Python

How Do I Start Learning Python?

Python is hot right now. Recently, several people have asked me how they can start learning Python. Here are my answers, nuanced by goals and roles.

I’m completely new to programming. How can I start learning Python?

That’s awesome! Python is a great language for beginners. You can do just about anything with Python, and its learning curve is lower than other languages. Here’s what I recommend:

  1. First, find a friend who knows Python. They can encourage you in your journey and also help you when you get stuck. If you need help finding Python friends, look for a local Python meetup, or just reach out to me.
  2. Second, install the latest version of Python from Python.org onto your computer. If you want to learn Python, then you’ll need to get your hands dirty!
  3. Third, read through a good Python book for beginners. Despite all the material available online, nothing beats a good book. I recommend Automate the Boring Stuff with Python by Al Sweigart. It’s a book written specifically for people who are new to coding, and it shows very practical things you can do with Python. You can even read it for free online! Udemy also offers an online course based on this book. Make sure you follow along with the example code on your own machine.

Once you finish your first book, keep learning! Try another book. Take an online course. Come up with a fun project you can do yourself, like making a website or programming a circuit board.

I’m a hobbyist. How can I start learning Python for fun?

Python is a great language for fun side projects. It’s easy to learn, and it has tons of packages to do just about anything. If you just want to start programming in general, then I’d recommend reading Automate the Boring Stuff with Python by Al Sweigart or Python Crash Course by Eric Matthes. No Starch Press also publishes a number of other Python books on nifty topics like games, math, and ciphers.

If you’re a hobbyist, then my main recommendation would be to come up with a fun project. Learning Python by itself is great, but learning Python to do a cool project will keep you motivated with a clear goal. Here are some ideas:

I’m a software engineer. How can I pick up Python quickly?

If you already know how to code, and you just need to pick up Python for a project on the job, don’t fret. Python will be very quick to pick up. When I re-learned Python a few years ago, I read the Python Programming book on Wikibooks. Learn X in Y Minutes and learnpython.org are also great resources for learning quickly by example. Once you breeze through the language, then you’ll probably need to lear packages and frameworks specific to your project. Some projects have better docs than others. For example, Django and pytest have great docs online.

I’m a scientist. Should I start using Python, and if so, how?

Data scientists were the first scientific community to adopt Python in large numbers, but now scientists from all fields use it for data analysis and visualization. I personally know an environmental scientist and a virologist who both started using Python in the past few years. Compared to other languages like R and Julia, Python simply has more users, more packages, and more support. Furthermore, the Python Developers Survey 2018 showed that over half of all Python users use Python for data analysis. So yes, if you’re a scientist, then you should start using Python!

To get started with Python, first make sure you have basic programming skills. It might be tempting to dive headfirst into coding some data analysis scripts, but your work will turn out much better if you learn the basics first. If you are new to programming, then start by reading Automate the Boring Stuff with Python by Al Sweigart. To learn specifically about data analysis with Python, read Python for Data Analysis by William McKinney. I’d also recommend reading additional books or taking some courses on specific tools and frameworks that you intend to use. Furthermore, I’d yield my advice to any peers in your scientific community who have recommendations.

I’m a software tester. How can I start learning Python for automation?

Python is a great language for test automation. If you are a manual tester who hasn’t done any programming before, focus on learning how to code before learning how to do automation. Follow the advice I gave above for newbies. Once you have basic Python skills, then learn pytest, the most popular and arguably the best test framework for Python. I recommend reading pytest Quick Start Guide by Bruno Oliveira or Python Testing with pytest by Brian Okken. If you want to learn about Test-Driven Development with a Django app, then check out the goat book by Harry Percival.

I’m a kid. Are there any good ways for me to learn Python?

Yes! Python is a great language for kids as well as adults. Its learning curve is low, but it still has tons of power. No Starch Press publishes a few Python books specifically for kids. Project kits from Adafruit and Raspberry Pi are another great way for kids to get their hands dirty with fun projects. If you want to learn by making games, check out Arcade Academy or PursuedPyBear. Many Python conferences also run “Young Coders” events that encourage kids to come and do things with Python.

Should I learn Python, JavaScript, Java, or another language?

