PwP - Ćwiczenia _01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d4e3ef30",
   "metadata": {},
   "source": [
    "# Język programowania Python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe0aaf84",
   "metadata": {},
   "source": [
    "Zapoznamy się z słowami kluczowymi:\n",
    "* is, in, or, not, and, import\n",
    "* None, True, False\n",
    "\n",
    "funkcjami wbudowanymi:\n",
    "* print, help, type, dir, id, input\n",
    "* range, len, abs, max, min, pow, round, sum, all, any, chr, ord\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4c513cf",
   "metadata": {},
   "source": [
    "**Python** jest **interpretowanym**, wysokopoziomowym językiem programowania o (**silnym**) **dynamicznym typowaniu** (oraz automatycznej dealokacji pamięci) ogólnego przeznaczenia. Wspiera programowanie w różnych paradygmatach (proceduralne, funkcyjne, obiektowe itd.)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3fb6844",
   "metadata": {},
   "source": [
    "**Dynamiczne typowanie** oznacza, iż możliwa jest zmiana typu wartości przechowywanych w zmiennych w trakcie działania programu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1cecd7fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'int'>\n",
      "<class 'str'>\n",
      "<class 'float'>\n",
      "5.0\n"
     ]
    }
   ],
   "source": [
    "x = 5\n",
    "print(type(x))\n",
    "\n",
    "x = \"and now for sth completely different\"\n",
    "print(type(x))\n",
    "\n",
    "x = 5.0\n",
    "print(type(x))\n",
    "\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf0caa96",
   "metadata": {},
   "source": [
    "Natomiast **typowanie silne** oznacza, że Python nie pozwala automatycznie konwertować typów między sobą w niejawny sposób."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6699c488",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for +: 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[18], line 4\u001b[0m\n\u001b[0;32m      1\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m\n\u001b[0;32m      2\u001b[0m y \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m5\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m----> 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(x \u001b[38;5;241m+\u001b[39m y)\n",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "x = 5\n",
    "y = \"5\"\n",
    "\n",
    "print(x + y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf36874b",
   "metadata": {},
   "source": [
    "Jednakże dla typów numerycznych *float* i *int* taka operacja byłaby możliwa."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43bee474",
   "metadata": {},
   "source": [
    "### The Zen of Python - Easter Egg czy Filozofia Języka?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b9328079",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Zen of Python, by Tim Peters\n",
      "\n",
      "Beautiful is better than ugly.\n",
      "Explicit is better than implicit.\n",
      "Simple is better than complex.\n",
      "Complex is better than complicated.\n",
      "Flat is better than nested.\n",
      "Sparse is better than dense.\n",
      "Readability counts.\n",
      "Special cases aren't special enough to break the rules.\n",
      "Although practicality beats purity.\n",
      "Errors should never pass silently.\n",
      "Unless explicitly silenced.\n",
      "In the face of ambiguity, refuse the temptation to guess.\n",
      "There should be one-- and preferably only one --obvious way to do it.\n",
      "Although that way may not be obvious at first unless you're Dutch.\n",
      "Now is better than never.\n",
      "Although never is often better than *right* now.\n",
      "If the implementation is hard to explain, it's a bad idea.\n",
      "If the implementation is easy to explain, it may be a good idea.\n",
      "Namespaces are one honking great idea -- let's do more of those!\n"
     ]
    }
   ],
   "source": [
    "import this"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ee9621d",
   "metadata": {},
   "source": [
    "## Podstawy składni i semantyki\n",
    "\n",
    "Składnia odnosi się do zasad programowania, na podstawie których język będzie pisany i interpretowany, podczas gdy semantyka to znaczenie zapisanych wyrażeń."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4eaecf04",
   "metadata": {},
   "source": [
    "### Składnia"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba2284c4",
