How to learn python

Python For Beginners

Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It’s also easy for beginners to use and learn, so jump in!

Installing

Installing Python is generally easy, and nowadays many Linux and UNIX distributions include a recent Python. Even some Windows computers (notably those from HP) now come with Python already installed. If you do need to install Python and aren’t confident about the task you can find a few notes on the BeginnersGuide/Download wiki page, but installation is unremarkable on most platforms.

Learning

Before getting started, you may want to find out which IDEs and text editors are tailored to make Python editing easy, browse the list of introductory books, or look at code samples that you might find helpful.

There is a list of tutorials suitable for experienced programmers on the BeginnersGuide/Tutorials page. There is also a list of resources in other languages which might be useful if English is not your first language.

The online documentation is your first port of call for definitive information. There is a fairly brief tutorial that gives you basic information about the language and gets you started. You can follow this by looking at the library reference for a full description of Python’s many libraries and the language reference for a complete (though somewhat dry) explanation of Python’s syntax. If you are looking for common Python recipes and patterns, you can browse the ActiveState Python Cookbook

Looking for Something Specific?

If you want to know whether a particular application, or a library with particular functionality, is available in Python there are a number of possible sources of information. The Python web site provides a Python Package Index (also known as the Cheese Shop, a reference to the Monty Python script of that name). There is also a search page for a number of sources of Python-related information. Failing that, just Google for a phrase including the word »python» and you may well get the result you need. If all else fails, ask on the python newsgroup and there’s a good chance someone will put you on the right track.

Frequently Asked Questions

If you have a question, it’s a good idea to try the FAQ, which answers the most commonly asked questions about Python.

Looking to Help?

If you want to help to develop Python, take a look at the developer area for further information. Please note that you don’t have to be an expert programmer to help. The documentation is just as important as the compiler, and still needs plenty of work!

The PSF

The Python Software Foundation is the organization behind Python. Become a member of the PSF and help advance the software and our mission.

Beginner’s Guide to Python

New to programming? Python is free and easy to learn if you know where to start! This guide will help you to get started quickly.

New to Python?

Read BeginnersGuide/Overview for a short explanation of what Python is.

Getting Python

Next, install the Python 3 interpreter on your computer. This is the program that reads Python programs and carries out their instructions; you need it before you can do any Python programming. Mac and Linux distributions may include an outdated version of Python (Python 2), but you should install an updated one (Python 3). See BeginnersGuide/Download for instructions to download the correct version of Python.

There are also Python interpreter and IDE bundles available, such as Thonny. Other options can be found at IntegratedDevelopmentEnvironments.

At some stage, you’ll want to edit and save your program code. Take a look at HowToEditPythonCode for some advice and recommendations.

Learning Python

Next, read a tutorial and try some simple experiments with your new Python interpreter.

If you have never programmed before, see BeginnersGuide/NonProgrammers for a list of suitable tutorials.

If you have previous programming experience, consult BeginnersGuide/Programmers, which lists more advanced tutorials.

If English isn’t your first language, you might be more comfortable with a tutorial that’s been translated into your language. Consult python.org’s list of Non-English resources.

Most tutorials assume that you know how to run a program on your computer. If you are using Windows and need help with this, see How do I Run a Program Under Windows.

Some sites offer in-browser coding for those who want to learn Python:

please keep this list alphabetized

Dataquest for Python for data science.

HackInScience free and open source platform.

Print a cheat sheet of the most important Python features and post it to your office wall until you know the basics well.

Once you have read a tutorial, you can browse through Python’s online documentation. It includes a tutorial that might come in handy, a Library Reference that lists all of the modules that come standard with Python, and the Language Reference for a complete (if rather dry) explanation of Python’s syntax.

When you are ready to write your first program, you will need a text editor or an IDE. If you don’t want to use Thonny or something more advanced, then you can use IDLE, which is bundled with Python and supports extensions.

Need Help?

Need help with any of this? Read BeginnersGuide/Help for mailing lists and newsgroups.

Most Python books will include an introduction to the language; see IntroductoryBooks for suggested titles.

Consult BeginnersGuide/Examples for small programs and little snippets of code that can help you learn.

Or, if you prefer to learn Python through listening to a lecture, you can attend a training course or even hire a trainer to come to your company. Consult the PythonEvents page to see if any training courses are scheduled in your area and the PythonTraining page for a list of trainers.

