sem04_functions/sem04_194.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ванильные функцие "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f(x, y):\n",
    "    z = x**2 + 2*x*y + y**2\n",
    "    # print(z)\n",
    "    return z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f(3, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2704"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f(50, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "121"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def ggg(x, y=5):\n",
    "    \"\"\"\n",
    "     Привет, меня зовут f и я люблю пельмени\n",
    "    \"\"\"\n",
    "    z = x**2 + 2*x*y + y**2\n",
    "    return z\n",
    "\n",
    "ggg(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "225"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f(6, y=9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import my_module as mm\n",
    "mm.ggg(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Лямбда-функция"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# fff\n",
    "## ffff\n",
    "### fff\n",
    "\n",
    "__ljkelg__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h = lambda w: w**2\n",
    "h(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>digit</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Masha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Kat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Ololosha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pasha</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  digit      name\n",
       "0     1     Masha\n",
       "1     2       Kat\n",
       "2     3  Ololosha\n",
       "3     4    Robert\n",
       "4     5     Pasha"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "X =[[1,2,3,4,5], \n",
    "    ['Masha','Kat', 'Ololosha', 'Robert', 'Pasha' ]]\n",
    "\n",
    "df = pd.DataFrame(X, ['digit', 'name']).T\n",
    "#df.columns = ['digit', 'name']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>digit</th>\n",
       "      <th>name</th>\n",
       "      <th>name_len</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Masha</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Kat</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Ololosha</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Robert</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pasha</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  digit      name  name_len\n",
       "0     1     Masha         5\n",
       "1     2       Kat         3\n",
       "2     3  Ololosha         8\n",
       "3     4    Robert         6\n",
       "4     5     Pasha         5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['name_len'] = df['name'].apply(len)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    sasha\n",
       "1    tasha\n",
       "2    oasha\n",
       "3    basha\n",
       "4    sasha\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['name'].apply(lambda w: w[2] + 'asha')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    sasha\n",
       "1    tasha\n",
       "2    oasha\n",
       "3    basha\n",
       "4    sasha\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def jjj(w):\n",
    "    return w[2] + 'asha'\n",
    "\n",
    "df['name'].apply(jjj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Kat', 'Masha', 'Ololosha', 'Pasha', 'Robert']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = ['Masha','Kat', 'Ololosha', 'Robert', 'Pasha' ]\n",
    "sorted(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'а' < 'я'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'ё' < 'я'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1072, 1103, 1105)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ord('а'), ord('я'), ord('ё')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Kat', 'Masha', 'Pasha', 'Robert', 'Ololosha']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = ['Masha','Kat', 'Ololosha', 'Robert', 'Pasha' ]\n",
    "sorted(x, key=lambda w: len(w))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Чтение файлов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "content = \"\"\"\n",
    "1\n",
    "\n",
    "2\n",
    "3   \n",
    "\n",
    "4\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "FILENAME = \"myfile.txt\"\n",
    "\n",
    "with open(FILENAME, \"w\") as f:\n",
    "    f.write(content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['\\n', '1\\n', '\\n', '2\\n', '3   \\n', '\\n', '4\\n']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(FILENAME, \"r\") as f:\n",
    "    a = f.readlines()   \n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-1\n",
      "-\n",
      "-2\n",
      "-3   \n",
      "-\n",
      "-4\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('-'.join(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('\\n', '1\\n')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = open(FILENAME)\n",
    "a = f.readline()\n",
    "b = f.readline()\n",
    "a, b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['\\n', '2\\n', '3   \\n', '\\n', '4\\n']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = f.readlines()\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle  # позволяет хранить данные в бинарном виде\n",
    "\n",
    "a = [1,2,4, 'Ьфырф']\n",
    "\n",
    "with open('a.pickle', \"wb\") as f:\n",
    "    pickle.dump(a, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 4, 'Ьфырф']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open('a.pickle', \"rb\") as f:\n",
    "    b = pickle.load(f)\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a == b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert a == b, 'Не равно'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "ename": "AssertionError",
     "evalue": "Не равно",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-35-6dd8078134d4>\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[0ma\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Не равно'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m: Не равно"
     ]
    }
   ],
   "source": [
    "assert a == 4, 'Не равно'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# задачки"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_problem(func, test_data):\n",
    "    for inputs, true_answer in test_data:\n",
    "        answer = func(inputs)\n",
    "        assert answer == true_answer, f'Expected {true_answer}, got {answer}. Input: {inputs}'\n",
    "    print(\"OK!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 5)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fizz_buzz(n):\n",
    "    answer = [ ]\n",
    "    for i in range(n):\n",
    "        if i % 3 == 0:\n",
    "            answer.append('Fizz')\n",
    "        \n",
    "    \n",
    "    return answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fizz_buzz(n):\n",
    "    answer = [ ]\n",
    "    for i in range(1, n + 1):\n",
    "        if (i % 3 == 0)&(i % 5 == 0):\n",
    "            answer.append('FizzBuzz')\n",
    "        elif i % 3 == 0:\n",
    "            answer.append('Fizz')\n",
    "        elif i % 5 == 0:\n",
    "            answer.append('Buzz')\n",
    "        else:\n",
    "            answer.append(str(i))\n",
    "    return answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1', '2', 'Fizz', '4', 'Buzz']"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fizz_buzz(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK!\n"
     ]
    }
   ],
   "source": [
    "FIZZ_BUZZ_TESTS_DATA = [\n",
    "    (1, [\"1\"]),\n",
    "    (2, [\"1\", \"2\"]),\n",
    "    (15, [\"1\", \"2\", \"Fizz\", \"4\", \"Buzz\", \"Fizz\", \"7\", \"8\", \"Fizz\", \"Buzz\", \"11\", \"Fizz\", \"13\", \"14\", \"FizzBuzz\"]),\n",
    "]\n",
    "test_problem(fizz_buzz, FIZZ_BUZZ_TESTS_DATA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [1,22,3,4]\n",
    "x[-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def fib(n):\n",
    "    y0 =0\n",
    "    y1 = 1\n",
    "    if n == 1:\n",
    "        return 1\n",
    "    if n == 0:\n",
    "        return 0\n",
    "    for i in range(n-1):\n",
    "        y2 = y1 + y0\n",
    "        y1,y0 = y2,y1\n",
    "    return y2\n",
    "\n",
    "fib(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# фу, O(2^n)\n",
    "def fib(n):\n",
    "    if n == 1:\n",
    "        return 1\n",
    "    if n == 0:\n",
    "        return 0\n",
    "    return fib(n-1) + fib(n-2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fib(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK!\n"
     ]
    }
   ],
   "source": [
    "FIBONACCI_TESTS_DATA = [\n",
    "    (1, 1),\n",
    "    (2, 1),\n",
    "    (3, 2),\n",
    "    (4, 3),\n",
    "    (5, 5),\n",
    "    (10, 55),\n",
    "    (40, 102334155),\n",
    "]\n",
    "test_problem(fib, FIBONACCI_TESTS_DATA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  }
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