   "metadata": {},
   "source": [
    "#### Indentacja\n",
    "W Pythonie bloki kodu wyznaczane są wcięciami, do których konstrukcji musi być użyty zawsze ten sam znak (**spacja** lub tabulator) i które muszą mieć ten sam rozmiar. Zgodnie z konwencją jeden poziom wcięcia to 4 spacje."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "debff3b1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "2\n",
      "3\n"
     ]
    }
   ],
   "source": [
    "c = 0\n",
    "\n",
    "for i in range(3):\n",
    "    c += 1\n",
    "    print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cc1643e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "c = 0\n",
    "\n",
    "for i in range(3):\n",
    "    c += 1\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bff3d47",
   "metadata": {},
   "source": [
    "Wewnątrz linijki spacje są obojętne, ale po \"**:**\" musi pojawić się wcięcie (chyba, że występuje tylko jeden poziom)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fef8c69e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "x             =        1    +                2\n",
    "print      (\n",
    "                  x\n",
    "           )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "59866d06",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 1 "
     ]
    }
   ],
   "source": [
    "for i in range(3): print(i, end=\" \")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9963592",
   "metadata": {},
   "source": [
    "#### Komentarze i docstringi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b988f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# hasztag pozwala na wprowadzenie komentarza jednolinijkowego\n",
    "\n",
    "\"\"\"\n",
    "tekst pomiędzy\n",
    "3x zwielokrotnionymi cudzysłowami\n",
    "będzie traktowany jako 'komentarz'\n",
    "tzw. docstring\n",
    "czyli 'komentarz dokumentujący' - który często opisuje działanie funkcji, klasy lub modułu\n",
    "\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "5ce65775",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prints the values to a stream, or to sys.stdout by default.\n",
      "\n",
      "  sep\n",
      "    string inserted between values, default a space.\n",
      "  end\n",
      "    string appended after the last value, default a newline.\n",
      "  file\n",
      "    a file-like object (stream); defaults to the current sys.stdout.\n",
      "  flush\n",
      "    whether to forcibly flush the stream.\n"
     ]
    }
   ],
   "source": [
    "# aby wyświetlić docstring\n",
    "print(print.__doc__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b5d44e4",
   "metadata": {},
   "source": [
    "#### Słowa kluczowe / zastrzeżone\n",
    "\n",
    "To identyfikatory, które z góry mają ekreślone znaczenie. Nie należy przypisywać im innych wartości!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "70f8b587",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35\n"
     ]
    }
   ],
   "source": [
    "import keyword\n",
    "\n",
    "# funkcja len() zwraca długość kolekcji\n",
    "\n",
    "print(len(keyword.kwlist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a5583056",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Here is a list of the Python keywords.  Enter any keyword to get more help.\n",
      "\n",
      "False               class               from                or\n",
      "None                continue            global              pass\n",
      "True                def                 if                  raise\n",
      "and                 del                 import              return\n",
      "as                  elif                in                  try\n",
      "assert              else                is                  while\n",
      "async               except              lambda              with\n",
      "await               finally             nonlocal            yield\n",
      "break               for                 not                 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(\"keywords\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c17a08e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The \"pass\" statement\n",
      "********************\n",
      "\n",
      "   pass_stmt ::= \"pass\"\n",
      "\n",
      "\"pass\" is a null operation — when it is executed, nothing happens. It\n",