Teachers can join the EDU-SIG, a mailing list for discussion of Python’s use in teaching at any level ranging from K-12 up to university.

11 Beginner Tips for Learning Python Programming

Table of Contents

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: 11 Beginner Tips for Learning Python

We are so excited that you have decided to embark on the journey of learning Python! One of the most common questions we receive from our readers is “What’s the best way to learn Python?”

I believe that the first step in learning any programming language is making sure that you understand how to learn. Learning how to learn is arguably the most critical skill involved in computer programming.

Why is knowing how to learn so important? The answer is simple: as languages evolve, libraries are created, and tools are upgraded. Knowing how to learn will be essential to keeping up with these changes and becoming a successful programmer.

In this article, we will offer several learning strategies that will help jump start your journey of becoming a rockstar Python programmer!

Free Download: Get a sample chapter from Python Basics: A Practical Introduction to Python 3 to see how you can go from beginner to intermediate in Python with a complete curriculum, up-to-date for Python 3.8.

Make It Stick

Here are some tips to help you make the new concepts you are learning as a beginner programmer really stick:

Tip #1: Code Everyday

Consistency is very important when you are learning a new language. We recommend making a commitment to code every day. It may be hard to believe, but muscle memory plays a large part in programming. Committing to coding everyday will really help develop that muscle memory. Though it may seem daunting at first, consider starting small with 25 minutes everyday and working your way up from there.

Check out the First Steps With Python Guide for information on setup as well as exercises to get you started.

Tip #2: Write It Out

As you progress on your journey as a new programmer, you may wonder if you should be taking notes. Yes, you should! In fact, research suggests that taking notes by hand is most beneficial for long-term retention. This will be especially beneficial for those working towards the goal of becoming a full-time developer, as many interviews will involve writing code on a whiteboard.

Once you start working on small projects and programs, writing by hand can also help you plan your code before you move to the computer. You can save a lot of time if you write out which functions and classes you will need, as well as how they will interact.

Tip #3: Go Interactive!

Whether you are learning about basic Python data structures (strings, lists, dictionaries, etc.) for the first time, or you are debugging an application, the interactive Python shell will be one of your best learning tools. We use it a lot on this site too!

To use the interactive Python shell (also sometimes called a “Python REPL”), first make sure Python is installed on your computer. We’ve got a step-by-step tutorial to help you do that. To activate the interactive Python shell, simply open your terminal and run python or python3 depending on your installation. You can find more specific directions here.

Now that you know how to start the shell, here are a few examples of how you can use the shell when you are learning:

Learn what operations can be performed on an element by using dir():

The elements returned from dir() are all of the methods (i.e. actions) that you can apply to the element. For example:

Notice that we called the upper() method. Can you see what it does? It makes all of the letters in the string uppercase! Learn more about these built-in methods under “Manipulating strings” in this tutorial.

Learn the type of an element:

Use the built-in help system to get full documentation:

Import libraries and play with them:

Run shell commands:

Tip #4: Take Breaks

When you are learning, it is important to step away and absorb the concepts. The Pomodoro Technique is widely used and can help: you work for 25 minutes, take a short break, and then repeat the process. Taking breaks is critical to having an effective study session, particularly when you are taking in a lot of new information.

Breaks are especially important when you are debugging. If you hit a bug and can’t quite figure out what is going wrong, take a break. Step away from your computer, go for a walk, or chat with a friend.

In programming, your code must follow the rules of a language and logic exactly, so even missing a quotation mark will break everything. Fresh eyes make a big difference.

Tip #5: Become a Bug Bounty Hunter

Speaking of hitting a bug, it is inevitable once you start writing complex programs that you will run into bugs in your code. It happens to all of us! Don’t let bugs frustrate you. Instead, embrace these moments with pride and think of yourself as a bug bounty hunter.

When debugging, it is important to have a methodological approach to help you find where things are breaking down. Going through your code in the order in which it is executed and making sure each part works is a great way to do this.

Make It Collaborative

Once things start to stick, expedite your learning through collaboration. Here are some strategies to help you get the most out of working with others.