Each programming language has advantages and disadvantages, but the main factor in choosing a language should be what you intend to develop. For example, Web app front-ends require JavaScript because browsers use JavaScript and not other languages. Java is popular all around for several applications like backend services and Android apps. C# is a mainstay for Microsoft .NET development. Python excels at backend web development, infrastructure, automation, and data science.

If you are new to programming and just want to start somewhere, I’d strongly recommend Python. Compared to other programming languages, it’s easy to learn. As you grow your skills, Python will grow with you because it has so many packages. You can also explore a variety of interest within the Python community because Python is popular in many domains. These days, you just can’t go wrong learning Python!

Should I learn Python 2 or 3?

Learn Python 3. Python 2 hit end of life on January 1, 2020. Some older projects may continue to use Python 2, but support for Python 2 is dead.

What tools should I use for coding in Python?

The most important tool for coding in any language is arguably the editor or IDE. These days, I use Visual Studio Code with the Python extension. VS Code feels lightweight, but it provides all the things I need as a developer: syntax highlighting, running and debugging, Git integration, and a terminal in the same window. VS Code is also fully customizable. JetBrains PyCharm is another great editor that I recommend. PyCharm a bit heavier than VS Code, but it also has richer features. Both are fantastic choices.

Virtual environments are indispensable part of Python development. They manage Python dependency packages locally per project rather than globally for an entire machine. Local package management is necessary when a user doesn’t have system-wide access or when a project needs a different package version than the one installed globally. To learn about virtual environments, take the venv tutorial in the official Python docs.

Source control is another vital part of programming. Using a source control system like Git maintains a history of your project. If you ever make a mistake, you can revert the code to its last known working state. Source control also makes it much easier for multiple people to work on the same project together simultaneously. Git is one of the most popular source control tools in use today. To learn more about Git, check out GitHub’s learning resources.

What Python books should I read?

Please check my suggestions above to know what Python books could be good for you.

What Python courses should I take online?

To be honest, I don’t have any specific Python courses to recommend. Most online courses are very similar. They include videos, transcripts, quizzes, and maybe even projects. If you want to take an online course, then I recommend finding one that looks good to you and giving it a try. I also recommend using multiple resources – either taking more than one course or reading more than one book. The second pass will reinforce the basics and also reveal new tidbits that the first pass may have missed.

Should I take a Python boot camp?

Boot camps are high-intensity programs that train people to become developers. Many boot camps focus on one main technology stack or skill, such as Web development with JavaScript or data science with Python. They can take weeks or months of full-time focus to complete, and they can be expensive.

Boot camp isn’t right for everyone. Most people go to boot camp in order to find a job after completing the program. They can be a great way to pivot your career if you seriously want to become a software developer but don’t want to go “back to school.” However, they may not be ideal if you just want to learn programming for fun or as a secondary skill.

Personally, I don’t have any boot camps to recommend, but I do know that most major US cities have boot camp programs. If you think boot camp is right for you, then check them out.

Should I go to a Python conference?

YES! Absolutely yes! People come to Python for the language, but they stay for the people. Python conferences are the best way to engage the Python community. They are places to learn and be inspired. You’ll also score tons of cool swag. Lives change at Python conferences.

The main Python conference is PyCon US. Thousands of people attend each year. However, there are several other Python conferences worldwide and regionally around the US. Personally, I’ve been to PyCon, PyOhio, PyGotham, PyCon Canada, PyCaribbean, PyTexas, PyCascades, DjangoCon, and PyData Carolinas. Try to find a regional conference near you if you can’t make it to PyCon.

How much will it cost to use and learn Python?

It’s possible to learn and use Python for free! Python is an open source language. As long as you have a machine with Internet access, you can download Python for free and get rolling. There are tons of free learning resources online, too. Typically, you can learn the basics for free, but you might want to buy some books or courses for specific tools or frameworks.

Beyond Unit Tests: End-to-End Web UI Testing

On October 4, 2019, I gave a talk entitled Beyond Unit Tests: End-to-End Web UI Testing at PyGotham 2019. Check it out below! I show how to write a concise-yet-complete test solution for Web UI test cases using Python, pytest, and Selenium WebDriver.

This talk is a condensed version of my Hands-On Web UI Testing tutorials that I delivered at DjangoCon 2019 and PyOhio 2019. If you’d like to take the full tutorial, check out https://github.com/AndyLPK247/djangocon-2019-web-ui-testing. Full instructions are in the README.