      "is useful as a placeholder when a statement is required syntactically,\n",
      "but no code needs to be executed, for example:\n",
      "\n",
      "   def f(arg): pass    # a function that does nothing (yet)\n",
      "\n",
      "   class C: pass       # a class with no methods (yet)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(\"pass\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4931983",
   "metadata": {},
   "source": [
    "### Semantyka"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2404aa82",
   "metadata": {},
   "source": [
    "W Pythonie **wszystko jest obiektem** – również typy podstawowe. Typ zmiennej x możemy sprawdizć kożystając z funkcji *type()*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c802702a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'float'>\n"
     ]
    }
   ],
   "source": [
    "x = 1.5\n",
    "\n",
    "print(type(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "35a66efb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['__abs__', '__add__', '__bool__', '__ceil__', '__class__', '__delattr__', '__dir__', '__divmod__', '__doc__', '__eq__', '__float__', '__floor__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__getformat__', '__getnewargs__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__int__', '__le__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__pos__', '__pow__', '__radd__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rmod__', '__rmul__', '__round__', '__rpow__', '__rsub__', '__rtruediv__', '__setattr__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__trunc__', 'as_integer_ratio', 'conjugate', 'fromhex', 'hex', 'imag', 'is_integer', 'real'] "
     ]
    }
   ],
   "source": [
    "# funkcja dir() zwraca listę atrybutów i metod klasy obiektu\n",
    "print(dir(float), end = \" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c83dbf7b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.5\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "# symbol . pozwala się do nich odwołać (również modułów, podmodułów)\n",
    "\n",
    "print(x.real)\n",
    "print(x.is_integer())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4b26628",
   "metadata": {},
   "source": [
    "Każdy obiekt ma trzy właściwości:\n",
    "\n",
    "  * tożsamość id(x)\n",
    "  * typ type(x)\n",
    "  * wartość x\n",
    "    \n",
    "Tożsamość sprawdzamy operatorem <em>is</em>\n",
    "\n",
    "Równość wartości sprawdzamy operatorem <em>==</em>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a9d4d10",
   "metadata": {},
   "source": [
    "Deklarowane przez nas zmienne to wskaźniki, przechowują adres w pamięci."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c5ee7305",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1693017512592\n",
      "1693017512560\n",
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "x = 100000\n",
    "y = 100000\n",
    "\n",
    "print(id(x))\n",
    "print(id(y))\n",
    "\n",
    "print(x == y)\n",
    "print(x is y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91ade9e6",
   "metadata": {},
   "source": [
    "W pewnych przypadkach może nas jednak spotkać zaskoczenie.. jest to wynikiem optymalizacji użycia pamięci dla małych liczb (-5 do 256) oraz krótkiego tekstu bez spacji."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "225baab9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "140719907771176\n",
      "140719907771176\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "x = 1\n",
    "y = 1\n",
    "\n",
    "print(id(x))\n",
    "print(id(y))\n",
    "\n",
    "print(x == y)\n",
    "print(x is y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "048f6e28",
   "metadata": {},
   "source": [
    "### Wbudowane typy zmiennych"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "a6794ead",
   "metadata": {},
   "source": [
    "![typywp.png](attachment:typywp.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2c5a6e8",
   "metadata": {},
   "source": [
    "#### Podstawowe operacje na typach liczbowych"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7cb0d67b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# integer (zmienna liczbowa całkowita)\n",
    "i = 255\n",
    "# alternatywne notacje\n",
    "i = 0xff # szesnastkowa, hexadecimal\n",
    "i = 0o377 # ósemkowa, octal\n",
    "i = 0b11111111 # dwójkowa, binary\n",
    "\n",
    "# float (zmienna zmiennoprzecinkowa)\n",
    "f = 0.25\n",