Tip #6: Surround Yourself With Others Who Are Learning

Though coding may seem like a solitary activity, it actually works best when you work together. It is extremely important when you are learning to code in Python that you surround yourself with other people who are learning as well. This will allow you to share the tips and tricks you learn along the way.

Don’t worry if you don’t know anyone. There are plenty of ways to meet others who are passionate about learning Python! Find local events or Meetups or join PythonistaCafe, a peer-to-peer learning community for Python enthusiasts like you!

Tip #7: Teach

It is said that the best way to learn something is to teach it. This is true when you are learning Python. There are many ways to do this: whiteboarding with other Python lovers, writing blog posts explaining newly learned concepts, recording videos in which you explain something you learned, or simply talking to yourself at your computer. Each of these strategies will solidify your understanding as well as expose any gaps in your understanding.

Tip #8: Pair Program

Pair programming is a technique that involves two developers working at one workstation to complete a task. The two developers switch between being the “driver” and the “navigator.” The “driver” writes the code, while the “navigator” helps guide the problem solving and reviews the code as it is written. Switch frequently to get the benefit of both sides.

Pair programming has many benefits: it gives you a chance to not only have someone review your code, but also see how someone else might be thinking about a problem. Being exposed to multiple ideas and ways of thinking will help you in problem solving when you got back to coding on your own.

Tip #9: Ask “GOOD” Questions

People always say there is no such thing as a bad question, but when it comes to programming, it is possible to ask a question badly. When you are asking for help from someone who has little or no context on the problem you are trying to solve, its best to ask GOOD questions by following this acronym:

Good questions can save a lot of time. Skipping any of these steps can result in back-and-forth conversations that can cause conflict. As a beginner, you want to make sure you ask good questions so that you practice communicating your thought process, and so that people who help you will be happy to continue helping you.

Make Something

Most, if not all, Python developers you speak to will tell you that in order to learn Python, you must learn by doing. Doing exercises can only take you so far: you learn the most by building.

Tip #10: Build Something, Anything

For beginners, there are many small exercises that will really help you become confident with Python, as well as develop the muscle memory that we spoke about above. Once you have a solid grasp on basic data structures (strings, lists, dictionaries, sets), object-oriented programming, and writing classes, it’s time to start building!

What you build is not as important as how you build it. The journey of building is truly what will teach you the most. You can only learn so much from reading Real Python articles and courses. Most of your learning will come from using Python to build something. The problems you will solve will teach you a lot.

There are many lists out there with ideas for beginner Python projects. Here are some ideas to get you started:

If you find it difficult to come up with Python practice projects to work on, watch this video. It lays out a strategy you can use to generate thousands of project ideas whenever you feel stuck.

Tip #11: Contribute to Open Source

In the open-source model, software source code is available publicly, and anyone can collaborate. There are many Python libraries that are open-source projects and take contributions. Additionally, many companies publish open-source projects. This means you can work with code written and produced by the engineers working in these companies.

Contributing to an open-source Python project is a great way to create extremely valuable learning experiences. Let’s say you decide to submit a bug fix request: you submit a “pull request” for your fix to be patched into the code.

Next, the project managers will review your work, providing comments and suggestions. This will enable you to learn best practices for Python programming, as well as practice communicating with other developers.

For additional tips and tactics that will help you break into the open-source world, check out the video embedded below:

Go Forth and Learn!

Now that you have these strategies for learning, you are ready to begin your Python journey! Find Real Python’s Beginners Roadmap for Learning here! We also offer a beginner’s level Python course, which uses interesting examples to help you learn programming and web development.

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: 11 Beginner Tips for Learning Python

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About Krishelle Hardson-Hurley

After 6 years of teaching high school math, Krishelle switched careers and now works as a Site Reliability Engineer at Dropbox in San Francisco, CA.

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What Do You Think?

What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment below and let us know.

Commenting Tips: The most useful comments are those written with the goal of learning from or helping out other students. Get tips for asking good questions and get answers to common questions in our support portal. Looking for a real-time conversation? Visit the Real Python Community Chat or join the next “Office Hours” Live Q&A Session. Happy Pythoning!

Related Tutorial Categories: basics python

How to Learn Python (Step-By-Step) in 2022

Why Should You Learn Python?

Python is one of the most popular and in-demand programming languages in the world, and it’s here to stay.

But what’s the best way to learn Python?

