{ "metadata": { "name": "", "signature": "sha256:c98f6053669a8fdf1a4d00dbc34d3df4c115195abc417176423fbbace747fc63" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "\u041e\u0431\u044a\u0435\u043a\u0442\u044b \u0438 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0435" ] }, { "cell_type": "code", "collapsed": false, "input": [ "a = [1, 2, 3]\n", "b = a\n", "b[1] = 4\n", "print(a)\n", "print(b)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, 4, 3]\n", "[1, 4, 3]\n" ] } ], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "a = [1, 2, 3]\n", "b = list(a)\n", "b[1] = 4\n", "print(a)\n", "print(b) " ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, 2, 3]\n", "[1, 4, 3]\n" ] } ], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "a = [1, [2, 3]]\n", "b = list(a)\n", "b[1][0] = 4\n", "print(a)\n", "print(b) " ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, [4, 3]]\n", "[1, [4, 3]]\n" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "import copy\n", "a = [1, [2, 3]]\n", "b = copy.copy(a)\n", "b[1][0] = 4\n", "print(a)\n", "print(b) " ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, [4, 3]]\n", "[1, [4, 3]]\n" ] } ], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "import copy\n", "a = [1, [2, 3]]\n", "b = copy.deepcopy(a)\n", "b[1][0] = 4\n", "print(a)\n", "print(b) " ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, [2, 3]]\n", "[1, [4, 3]]\n" ] } ], "prompt_number": 5 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "if" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import math" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "def sample_function(t):\n", " if t < -2:\n", " return -2\n", " elif -2 <= t < 0:\n", " return t\n", " elif t == 0:\n", " return 0\n", " else:\n", " return t * math.sin(1 / t)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "sample_function(-5)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "-2" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "sample_function(-1)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "-1" ] } ], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "sample_function(0)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "0" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "sample_function(1)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "0.8414709848078965" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "%pylab inline" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "t = arange(-5, 5, 0.01)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "grid()\n", "plot(t, list(map(sample_function, t)))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ "[]" ] }, { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEACAYAAAC9Gb03AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text": [ "" ] } ], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "x = 1 if True else 2\n", "x" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "1" ] } ], "prompt_number": 10 }, { "cell_type": "code", "collapsed": false, "input": [ "x = 1 if False else 2\n", "x" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 11, "text": [ "2" ] } ], "prompt_number": 11 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "for" ] }, { "cell_type": "code", "collapsed": false, "input": [ "a = [[1, 2], [3, 4]]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "for x in a:\n", " for y in x:\n", " print(y)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1\n", "2\n", "3\n", "4\n" ] } ], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "for x, y in a:\n", " print(x, y)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1 2\n", "3 4\n" ] } ], "prompt_number": 3 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "\u0424\u0443\u043d\u043a\u0446\u0438\u0438" ] }, { "cell_type": "code", "collapsed": false, "input": [ "def f(a, b, c):\n", " print(a, b, c, sep=\", \")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, 2, 3)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, c=3, b=2)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "a = [1, 2, 3]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "f(a)" ], "language": "python", "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "f() missing 2 required positional arguments: 'b' and 'c'", "output_type": "pyerr", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mTypeError\u001b[0m: f() missing 2 required positional arguments: 'b' and 'c'" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "f(*a)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "a = [2, 3]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, *a)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "d = {'c': 3, 'b': 2, 'a': 1}" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "f(**d)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 10 }, { "cell_type": "code", "collapsed": false, "input": [ "def f(a, b=2, c=3):\n", " print(a, b, c, sep=\", \")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 2, 3\n" ] } ], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, 4)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 4, 3\n" ] } ], "prompt_number": 13 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, 4, 5)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1, 4, 5\n" ] } ], "prompt_number": 14 }, { "cell_type": "code", "collapsed": false, "input": [ "def f(a, b=[]):\n", " b.append(a)\n", " print(b)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 15 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1]\n" ] } ], "prompt_number": 16 }, { "cell_type": "code", "collapsed": false, "input": [ "f(2)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, 2]\n" ] } ], "prompt_number": 17 }, { "cell_type": "code", "collapsed": false, "input": [ "f(3)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[1, 2, 3]\n" ] } ], "prompt_number": 18 }, { "cell_type": "code", "collapsed": false, "input": [ "def f(*args, **kwargs):\n", " print(args, kwargs, sep=\", \")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 19 }, { "cell_type": "code", "collapsed": false, "input": [ "f(1, 2, 3, x=4, y=5)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "(1, 2, 3), {'y': 5, 'x': 4}\n" ] } ], "prompt_number": 20 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "str.format" ] }, { "cell_type": "code", "collapsed": false, "input": [ "name = 'Alice'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "\"Hello, {0}\".format(name)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 2, "text": [ "'Hello, Alice'" ] } ], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "\"Hello, {}\".format(name)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "'Hello, Alice'" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "name1 = 'Bob'\n", "name2 = 'Malory'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "\"Hello, {} and {}\".format(name1, name2)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "'Hello, Bob and Malory'" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "\"{0}cad{0}\".format(\"abra\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "'abracadabra'" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "\"{0.real} + {0.imag}i\".format(1 + 2j)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ "'1.0 + 2.0i'" ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "\"Hello, {name}\".format(name=\"Guido\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 8, "text": [ "'Hello, Guido'" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "\"Hello, {name[0]} and {name[1]}\".format(name=[\"Jack\", \"Jill\"])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ "'Hello, Jack and Jill'" ] } ], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "a = 1\n", "b = 2\n", "\"{a} + {b} = {}\".format(a + b, **locals())" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "'1 + 2 = 3'" ] } ], "prompt_number": 10 } ], "metadata": {} } ] }