    "# alternatywna notacja eksponencjalna\n",
    "f = 2.5e-01 # exponent notation\n",
    "\n",
    "# complex (liczby zespolone)\n",
    "c = 3.5 + 0.5j\n",
    "\n",
    "# zmienna nieokreślona None\n",
    "x = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "25c526d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# operacje matematyczne\n",
    "\n",
    "y = i + 1 # dodawanie\n",
    "y = i - 1 # odejmowanie\n",
    "y = i * 1 # mnożenie\n",
    "y = i / 1 # dzielenie\n",
    "y = i % 5 # reszta z dzielenia\n",
    "y = i // 5 # dzielenie całkowite\n",
    "y = i**3 # potęgowanie"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7c2a654",
   "metadata": {},
   "source": [
    "#### Wartości logiczne i operacje na nich"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "fc35ed63",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bool (boolean, wartości logiczne)\n",
    "# True (1) lub False (0)\n",
    "\n",
    "b = True\n",
    "b = i <= 255\n",
    "b = i == 255\n",
    "b = i != 255\n",
    "\n",
    "# operatory logiczne\n",
    "b = i < 0 and i > 255\n",
    "b = i < 0 or i < 255\n",
    "b = (i >= 0 and i < 256) or i % 10 == 5\n",
    "b = not (i >= 0 and i < 10) or i % 10 == 5\n",
    "b = x is None\n",
    "b = x is not None\n",
    "b = 10 in [0, 10, 20, 30]\n",
    "b = 10 not in [0, 1, 2, 3]\n",
    "\n",
    "# funkcje any() i all()\n",
    "b = any([i == 0 , i == 255, i == 300])\n",
    "b = all([i > 0, i == 255, i < 256])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae848c29",
   "metadata": {},
   "source": [
    "#### Kolekcje uporządkowane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "6188f707",
   "metadata": {},
   "outputs": [],
   "source": [
    "# str (string, zmienna tekstowa)\n",
    "# można zamiennie używać \" lub ', zleca się jednak '\n",
    "# zmienne str są immutable, niezmienne\n",
    "\n",
    "s = 'no hejka'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "2669ee5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n\n",
      "hejka\n",
      "akjeh on\n",
      "n ek\n"
     ]
    }
   ],
   "source": [
    "# stringi można indeksować\n",
    "# start (inclusive) : end (exclusive)\n",
    "# start : end : step\n",
    "# w pythonie indeksujemy od 0\n",
    "\n",
    "print(s[0], s[3:], s[::-1], s[::2], sep='\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1d85f55f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'str' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[77], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m s[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mt\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "\u001b[1;31mTypeError\u001b[0m: 'str' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "# ale nie można zmieniać wartości\n",
    "# immutable\n",
    "\n",
    "s[0] = \"t\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "701d30d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "# metoda count klasy str, występuje również w innych typach sekwencyjnych\n",
    "\n",
    "txt = \"Lubię pythona zajęcia z pythona, python\"\n",
    "\n",
    "print(txt.count('python'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "f5ae63bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Imię Nazwisko\n"
     ]
    }
   ],
   "source": [
    "# konkatenacja stringów\n",
    "\n",
    "s1 = 'Imię'\n",
    "s2 = 'Nazwisko'\n",
    "s = s1 + ' ' + s2\n",
    "\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "1de7987f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ImięImięImię\n"
     ]
    }
   ],
   "source": [
    "print(s1 * 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "13dc5ad7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IMIĘ nazwisko\n"
     ]
    }
   ],
   "source": [
    "print(s1.upper() + ' ' + s2.lower())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "e6044ffd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a\n"
     ]
    }
   ],
   "source": [
    "x = 97\n",
    "print(chr(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "edee52a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "80\n"
     ]
    }
   ],
   "source": [
    "x = \"P\"\n",
    "print(ord(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "150b7ef3",
   "metadata": {},
   "source": [