That can be difficult and painful to figure out. Unfortunately, I know this from experience.

A little over a decade ago, I was just a college graduate with a history degree. I then became a machine learning engineer, data science consultant, and now CEO of Dataquest.

If I could do everything over, I would follow the steps I’m going to share with you in this article. It would have fast-tracked my career, saved me thousands of hours, and prevented a lot of stress.

Let’s get started.

Is Python Really That Difficult?

When I was learning, I found most of the Python courses and resources were too generic.

Right away, I wanted to learn how to make websites using Python. But the Python learning resource wanted me to spend months on syntax before they got into what interested me.

This barrier felt intimidating and daunting. I put it off for months. Whenever I started a Python course, I quickly lost interest. Python code continued to look foreign and confusing:

For example, the code above is from the tutorial for Django, a popular Python website development framework. Experienced programmers will often throw snippets like the above at you, “It’s easy!”, they’ll promise.

However, to some beginners, this code might as well be an alien language.

Most Python tutorials assume that you need to learn all of Python syntax before you can start doing anything interesting. But that’s boring! Instead, you probably want to be analyzing data, or building a website, or creating an autonomous drone with artificial intelligence.

All that time spent on syntax saps your motivation, and most people give up.

I like to think of this as the “cliff of boring”. You need to be able to climb the “cliff of boring” to make it to the “land of interesting stuff you work on” (better name pending).

But you don’t have to spend months on that cliff.

Learning Python syntax doesn’t have to feel like this.

Learning Python Doesn’t Have to be Painful

After many failed attempts, I found a process that worked better for me. In fact, I think this is the best way to learn Python programming.

First, I spent as little time as possible memorizing Python syntax.

Then, I took what I learned and immediately dove headfirst into a project I actually found interesting.

Following this process is not only much more fun, but it allows you to learn at an incredible rate.

Step 1: Figure Out What Motivates You to Learn Python

Before you start, it’s worth asking yourself why you want to learn Python programming.

At times, your learning experience will be boring and monotonous. To successfully make it through those stages, you need to anchor yourself by focusing on things you’re highly interested in.

As a beginner, I struggled to keep myself awake when trying to memorize syntax. However, when I needed to apply Python fundamentals to build a website to automatically score essays, I happily stayed up nights to finish it.

To get started, find one or two areas that interest you. Some projects that you might find interesting are:

Yes, you can make robots using the Python programming language! From the Raspberry Pi Cookbook.

Step 2: Learn the Basic Syntax

Unfortunately, this step can’t be skipped. But you can spend the minimum amount of time on this, as it isn’t very motivating.

Here are some good resources to help you learn the Python basics:

I can’t emphasize this enough: Only spend the minimum amount of time possible on syntax.

The sooner you can get to work on projects, the faster you will learn. You can always refer back to the syntax when you get stuck later. Ideally, you will spend a couple of weeks on this phase, but no more than a month.

Quick note: Learn Python 3, not Python 2. Unfortunately a lot of “learn Python” resources online still teach Python 2, but you should definitely learn Python 3. Python 2 is no longer supported, so bugs and security holes will not be fixed!

Step 3: Make Structured Projects

Once you’ve learned the basic Python syntax, start doing projects on your own. Until you apply your knowledge, it will be hard to remember everything you’ve learned.

Projects will stretch your capabilities, help you learn new Python concepts, and it will help you build a portfolio to showcase your abilities to potential employers.

It’s better to begin with structured projects until you feel comfortable enough to make projects on your own. Here at Dataquest, virtually all of our Python courses contain structured projects to help you apply what you’ve learned.

Some additional recommended resources for structured projects are:

Data science / Machine learning

Mobile Apps

Websites

Games

An example of a game you can make with Pygame. This is Barbie Seahorse Adventures 1.0, by Phil Hassey.

Hardware / Sensors / Robots

Scripts to Automate Your Work

Once you’ve done a few structured projects in your own area, you should be able to move into working on your own projects. But, before you do, it’s important to spend some time learning how to solve problems.

Step 4: Work on Python Projects on Your Own

After you’ve worked through a few structured projects, you will learn Python faster if you can start to work on your own projects on things you find interesting.

Remember to start with a small project, though. It’s better to start a small project that you finish rather than a huge project that never gets done.

