notebooks/Introduction_to_Python_3_I_O_and_Modules_chapter.ipynb

{"nbformat": 4, "nbformat_minor": 0, "metadata": {"colab": {"name": "Introduction_to_Python_3_I_O_and_Modules_chapter.ipynb", "provenance": [], "collapsed_sections": ["0ZEC4V3pjalH", "FrOuZWcdbkyh", "23NhvjOzSlu4", "Zb4bybUiS3qz", "At7-_WM6bn6A", "xFAS-L5uZtff", "IyTNBT8sh-UE", "8USdvrcJvk9n", "PNT4q5Ks7v79", "xNpgmyOd0gHR", "iPp6yJhCApcR", "vDyUpa7_L54U", "dRtVOqsBC4AJ", "v3CGE72REsXJ"]}, "kernelspec": {"name": "python3", "display_name": "Python 3"}}, "cells": [{"cell_type": "markdown", "metadata": {"id": "1Ycy34VcX4lu"}, "source": ["# Introduction to Python 3: I/O and Modules\n", "## Luca de Alfaro\n", "Copyright Luca de Alfaro, 2018-21.  CC-BY-NC License.\n"]}, {"cell_type": "markdown", "metadata": {"id": "df34bcac19d3dc0a", "colab_type": "text"}, "source": "\nPrepared on: Tue Aug  3 11:57:09 2021\n\nThis is a book chapter; it is not a homework assignment.  \nDo not submit it as a solution to a homework assignment; you would receive no credit.\n"}, {"cell_type": "markdown", "metadata": {"id": "iPp6yJhCApcR"}, "source": ["## Print, and file input/output"]}, {"cell_type": "markdown", "metadata": {"id": "JlcDQwzfp3xD"}, "source": ["We have seen that the `print()` function takes any number of arguments,\n", "and prints them with intervening spaces:\n"]}, {"cell_type": "code", "metadata": {"id": "LR3MyRgwAuAT"}, "source": ["print(\"I have\", 3, 'chicken')\n"], "execution_count": 1, "outputs": [{"output_type": "stream", "text": ["I have 3 chicken\n"], "name": "stdout"}]}, {"cell_type": "markdown", "metadata": {"id": "S99Z7Mv-p6k-"}, "source": ["We can also use `{}` and `.format()` to specify a string with `{}` holes, \n", "which are filled by the arguments of `.format()`: \n"]}, {"cell_type": "code", "metadata": {"id": "pJNS96GMA71h"}, "source": ["print(\"I have {} chicken\".format(3))\n", "print(\"{} is divisible by {}\".format(10, 2))\n"], "execution_count": 2, "outputs": [{"output_type": "stream", "text": ["I have 3 chicken\n", "10 is divisible by 2\n"], "name": "stdout"}]}, {"cell_type": "markdown", "metadata": {"id": "UNNem9yJqD8M"}, "source": ["You can also use formatting options to specify the number of \n", "digits to print for floating point numbers, etc. \n"]}, {"cell_type": "code", "metadata": {"id": "GZNGrOqfBO5J"}, "source": ["print(\"A gazillion is {:.2f}% less than a bazillion\".format(15.67980))\n"], "execution_count": 3, "outputs": [{"output_type": "stream", "text": ["A gazillion is 15.68% less than a bazillion\n"], "name": "stdout"}]}, {"cell_type": "markdown", "metadata": {"id": "KFV11_h6qIQf"}, "source": ["For file input output, you can open files for read and for write\n", "like this, except that in a colab notebook, it's a little bit more complicated\n", "because we don't have access to the local file system. \n"]}, {"cell_type": "code", "metadata": {"id": "pkH3a2xEBxMC"}, "source": ["with open('myfile', 'w') as f:\n", "    f.write(\"hello\")\n"], "execution_count": 4, "outputs": []}, {"cell_type": "markdown", "metadata": {"id": "rCtXSuUmqL86"}, "source": ["    \n", "We don't need to close the file; it is closed as soon as we go out of the \n", "scope of the with statement."]}, {"cell_type": "code", "metadata": {"id": "iK0t68PzCTTs"}, "source": ["with open('myfile') as f:\n", "    s = f.read() # This reads the file in a single shot\n", "print(s)\n"], "execution_count": 5, "outputs": [{"output_type": "stream", "text": ["hello\n"], "name": "stdout"}]}, {"cell_type": "markdown", "metadata": {"id": "h5MdOSz-qRhM"}, "source": ["You can also read files one line at a time by iterating over them:\n"]}, {"cell_type": "code", "metadata": {"id": "MVuuYwryCb-c"}, "source": ["with open('mylongfile', 'w') as f:\n", "    f.write('hello\\n')\n", "    f.write('there!\\n')\n", "with open('mylongfile') as g:\n", "    for s in g:\n", "        print(s)\n"], "execution_count": 6, "outputs": [{"output_type": "stream", "text": ["hello\n", "\n", "there!\n", "\n"], "name": "stdout"}]}, {"cell_type": "markdown", "metadata": {"id": "vDyUpa7_L54U"}, "source": ["## Importing modules"]}, {"cell_type": "markdown", "metadata": {"id": "M5i18N9zqVjH"}, "source": ["Python libraries are organized in modules. \n", "You need to import them before using them. \n"]}, {"cell_type": "code", "metadata": {"id": "5wYw6n_5L98R"}, "source": ["import math\n", "math.sqrt(3.)\n"], "execution_count": 7, "outputs": [{"output_type": "execute_result", "data": {"text/plain": ["1.7320508075688772"]}, "metadata": {"tags": []}, "execution_count": 7}]}, {"cell_type": "markdown", "metadata": {"id": "6heGK8AIqYve"}, "source": ["If you like, you can also import individual functions from libraries.\n"]}, {"cell_type": "code", "metadata": {"id": "ptW6o8nZMI3v"}, "source": ["from math import sqrt as square_root\n", "square_root(2.)\n"], "execution_count": 8, "outputs": [{"output_type": "execute_result", "data": {"text/plain": ["1.4142135623730951"]}, "metadata": {"tags": []}, "execution_count": 8}]}, {"cell_type": "markdown", "metadata": {"id": "jRH24PaU-iso"}, "source": ["One of the things that makes Python great is the huge set of modules that are available for it.  You can look at https://docs.python.org/3/library/ for information about the Python standard library, but there is a very large number of modules besides the standard library.  The general rule is, before you try to implement something, look at whether there is a module available that does (part of) what you want to do."]}]}