    "#### Formatowanie tekstu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "ec81afa4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Liczba pi: 3.141592653589793, ale z zaokrągleniem 3.14\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "\n",
    "# f-strings, {zmienna:format}\n",
    "\n",
    "pi = math.pi\n",
    "\n",
    "print(f\"Liczba pi: {pi}, ale z zaokrągleniem {pi:.3}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "a713a47f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000-3.141592653589793-xyz\n",
      "      1000\n",
      "01000\n",
      "{binarnie}: 1111101000\n",
      "01750 = #3e8\n",
      "3.1416\n",
      "    3.1416\n",
      "3.1416e+00\n",
      "  3.14E+00\n",
      "--       xyz--\n",
      "--xyz       --\n",
      "--***1000***--\n",
      "-z-3-0.667\n"
     ]
    }
   ],
   "source": [
    "number = 1000\n",
    "text = 'xyz'\n",
    "\n",
    "print(f'{number}-{pi}-{text}')\n",
    "print(f'{number:10d}\\n{number:05d}')\n",
    "print(f'{{binarnie}}: {number:b}')\n",
    "print(f'0{number:o} = #{number:x}')\n",
    "print(f'{pi:0.4f}\\n{pi:10.4f}')\n",
    "print(f'{pi:0.4e}\\n{pi:10.2E}')\n",
    "print(f'--{text:>10}--\\n--{text:<10}--')\n",
    "print(f'--{number:*^10d}--')\n",
    "print(f'-{text[2]}-{len(text)}-{2/3:0.3f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f73ece9",
   "metadata": {},
   "source": [
    "#### Listy i podstawowe operacje na nich"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f6603ec",
   "metadata": {},
   "source": [
    "Elementy listy/krotki mogą być tego samego lub różnych typów, mogą być również referencjami do funkcji."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "592e6baa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['można', 1, 1240.0, 155, None, <built-in function print>]\n"
     ]
    }
   ],
   "source": [
    "l = ['cośtam', 1, 1.24e03, 0x9b, None, print]\n",
    "\n",
    "l[0] = \"można\"\n",
    "\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "3cc4b525",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[162], line 5\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# immutable\u001b[39;00m\n\u001b[0;32m      3\u001b[0m k \u001b[38;5;241m=\u001b[39m (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcośtam\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1.24e03\u001b[39m, \u001b[38;5;241m0x9b\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28mprint\u001b[39m)\n\u001b[1;32m----> 5\u001b[0m k[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnie można\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "\u001b[1;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "# immutable\n",
    "\n",
    "k = ('cośtam', 1, 1.24e03, 0x9b, None, print)\n",
    "\n",
    "k[0] = \"nie można\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed7c7098",
   "metadata": {},
   "source": [
    "Listy - metody append(), extend() oraz reverse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "1dc7ecd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# utworzenie pustej listy\n",
    "\n",
    "l = list()\n",
    "l = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "fa2223fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
     ]
    }
   ],
   "source": [
    "# utworzenie listy od 0 do 9\n",
    "l = list(range(10))\n",
    "\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "23fad059",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "range(stop) -> range object\n",
      "range(start, stop[, step]) -> range object\n",
      "\n",
      "Return an object that produces a sequence of integers from start (inclusive)\n",
      "to stop (exclusive) by step.  range(i, j) produces i, i+1, i+2, ..., j-1.\n",
      "start defaults to 0, and stop is omitted!  range(4) produces 0, 1, 2, 3.\n",
      "These are exactly the valid indices for a list of 4 elements.\n",
      "When step is given, it specifies the increment (or decrement).\n"
     ]
    }
   ],
   "source": [
    "# co to w ogóle jest range? Można również spróbować help(range)\n",
    "print(range.__doc__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "152d1cc4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, '66']\n"
     ]
    }
   ],
   "source": [
    "# dodawanie elementu na koniec metodą append()\n",
    "p = \"66\"\n",
    "\n",
    "l.append(p)\n",
    "\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "5dcafdd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, '66', 10, 11, 12, 13, 14]\n"
     ]
    }
   ],
   "source": [