Sometimes it can feel daunting to find a good Python project to work on. Here are some tips to finding some interesting projects:

Some additional ideas to spark your imagination:

Data Science / Machine Learning Project Ideas

You could make a more interactive version of this map. From RealClearPolitics.

Mobile App Project Ideas

Website Project Ideas

Python Game Project Ideas

Hardware / Sensors / Robots Project Ideas

Work Automation Project Ideas

My first project on my own was adapting my automated essay scoring algorithm from R to Python. It didn’t end up looking pretty, but it gave me a sense of accomplishment and started me on the road to building my skills.

The key is to pick something and do it. If you get too hung up on picking the perfect project, there’s a risk that you’ll never make one.

As you build your project, you will encounter problems and errors with your code — it’s inevitable. Don’t let it discourage you. There are a number of resources that can help you, including:

Step 5: Keep working on harder projects

Keep increasing the difficulty and scope of your projects. If you’re completely comfortable with what you’re building, it means it’s time to try something harder.

Continue to find new projects that challenge your skills and push you to grow even more.

Here are some ideas for when that time comes:

Going forward

At the end of the day, Python is continually evolving. There are only a few people who can legitimately claim to completely understand Python, because they created it.

You’ll constantly be learning and working on new projects to hone your skill. If you do this right, you’ll find yourself looking back on your code from 6 months ago and thinking about how terrible it is. If you get to this point, you’re on the right track.

Python is a fun and rewarding language. I think that anyone can reach a high level of proficiency if they find the right motivation.

I hope this guide has been useful on your journey. If you have any other resources to suggest, please let us know!

Find out more about how you can learn Python and add this skill to your portfolio by visiting Dataquest.

Common Python Questions:

Is it hard to learn Python?

Learning Python can certainly be challenging, and you’re likely to have frustrating moments. Staying motivated to keep learning is one of the biggest challenges.

However, if you take the step-by-step approach I’ve outlined here, you should find that it’s easy to power through because you’ll be working on projects that genuinely interest you.

Can you learn Python for free?

There are lots of free Python learning resources out there — just here at Dataquest, we have dozens of free Python tutorials and our interactive data science learning platform, which teaches Python, is free to sign up for and includes many free lessons. The internet is full of free Python learning resources!

The downside to learning for free is that to learn what you want, you’ll probably need to patch together a bunch of different free resources. You’ll spend extra time researching what you need to learn next, and then finding free resources that teach it. Platforms that cost money may offer better teaching methods (like the interactive, in-browser coding Dataquest offers), and they also save you the time of having to find and build your own curriculum.

Can you learn Python from scratch (with no coding experience)?

Yes. At Dataquest, we’ve had many learners start with no coding experience and go on to get jobs as data analysts, data scientists, and data engineers. Python is a great language for programming beginners to learn, and you don’t need any prior experience with code to pick it up.

How long does it take to learn Python?

Learning a programming language is a bit like learning a spoken language — you’re never really done, because programming languages evolve and there’s always more to learn! However, you can get to a point of being able to write simple-but-functional Python code pretty quickly.

How long it takes to get to job-ready depends on your goals, the job you’re looking for, and how much time you can dedicate to study. But for some context, Dataquest learners we surveyed in 2020 reported reaching their learning goals in less than a year — many in less than six months — with less than ten hours of study per week.

How can I learn Python faster?

Unfortunately, there aren’t really any secret shortcuts! People are always looking for the ultimate Python crash course, but it doesn’t really exist. The best thing you can do is find a platform that teaches Python (or build a curriculum for yourself) specifically for the skill you want to learn (for example, Python for game dev, or Python for data science).

This should ensure that you’re not wasting any time learning things you won’t actually need for your day-to-day Python work. But make no mistake, whatever you want to do with Python, it’ll take some time to learn!

Do you need a Python certification to find work?

We’ve written about Python certificates in depth, but the short answer is: probably not. Different companies and industries have different standards, but in data science, certificates don’t carry much weight. Employers care about the skills you have — being able to show them a GitHub full of great Python code is much more important than being able to show them a certificate.

Should you learn Python 2 or 3?

We’ve written about Python 2 or Python 3 as well, but the short answer is this: learn Python 3. A few years ago, this was still a topic of debate, and some extreme predictions even claimed that Python 3 would “kill Python.” That hasn’t happened, and today, Python 3 is everywhere.