Be sure to check out the other PyGotham 2019 talks, too. My favorite was Dungeons & Dragons & Python: Epic Adventures with Prompt-Toolkit and Friends by Mike Pirnat.

Python Program Main Function

This article will show you the best way to handle “main” functions in Python.

Python is like a scripting language in that all lines in a Python “module” (a .py file) are executed whenever the file is run. Modules don’t need a “main” function. Consider a module named stuff.py with the following code:

def print_stuff():
  print("stuff happened!")

print_stuff()

This is the output when it is run:

$ python stuff.py
stuff happened!

The print_stuff function was called as a regular line of code, not in any function. When the module ran, this line was executed.

This will cause a problem, though, if stuff is imported by another module. Consider a second module named more_stuff.py:

import stuff

stuff.print_stuff()
print("more stuff!")

At first glance, we may expect to see two lines printed. However, running more_stuff actually prints three lines:

$ python more_stuff.py
stuff happened!
stuff happened!
more stuff!

Why did “stuff happened!” get printed twice? Well, when “import stuff” was called, the stuff module was loaded. Whenever a module is loaded, all of its code is executed. The print_stuff function was called at line 4 in the stuff module. Then, it was called again at line 3 in the more_stuff module.

So, how can we avoid this problem? Simple: check the module’s __name__. The __name__ variable (pronounced “dunder name”) is dynamically set to the module’s name. If the module is the main entry point, then __name__ will be set to “__main__”. Otherwise, if the module is simply imported, then it will be set to the module’s filename without the “.py” extension.

Let’s rewrite our modules. Here’s stuff:

def print_stuff():
  print("stuff happened!")

if __name__ == '__main__':
  print_stuff()

And here’s more_stuff:

import stuff

if __name__ == '__main__':
  stuff.print_stuff()
  print("more stuff!")

If we rerun more_stuff, then the line “stuff happened!” will print only once:

$ python more_stuff.py
stuff happened!
more stuff!

As a best programming practice, Python modules should not contain any directly-called lines. They should contain only functions, classes, and variable initializations. Anything to be executed as a “main” body should be done after a check for “if __name__ == ‘__main__'”. That way, no rogue calls are made when modules are imported by other modules. The conditional check for __name__ also makes the “main” body clear to the reader.

Some people still like to have a “main” function. That’s cool. Just do it like this:

import stuff

def main():
  stuff.print_stuff()
  print("more stuff!")

if __name__ == '__main__':
  main()

For more information, read this Stack Overflow article:
What does if __name__ == “__main__”: do?

PyOhio 2019 Reflections

PyOhio 2019 was one of my favorite conferences, ever. It was my ninth Python conference and my second PyOhio conference. There were so many good things that happened in such short time that, even three weeks later, I’m still processing everything. Here are my reflections on this outstanding conference.

Roadtrip

PyOhio 2019 was held in Columbus, Ohio at the Ohio State Union. I really wanted to go because PyOhio 2018 was such a good time, and I started asking my friends in North Carolina if anyone wanted to join me. My friends Rick and Justin all emphatically replied YES! To make traveling more fun, we decided to turn it into a road trip! We dubbed ourselves the “PyCarolinas delegation”, piled into my Chrysler 300, and made the 8-hour drive in good time. Our friend Greg also joined us at PyOhio, though he traveled separately with his wife.

This was the first time I ever did a road trip to a conference. I’m so glad we did it. I felt like I got to spend great quality time with my friends. Many parts of the drive were quite scenic. We also discovered a Beef Jerky Outlet!

My Talks

At PyOhio 2019, I delivered the holy trifecta of speaking opportunities: a talk, a tutorial, and a lightning talk. I felt both honored and humbled to be chosen for all three.

My talk was entitled Surviving Without Python. I talked about how we can use Python’s principles, projects, and people to inspire us even when we don’t use Python to solve our problems:

My tutorial was entitled Hands-On Web UI Testing. Python’s popularity continues to rise, and many people use it for testing. In my tutorial, I showed how you can develop a simple yet powerful solution with Python, pytest, and Selenium WebDriver to automate Web UI tests. The tutorial project in GitHub contains the code, instructions, and slides.