    "# rozszerzanie o elementy innej kolekcji\n",
    "l.extend(range(10, 15, 1))\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "36351e93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]\n"
     ]
    }
   ],
   "source": [
    "# odwracanie in-place\n",
    "l = list(range(10))\n",
    "l.reverse()\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "8e5aff54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[14, 13, 12, 11, 10, '66', 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "cb95bb6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
     ]
    }
   ],
   "source": [
    "l = l[::-1]\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "d2ade1c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 5]\n"
     ]
    }
   ],
   "source": [
    "# sort vs sorted\n",
    "\n",
    "l = [5, 1, 2]\n",
    "\n",
    "sorted(l)\n",
    "print(l)\n",
    "\n",
    "l.sort() # tylko do list\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "1b8a7e09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['a', 'to była referencja', 'c']\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# mutability\n",
    "l1 = ['a', 'b', 'c']\n",
    "l2 = l1\n",
    "l2[1] = 'to była referencja'\n",
    "\n",
    "print(l1)\n",
    "print(l1 == l2) # id()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "f024ea3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['a', 'b', 'c']\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "l1 = ['a', 'b', 'c']\n",
    "l2 = l1.copy() # lub l2 = l1[:]\n",
    "l2[1] = 'a to inny obiekt'\n",
    "\n",
    "print(l1)\n",
    "print(l1 == l2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "2b884c70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 'a', 'b', 'c', 1, 2]\n"
     ]
    }
   ],
   "source": [
    "l = list(range(3))\n",
    "\n",
    "# przypisanie do pustego slice’a\n",
    "l[1:1] = ['a', 'b', 'c']\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "4c088fb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, ['a', 'b', 'c'], 2]\n"
     ]
    }
   ],
   "source": [
    "l = list(range(3))\n",
    "\n",
    "# vs przypisanie do pozycji 1\n",
    "l[1] = ['a', 'b', 'c']\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "38f22a18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['tak', 'tak', 'tak']\n"
     ]
    }
   ],
   "source": [
    "# metody split i join\n",
    "\n",
    "s = \"tak, tak, tak\"\n",
    "l  = s.split(\", \")\n",
    "\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "c78ae9e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "taktaktak\n"
     ]
    }
   ],
   "source": [
    "print(\"\".join(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "951ba982",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tak, tak, tak\n"
     ]
    }
   ],
   "source": [
    "print(\", \".join(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80a6a0b1",
   "metadata": {},
   "source": [
    "#### Kolekcje nieuporządkowane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "e2c98bd0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1.0, 2, 4.235, 'a', 'b', 'c'}\n"
     ]
    }
   ],
   "source": [
    "# set to kolekcja unikalnych elementów\n",
    "\n",
    "\n",
    "s = {1.0, 'tekst', 4.235}\n",
    "\n",
    "# dodaj pojedynczy element,\n",
    "s.add(2)\n",
    "\n",
    "# dodaj elementy z innej kolekcji\n",
    "s.update(['a', 'b', 'c'])\n",
    "\n",
    "# usuń pojedynczy element\n",
    "s.discard('tekst')\n",
    "\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "9e50f304",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 1, 2, 3}\n"
     ]
    }
   ],
   "source": [
    "# konwersja listy/krotki do zbioru (set)\n",
    "l = [0, 1, 1, 1, 1, 1, 2, 3]\n",
    "s = set(l)\n",
    "\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "5a84312e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 1, 2, 3}\n",
      "frozenset({0, 1, 2, 3})\n"
     ]
    }
   ],
   "source": [
    "# frozenset - immutable\n",
    "fs = frozenset(l)\n",
    "print(s, fs, sep='\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "54b94aff",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = {1, 2, 3, 4, 5, 6}\n",
    "s2 = {4, 5, 6, 7, 8, 9}\n",
    "\n",
    "# suma zbiorów, s1 lub s2\n",
    "union = s1 | s2\n",
    "union = s1.union(s2)\n",
    "\n",
    "# różnica zbiorów, s1 odjąć s2\n",
    "# elementy zbioru s1 nieobecne w s2\n",
    "diff = s1 - s2\n",