Is Python a good language to learn in 2021?

Yes. Python is a popular and flexible language that’s used professionally in a wide variety of contexts.

We teach Python for data science and machine learning, for example, but if you wanted to apply your Python skills in another area, Python is used in finance, web development, software engineering, game development, etc.

If you’re working with data, Python is the most in-demand programming language you could learn. Here’s data from open job postings on Indeed.com in February of 2021:

Python skill set is in high demand right now, and is listed above every other technical skill in data scientist and data engineering job postings. It ranks second, behind only SQL, in data analyst job postings. Many jobs in all three areas will require both Python and SQL skills, but SQL is a query language. In terms of programming skills, Python is most in-demand.

Incidentally, we’re sometimes asked why Dataquest doesn’t teach Julia, which is a high-level and general purpose language that can be used to write code that is fast to execute and easy to implement for scientific calculations.

The charts above probably answer that question — our curriculum is focused on real-world skills. We choose what courses that are in the most demand in the job market.

Moreover, Python data skills can be really useful even if you have no aspiration to become a full-time data scientist or programmer. Having some data analysis skills with Python can be useful for a wide variety of jobs — if you work with spreadsheets, chances are there are things you could be doing faster and better with Python.

Ready to get started? Learn more about how Dataquest can help you learn Python online.

How to Learn Python: A 5-Step-Guide

Python is one of the most popular programming languages in the world. If you’re interested in technology, choosing to learn Python is a great decision. But how should you learn Python? What is the best way to become a Python programmer?

While there are many approaches to learning programming, my suggestion is to go for a blend of both theory and practice: learn new concepts and put them into practice immediately.

Focusing too much on theory can leave you paralyzed. You will fill your head with an impressive mountain of concepts, but, without practice, you won’t be able to translate that knowledge into real, useful Python code.

Last Updated April 2021

Build 11 Projects and go from Beginner to Pro in Python with the World’s Most Fun Project-Based Python Course! | By Ziyad Yehia, Internet of Things Academy

On the other hand, focusing too much on practice can be very painful and frustrating. You end up repeatedly making the same mistakes because you don’t understand why you are making them. Even though you may eventually build things that work, you will be left with a weird feeling in your stomach that you don’t really know how to code; that you’re just hacking things together. You might even feel like a bit of a fake.

Based on the downsides of these two extremes, I believe the best way to learn Python is to take a blended approach: learn the theory but put everything you learn into practice immediately.

Here is a roadmap of what this approach looks like in the context of learning programming in Python:

1. Master Python’s building blocks (Python syntax)

Have you ever heard the saying “the journey of a thousand miles starts with a single step”? Well, this is true for learning Python, too.

Most of us usually want to jump to the fun part of writing code and building stunning apps right away.

While this is an exciting aspiration, we know deep down that it is crucial for us to first master the building blocks; first, we need to learn the basics.

Without solid foundations, you can’t go very far; but with solid foundations, you can go anywhere.

While you need to gain a solid grasp of the basics, you probably don’t want to be stuck learning the basics forever. So how long should you spend at this stage?

I’ve written another article on how long it takes to learn the basics of Python, and in that article, I present a step-by-step plan you can use to master the basics of Python in about six weeks.

If you’re in a rush and have the time to dedicate, I also share a couple of tips in that article that can help you cut your learning time down to about three days. It’s definitely something worth checking out.

Syntax refers to a collection of rules that a programming language follows to create a complete block of code.

When learning the Python syntax, you should focus on the following 8 topics:

If you master these topics, you can confidently say that you know how to code in Python. Another phrase used in the Python community for this is “pythonic code”. There’s always more to learn in the tech world, but these topics are going to be your bread and butter for most things you want to code.

For a detailed breakdown of how to approach each of these topics, check out this step-by-step plan for learning Python.

Remember, the most important part at this stage is to not only grasp the concepts but also apply them in some practical way.

Now, what do you do when you’ve mastered the basics?

2. Pick a specialty

This is the point where most people get stuck after they have started learning.

Thanks to Python’s simple syntax, most people gain a solid grasp of the basics, but then they don’t really know what to do next.

At this stage, it is important to realize that Python is just a highly flexible and powerful tool. You can use Python in many ways, but it’s up to you to decide exactly how you would like to use it.

