Automatice las cosas aburridas con la programación en Python

This lecture explains what programming is good for, even if you don't intend to become a software engineer. At the end of this lecture, you'll be able to download and install Python and be ready to learn to code.

This quiz is here just to ensure you know about the website where you can find the Automate the Boring Stuff with Python book for free: https://automatetheboringstuff.com.

You don't need to purchase the book, and you can read it online if you want more information on the topics in this course.

The student will learn how to put values and operators together to form expressions, the most basic instruction type in Python.

Now that you've done some basic instructions in the interactive shell, let's use the file editor to write a complete program.

You've made Python execute instructions, now learn how to make Python choose which instructions to execute.

The if/else statements are the basic instruction for letting your Python programs make decisions.

Loops allow your program to execute the same code over and over again.

The while loop will execute the same code over and over as long as some condition is true, but for loops allow you to execute a set number of iterations of a loop.

You don't have to write every bit of code yourself. Python comes with several functions that your program can call to leverage the code that others have written.

You aren't limited to the functions that come with Python. You can define your own functions using the def statement. Grouping code into functions helps make your programs shorter and easier to debug.

Functions also introduce the concept of scopes. Learn the difference between global scope and local scopes for variables.

Instead of crashing, you can have your programs gracefully handle errors as they come up.

You've learned several basic programming concepts. Let's apply them to make a simple "Guess the Number" game.

Lists are values that themselves can contain multiple values. Learn how lists can expand your programs' capabilities.

There are several instructions that can be used with lists. This lecture introduces multiple assignment and revisits for loops.

You don't have to write basic operations from scratch. Instead, learn about the methods that the list data type already comes with.

Most of the things you've learned about lists also apply to strings. Two for one!

Dictionaries also can contain multiple values. By using key-value pairs, you can begin to organize large amounts of data.

Dictionaries and lists can contain multiple values, including other dictionaries and lists. Combining them together you can organize your data into data structures.

There's much more to strings than concatenating and printing them. This lecture covers the other ways that strings can be represented in your Python code and why you would use these alternate forms.

There are lots of useful and common things you'll want to do with strings, but you don't have to write the code to do them yourself. Python comes with string methods for many basic operations.

String concatenation can become a mess of characters that makes your code hard to read. String formatting offers a simpler way to put strings together.

Once your programs are finished, you won't always want to launch IDLE every time you want to run them. This lecture covers how to create shortcuts for your programs on Windows. Mac and Linux are covered in the course notes.

Regular expressions offer a way to not only search for text, but to search for patterns of text. This is a large step in increasing the power of your programs.

In this lesson, you learn how the pipe regex character allows you to search for one of multiple patterns.

In this lesson, you'll learn how to find repeating patterns and know the difference between regular expressions that do greedy-matching and nongreedy-matching.

While the familiar search() method returns the first match of the regex's pattern, the findall() method returns all matches of the pattern. This lesson also explores character classes: a handy shortcut for specifying alternatives in regex pattern.

The regex dot-star is a common "catch all" pattern that you can use in your regular expressions. This lesson also explores matching patterns at the start or end of a string.

Regular expressions can not only find text patterns, but can also perform fin-and-replace for text patterns. The sub() method lets us make these text substitutions.

At this point, we'll combine our knowledge of regular expressions to create a script that can pull phone numbers and email addresses out of a document.

Files are stored in a hierarchical system of folders on your hard drive. In this lesson, you'll learn how to refer to specific files through absolute and relative file paths.

Python lets you write out text to files and read text in from files. This allows you to have data from your programs persist even after they've shut down.

Python can copy, move, and rename files with your given criteria much faster than you could do this by dragging file icons in a File Explorer program. This lesson covers functions to perform basic file operations.

Writing scripts to delete files can be a useful, but dangerous, feature to add to your programs. This lesson teaches you how you can keep bugs in your programs from causing any real damage.

"Walking a directory tree" is performing file operations not just on every file in a folder, but every file in every subfolder of that folder, and every subfolder of those subfolders, and so on. Normally this requires learning about recursion, but Python's os.walk() function makes this easy.

Assertions allow you to add "sanity checks" to your code. They won't fix bugs, but they will detect them early on and make the fix easier.

It's tempting to just add print() calls to help debug your programs, but Python's logging module offers a more powerful and convenient way to display debugging information.

All software developers eventually write bugs into their programs. The debugger is the main tool for finding and fixing bugs in every programmer's toolbox.

In this lesson, you'll learn about Python's webbrowser module. Although it's limited to opening up browser windows, this lesson explores how this can be used in a handy map script.

Being on the computer often means being on the internet. In this lesson, you'll learn how to use the Requests module to download files from the web.

While regular expressions are good for general text, the HTML-formatted text that make up the web pages your programs can download requires something more specific. The Beautiful Soup module has functions are locating information on a web page and extracting it for your programs.

The Selenium module provides the ultimate web scraping tool: it launches a browser that is controllable from your Python code.

Excel spreadsheets can be read just like any other file. In this lesson, you'll use the OpenPyXL module to extract data from spreadsheets.

This lesson continues with the OpenPyXL module to create or edit Excel spreadsheets.

PDFs are a ubiquitous format for reports and business information. In this lesson you'll learn how to make your Python programs interact with PDF files.

Python can read and modify Word documents, including Word's styles and text-formatting features.

Your Python scripts can automatically send out emails. This is a great for adding a notification feature to your programs so you can leave them running while you're away from your computer.

Python scripts can also log in to your email accounts for you to check your inbox and retrieve messages on your behalf.