    "diff = s1.difference(s2)\n",
    "\n",
    "# przecięcie, s1 i s2\n",
    "# elementy obecne zarówno w s1 jak i s2\n",
    "inter = s1 & s2\n",
    "inter = s1.intersection(s2)\n",
    "\n",
    "# różnica symetryczna, suma - przecięcie\n",
    "# elementy unikalne dla obu zbiorów\n",
    "sym = s1 ^ s2\n",
    "sym = s1.symmetric_difference(s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "9e9cee5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a\n",
      "c\n"
     ]
    }
   ],
   "source": [
    "# dict, dictionary (słownik) to kolekcja\n",
    "# par klucz : wartość, gdzie klucz to\n",
    "# zmienna typu podstawowego lub immutable collection\n",
    "\n",
    "d = dict()\n",
    "d = {}\n",
    "\n",
    "d = {\n",
    "    '1' : 'a',2.0 : ['b', 'b', 'b'],(1, 2) : 'c',10 : 20.5\n",
    "}\n",
    "\n",
    "print(d['1'])\n",
    "print(d[(1,2)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "8c04f2e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1': 'a', 2.0: ['b', 'b', 'b'], (1, 2): 'c', 10: 20.5, 'nowy klucz': 'nowa wartość'}\n"
     ]
    }
   ],
   "source": [
    "# dodajemy nową parę\n",
    "d['nowy klucz'] = 'nowa wartość'\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe3d4a5d",
   "metadata": {},
   "source": [
    "#### Minimum o przyjmowaniu danych od użytkownika"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "66458e82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Podaj swoją cenę: 7\n",
      "7\n",
      "<class 'str'>\n"
     ]
    }
   ],
   "source": [
    "x = input(\"Podaj swoją cenę: \")\n",
    "\n",
    "print(x)\n",
    "print(type(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f722a14",
   "metadata": {},
   "source": [
    "### Wywoływanie skryptów .py z wiersza poleceń (Linux)\n",
    "\n",
    "Skrypt rozpoczynamy od sekwencji znaków Shebang (#!), po której znajduje się ścieżka do interpretera. Uniksowe narzędzie powłokowe **env** pozwala wyszukać jego lokalizacje w zmiennej środowiskowej **$PATH**, co służy przenośność skryptu.\n",
    "\n",
    "            #!/usr/bin/env python\n",
    "            \n",
    "            \n",
    "Wiersz poleceń możemy wywołać kożystając z klawiszy **Ctrl+Alt+T**.\n",
    "\n",
    "Po utworzeniu pliku .py konieczna może być zmiana uprawnień do niego przed uruchomieniem **chmod +x myscript.py.**\n",
    "\n",
    "Teraz możemy wywołać nasz skrypt za pomocą **./myscript.py**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35195674",
   "metadata": {},
   "source": [
    "**Zadanie 0.** Utwórz skrypt *.py* wypisujący na ekranie napis \"Hello World!\". Uruchom go z wierasza poleceń."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00f984e9",
   "metadata": {},
   "source": [
    "**Zadanie 1.** Oblicz procentową zawartość GC w poniższej sekwencji. Wypisz ją na ekranie z dokładnością do drugiego miejsca po przecinku.\n",
    "\n",
    "                ATGCATATGACTCAATGCCCATTAAAAA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcc9ecaa",
   "metadata": {},
   "source": [
    "**Zadanie 2.** Napisz program, który pomiędzy słowa zdania \"Kocham Pythona Kocham Bioinformatykę\" umieszcza wyraz \"bardzo\" i wypisuje je dużymi literami."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abd0356e",
   "metadata": {},
   "source": [
    "**Zadanie 3.** Napisz program, który przyjmuje od użytkownika jego imię oraz nazwisko a następnie wypisuje propozycję jego adresu email w domenie student.uj.edu.pl. Upewnij się że zawiera tylko małe litery."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d56f2d6",
   "metadata": {},
   "source": [
    "**Zadanie 4.** Twój kolega chciałby sprawdzić czy imię jego najlepszego przyjaciela znajduje się na liście zabawnych imion. Najpierw chciałby ją uaktualnić, ale nie potrafi programować i jego kod nie działa. Pomóż mu naprawiając jego kod:\n",
    "\n",
    "names_list = (\"Dill Doe\", \"Chris P. Bacon\", \"Ben Dover\")\n",
    "\n",
    "names_list.append(\"Harry Dixon\")\n",
    "\n",
    "input = input(\"Podaję imię : )\n",
    "\n",
    "b = input in names_list\n",
    "\n",
    "print b"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3da3ce69",
   "metadata": {},
   "source": [
    "**Zadanie tylko jakby komuś bardzo się nudziło na zajęciach.** Zbadaj zawartość modułu *this*, odkoduj zawartą w nim wiadomość."
   ]
  }
 ],
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