So, how can Python be used to solve problems?

Well, Python is very popular across many industries in the software development world, including:

I have written a more detailed article on this topic, where you can read more about how Python is used in each of those industries.

So, which is the best choice? Well, the answer to that question is totally up to you.

Here are three points to consider when deciding what you would like to pursue:

If you’re finding it hard to decide, remember: it’s not like you’re signing your life away here.

You can always pick a specialty, try it out, and if it turns out to not be a good fit, pick another.

That said, whichever route you pick will involve hard work. There will be things you like about the topic and things you don’t like.

All of that’s okay because navigating these difficulties is what makes mastering something so worthwhile in the first place.

Whichever specialty you pick, try to stick with it for as long as you can.

3. Master the theory and frameworks of that specialty

So you’ve decided on a specialty that you would like to pursue. Congrats!

However, that’s only half of the battle. Now, you have to get good at it!

In order to gain more experience in your chosen specialty, we are again going to use our blended approach of theory and practice.

The theory side of things changes a bit here, though.

Let’s say you picked data science as your specialty. Here’s how I would suggest you approach mastering it:

Notice that the theory side of things now has two components.

There is the theory of data science as a topic:

Remember, Python is just a tool that will help you perform the mechanical tasks involved in applying the theory. Unless you understand the field, you will find it difficult to put your Python skills to use within that field.

At the same time, knowing a lot about the field of data science does not mean that you know how to use Python for data science. That requires a more specific focus on the different ways that Python is used within the field.

Using our data science example again, here are some questions you could ask at this stage:

Finally, you can focus on gaining practical experience with applying those Python libraries and frameworks to common and basic problems within your chosen field. By now, you should have a good idea of what these are and should be able to experiment. You will be able to find online Python tutorials that will guide you in your experimentation.

I have presented the flow here as a linear three-step process, but really it is an iterative and interconnected one. One day you will be learning about the field, another day you will be learning about relevant Python frameworks, and another day you will be tinkering with code; perhaps you will even be doing all three at once.

The key here is balance. On one hand, you don’t want to be so rigid and linear that you wait months before you start practicing. On the other hand, you don’t want to be so erratic that you never learn anything deeply. You are the best judge of what balance will mean for you in this situation.

4. Learn to work together with other developers

So, by now, you’ve:

This reminds me of a cool African Proverb:

“If you want to go fast, go alone. If you want to go far, go together”.

The best software is rarely built alone. There might be less administrative baggage with “going solo”, but to produce significant and impactful work, you need a team.

The idea of a “lone wolf” inventing world-changing software from their University dorm room is, in most cases, an urban myth.

Mark Zuckerberg had a computer scientist father; Steve Jobs had Steve Wozniak, and Bill Gates had Paul Allen.

No one is great at everything, and no-one is self-sufficient. We need other people, and we all shine brighter when we work together.

Learning to work with others is one of the greatest things you can do on your path to become a Python developer.

Working with others will give you the environment and exposure you need to thrive and become an experienced programmer, and the relationships you form will inspire you and help you stay motivated when the going gets tough.

Okay, so how do you find a team?

Well, there are plenty of ways to work with other developers, especially in the open-source community.

It’s impossible to put all the things you’ll learn at this stage into words.

To put it simply: everything will make sense to you, and everything will become real.

Oh, and if you’re struggling to come up with project ideas, check out this list for inspiration.

5. Keep learning & practicing

Like most things in tech, mastering Python involves continuous learning.

One of the most exciting parts about technology is how rapidly it evolves and changes. There’s always something new to learn, and every great developer adopts an attitude of lifelong learning, practicing, and experimenting.

So, the final tip is to keep at it! Just keep exposing yourself to new things, and keep trying to learn and practice new topics, and life will take care of the rest.

Wrapping up

If you enjoyed this article and are just at the start of your journey, I invite you to check out my Python Bible Course on Udemy.

The Python Bible has helped over 100,000 people, just like you, learn to code.

It is tailored perfectly to the needs of Python beginners, and it really stands out for being fun and project-based.

Following my philosophy of blending theory and practice, all the concepts you learn in the course will be used to build a set of 11-fun Python projects, from a baby simulator to an X-O game.

Either way, I hope you have found this article useful, and happy Pythoning!