Where to Go Next
You can now write, run, test and maintain a real Python program, read other people's code, and handle files, data, errors and the network. This page maps the next steps, in this catalogue and beyond, depending on what you want Python for. There is no single right order; pick the path that matches the reason you started.
Think of the trail map at the end of a first trail: several marked paths, all starting from where you are standing now.
Keep Your Code Safe
The most useful next step, whatever you do after it, is version control. Git for Beginners teaches how to keep a history of every change to your scripts, undo a mistake without fear, and share a project with other people. It takes a few evenings, and every later project benefits from it.
Build Services
If you want to build what answers requests, rather than send them, Backend Deep Dive uses Python to build a complete service, with a database, background jobs and the reliability work this book only touched in Chapter 10. The language is the one you now know. One small difference: its outgoing requests use a package called httpx, whose basic calls read almost exactly like requests.
Data and Machine Learning
If you came here from Machine Learning from Zero, you now have the "Python first" that book pointed to. The next step on that path is a pair of libraries: NumPy, for fast work with large arrays of numbers, and pandas, for tables of data. Both are installed with pip like any other package, and both assume exactly the lists, dictionaries, functions and files this book taught. A Machine Learning Deep Dive is on this catalogue's roadmap, meant to build on them.
How Software Is Made
If you want to understand the work around the code, how teams plan, review, test and ship software, Software Development from Zero covers the whole discipline without assuming a language, and now every example in it will read as something you could actually build.
Practice
The best second program is one you need. Pick one annoying task in your own life this week, renaming a folder of photos, totalling a spreadsheet, checking a website for a change, and automate it. It will take longer than doing the task by hand, once. After that it will not, and you will have learned more from it than from any further chapter.
- "I need another beginner course before I can build anything real." You can write useful programs now. The next courses deepen what you can do; they are not a gate.
- "A second programming language should be next." A second real project in Python teaches more than a second language, and the next language will be faster to learn for it.
- "Backend and data science are separate worlds." Both start from exactly the Python you now have, and many people work in both.
- A clear next step keeps the momentum going after the last page, which is where many learners stall.
- The deeper books in this catalogue now open without a language barrier in front of them.
Knowledge Check
You want to keep a history of changes to your scripts and undo mistakes. Which course fits?
- Git for Beginners, on version control
- Backend Deep Dive, on building services
- Machine Learning from Zero, on models
- APIs for Beginners, on web services
What does the machine-learning path add next, after this book?
- A new programming language designed for data
- A different way of installing packages than pip
- The NumPy and pandas libraries, used from Python
- A rewrite of everything in this book using classes
What does the page say makes the best second program?
- A copy of the complete program from Chapter 12
- One that automates a task you actually need done
- The largest program you can think of
- A program written in a second language
Why does Backend Deep Dive mention httpx?
- Because requests does not work in Backend Deep Dive
- Because httpx is a different programming language
- Because httpx replaces Python's standard library
- It uses httpx for requests, and its basic calls read like requests
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