My lightning talk was announcing PyCarolinas 2020. My friend Calvin and I are teaming up to bring PyCarolinas back! We are targeting June 2020 in Raleigh, NC. Please help us make it happen!

Other Talks

There were so many great talks at PyOhio. Here were a few highlights.

This was my favorite talk of the conference. Although a history lesson may seem out of place at a Python conference, Jon used it as a convicting call to action. Be sure to watch it to the end!
Dane showed how easy it is to use pytest. You don’t need to be an expert tester to write good tests!
Travis blew my mind with some of Python’s latest features. This talk was a great way to catch up on new things!
Dustin explained why it’s important to keep alive the passion we have for computing. I also loved the TI-83 Plus reference – that was in my talk, too!
Controversial? Yes. True? Yes. Aly? Preach!
Docs are vital for understanding code and features. Mason shows how to make docs just a regular part of the development process.

Sprints

Sprints are a Python conference event in which people work together on open-source projects. Conferences are the perfect time to have sprints because people are both co-located and excited. PyOhio 2019 was actually the first time I attended sprints. There were sprints on both Friday and Saturday nights. Accenture graciously hosted both sprints in their swanky office and provided refreshments.

I went to the sprints both nights with the honest intention to work on stuff. However, I spent the whole time socializing with friends. It was nevertheless time well spent! Many of us went to Jeni’s Splendid Ice Creams after the final sprint, too.

Swag

The PyOhio 2019 logo was lit! I joked that I was going to the conference just to get that logo sticker and t-shirt. Some other cool takeaways were the Numerator puzzles and the JP Morgan Chase puzzle blocks.

My sticker game is strong:

My backpack was also a hit!

Food and Drink

I had some good eats while in Columbus. My friend Mason recommended Raising Cane’s, which turned out to be awesome! So many people followed us there, too.

I also hopped an electric scooter to get bubble tea. Those scooters are so much fun. I hadn’t ridden one since PyTexas 2019! (Or maybe PyCon 2019; I don’t remember precisely.)

To relive PyOhio 2018 memories, I went to Eden Burger for a Vegan brunch on Sunday morning with friends! It was delicious and nutritious.

Our friend Greg recommended we visit Brewdog, a renowned Scottish craft brewery with a huge site on the outskirts of Columbus. We took the tour with the “beer school” course, and we stayed for a delicious dinner afterwards. So good, so very good. It was the best way to end the conference!

Friends

The best part about PyOhio 2019 was the time I spent with all my friends. I wish I could name everyone here, but there are just too many names. The Python community is the best. Conference friends are real friends. Also, for what it’s worth, they’ve given me the nickname “Pandy.”

Hope

My PyOhio 2019 experience can be summarized in one line:

Truth – I went all-in from leaving my house on Friday morning until returning Monday evening. The conference high is very real. My hope is that I’ll get to attend more great conferences like this, and also that I’ll be able to help make PyCarolinas as good as PyOhio!

Hands-On UI Testing with Python (SmartBear Webinar)

On August 14, 2019, I teamed up with SmartBear to deliver a one-hour webinar about Web UI testing with Python! It was an honor to work with Nicholas Brown, Digital Marketing Manager for CrossBrowserTesting at SmartBear Software, to make this webinar happen.

The Webinar

Source: https://crossbrowsertesting.com/resources/webinars/testing-with-python

In the webinar, I showed how to build a basic Web UI test automation solution using Python, pytest, and Selenium WebDriver. The tutorial covered automating one test, a simple DuckDuckGo search, from inception to automation. It also showed how to use CrossBrowserTesting to scale the solution so that it can run tests on any browser, any platform, and any version in the cloud as a service!

The example test project for the webinar is hosted in Github here: https://github.com/AndyLPK247/smartbear-hands-on-ui-testing-python

I encourage you to clone the Github repository and try to run the example test on your own! Make sure to get a CrossBrowserTesting trial license so you can try different browsers. You can also try to write new tests of your own. All instructions are in the README. Have fun with it!

The Q&A

After the tutorial, we took questions from the audience. Here are answers to the top questions:

How can we automate UI interactions for CAPTCHA?

CAPTCHA is a feature many websites use to determine whether or not a user is human. Most CAPTCHAs require the user to read obscured text from an image, but there are other variations. By their very nature, CAPTCHAs are designed to thwart UI automation.

