{ "cells": [ { "cell_type": "markdown", "id": "e89d9f25", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Documenting Functions\n", "#### CS 65: Introduction to Computer Science I" ] }, { "attachments": { "help.png": { "image/png": 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" } }, "cell_type": "markdown", "id": "46253128", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## The `help()` function\n", "\n", "Python provides a built-in `help()` function that shows you how to use other functions. You can check it out in the interactive shell in Thonny like this:\n", "\n", "

\n", "

\n", "\n", "
\n", "

\n" ] }, { "cell_type": "markdown", "id": "1fc679d3", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "Go ahead and try it yourself on other functions we've used.\n", "\n", "To use it with a method, you need to use dot notation with an appropriate object, but as above, just use the name and not parentheses." ] }, { "cell_type": "code", "execution_count": 4, "id": "89da1188", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on built-in function index:\n", "\n", "index(value, start=0, stop=9223372036854775807, /) method of builtins.list instance\n", " Return first index of value.\n", " \n", " Raises ValueError if the value is not present.\n", "\n" ] } ], "source": [ "help([].index)" ] }, { "cell_type": "markdown", "id": "0b6df65f", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Docstrings\n", "\n", "You can (and should!) support this with your functions too.\n", "\n", "To do it, add a __docstring__, a multiline comment starting as the first line in your function.\n", "\n", "Things typically included:\n", "* a description of the function's purpose\n", "* a description of each parameter - so that they know what to pass as arguments\n", "* a description of the return value, if any - so they know how to use what they get back" ] }, { "cell_type": "code", "execution_count": 5, "id": "c635704b", "metadata": {}, "outputs": [], "source": [ "def f_to_c(fahrenheit_temp):\n", " \"\"\"\n", " Convert a temperature from Fahrenheit to its Celsius equivalent.\n", " \n", " Paremeters:\n", " fahrenheit_temp: a float, the Fahrenheit temperature to be converted\n", " \n", " Returns:\n", " a float, the temperature converted into Celsius\n", " \"\"\"\n", " celsius_temp = (fahrenheit_temp-32)*(5/9)\n", " return celsius_temp" ] }, { "cell_type": "code", "execution_count": 6, "id": "da959e3a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function f_to_c in module __main__:\n", "\n", "f_to_c(fahrenheit_temp)\n", " Convert a temperature from Fahrenheit to its Celsius equivalent.\n", " \n", " Paremeters:\n", " fahrenheit_temp: a float, the Fahrenheit temperature to be converted\n", " \n", " Returns:\n", " a float, the temperature converted into Celsius\n", "\n" ] } ], "source": [ "help(f_to_c)" ] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }