1.82.D0.BE.D0.B4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Итераторы"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Итерируемая последовательность (Iterable)**\n",
    "\n",
    "Это обьект у которого определён метод \\_\\_iter\\_\\_, возвращающий обьект-итератор (Примеры: list, dict, file, range)\n",
    "\n",
    "**Итератор**\n",
    "\n",
    "Это обьект у которого определён метод \\_\\_next\\_\\_\n",
    "\n",
    "Метод next при каждом вызове должен возвращать следующий элемент последовательности, или выкидывать исключение StopIteration, если последовательность кончилась"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "2\n",
      "3\n",
      "4\n"
     ]
    },
    {
     "ename": "StopIteration",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mStopIteration\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-147-682c3267eef5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0miter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mStopIteration\u001b[0m: "
     ]
    }
   ],
   "source": [
    "a = iter([1, 2, 3, 4])\n",
    "while True:\n",
    "    print(next(a))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Упражнение\n",
    "\n",
    "Напишите свой класс Range и итератор для него"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Генераторы\n",
    "\n",
    "Генератор это функция исполнение которой **приостанавливается**, а не прекращается при возврате значения. Выполнение функции можно продолжить с того же места."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "def foo(x):\n",
    "    print('Generator enter')\n",
    "    yield x\n",
    "    x += 2\n",
    "    yield x\n",
    "    x += 3\n",
    "    yield x\n",
    "    print('Generator Done')      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "function"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(foo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = foo(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "generator"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generator enter\n",
      "3\n",
      "5\n",
      "8\n",
      "Generator Done\n"
     ]
    },
    {
     "ename": "StopIteration",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mStopIteration\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-152-5d9760d4b8fb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mStopIteration\u001b[0m: "
     ]
    }
   ],
   "source": [
    "print(next(a))\n",
    "print(next(a))\n",
    "print(next(a))\n",
    "print(next(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generator enter\n",
      "5\n",
      "7\n",
      "10\n",
      "Generator Done\n"
     ]
    }
   ],
   "source": [
    "b = foo(5)\n",
    "for i in b:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Примеры"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "def my_map(function, iterable):\n",
    "    for i in iterable:\n",
    "        yield function(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(my_map(lambda x: x**2, range(10)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "def my_zip(*iterables):\n",
    "    iterators = list(map(iter, iterables))\n",
    "    while True:\n",
    "        try:\n",
    "            yield [next(it) for it in iterators]\n",
    "        except StopIteration:\n",
    "            return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 3], [2, 4]]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(my_zip([1, 2, 3], [3, 4]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Упражнение \n",
    "\n",
    "Напишите свой генератор [filter](https://docs.python.org/3.6/library/functions.html#filter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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