When someone asked this question during the webinar, I didn’t have an answer, so I did some research afterwards. Unfortunately, it looks like there’s no easy solution. The best workarounds involve driving apps through their APIs to avoid CAPTCHAs. I also saw some services that offer to solve CAPTCHAs.

Are there any standard Page Object Pattern implementations in Python?

Not really. Mozilla maintains the PyPOM project, but I personally haven’t used it. I like to keep my page objects pretty simple, as shown in the tutorial. I also recommend the Screenplay Pattern, which handles concerns better as test automation solutions grow larger. I’m actually working on a Pythonic implementation of the Screenplay Pattern that I hope to release soon!

How can I run Python tests that use Selenium WebDriver and pytest from Jenkins?

Any major Continuous Integration tool like Jenkins can easily run Web UI tests in any major language. First, make sure the nodes are properly configured to run the tests – they’ll need Python with the appropriate packages. If you plan to use local browsers, make sure the nodes have the browsers and WebDriver executables properly installed. If you plan to use remote browsers (like with CrossBrowserTesting), make sure your CI environment can call out to the remote service. Test jobs can simply call pytest from the command line to launch the tests. I also recommend the “JUnit” pytest option to generate a JUnit-style XML test report because most CI tools require that format for displaying and tracking test results.

How can I combine API and database testing with Web UI testing?

One way to handle API and database testing is to write integration tests separate from Web UI tests. You can still use pytest, but you’d use a library like requests for APIs and SQLAlchemy for databases.

Another approach is to write “hybrid” tests that use APIs and database calls to help Web UI testing. Browsers are notoriously slow compared to direct back-end calls. For example, database calls could pre-populate data so that, upon login, the website already displays stuff to test. Hybrid tests can make tests much faster and much safer.

How can we test mobile apps and browsers using Python?

Even though our tutorial covered desktop-based browser UI interactions, the strategy for testing mobile apps and browsers is the same. Mobile tests need Appium, which is like a special version of WebDriver for mobile features. The Page Object Pattern (or Screenplay Pattern) still applies. CrossBrowserTesting provides mobile platforms, too!

Surviving Without Python


Python is such a popular language for good reason: Its principles are strong. However, if Python is “the second-best language for everything”… that means the first-best is often chosen instead. Oh no! How can Pythonistas survive a project or workplace without our favorite language?

Personally, even though I love Python, I don’t use it daily at my full time job. Nevertheless, Pythonic thinking guides my whole approach to software. I will talk about how the things that make Python great can be applied to non-Python places in three primary ways:

  1. Principles from the Zen of Python
  2. Projects that partially use Python
  3. People who build strong, healthy community

Check out my talk, Surviving Without Python, from PyOhio 2019! It was one of the most meaningful talks I’ve ever given.

Tutorial: Web Testing Made Easy with Python

Have you ever discovered a bug in a web app? Yuck! Almost everyone has. Bugs look bad, interrupt the user’s experience, and cheapen the web app’s value. Severe bugs can incur serious business costs and tarnish the provider’s reputation.

So, how can we prevent these bugs from reaching users? The best way to catch bugs is to test the web app. However, web UI testing can be difficult: it requires more effort than unit testing, and it has a bad rap for being flaky.

Never fear! Recently, I teamed up with the awesome folks at TestProject to develop a helpful tutorial that makes web UI test automation easy with the power of Python! The tutorial is named Web Testing Made Easy with Python, Pytest and Selenium WebDriver. It is available for free as a set of TestProject blog articles together with a GitHub example project.

In our tutorial, we will build a simple yet robust web UI test solution using Pythonpytest, and Selenium WebDriver. We cover strategies for good test design as well as patterns for good automation code. By the end of the tutorial, you’ll be a web test automation champ! Your Python test project can be the foundation for your own test cases, too.

How can you take the tutorial? Start reading here, and follow the instructions: https://blog.testproject.io/2019/07/16/open-source-test-automation-python-pytest-selenium-webdriver/

I personally want to thank TestProject for this collaboration. TestProject provides helpful tools that can supercharge your test automation. They offer a smart test recorder, a bunch of add-ons that act like test case building blocks, an SDK that can make test automation coding easier, and beautiful analytics to see exactly what the tests are doing. Not only is TestProject a cool platform, but the people with whom I’ve worked there are great. Be sure to check it out!