Real Python

Dependency Management With Python Poetry

2021-12-20T14:00:00+00:00

When your Python project relies on external packages, you need to make sure you’re using the right version of each package. After an update, a package might not work as it did before the update. A dependency manager like Python Poetry helps you specify, install, and resolve external packages in your projects. This way, you can be sure that you always work with the right dependency version on every machine.

In this tutorial, you’ll learn how to:

Start a new Poetry project
Add Poetry to an existing project
Use the pyproject.toml file
Pin dependencies
Install dependencies with poetry.lock
Execute basic Poetry CLI commands

Using Poetry will help you start new projects, maintain existing ones, and master dependency management. You’ll be prepared to work with pyproject.toml files, which will be the standard for defining build requirements in Python projects.

To complete this tutorial and get the most out of it, you should have a basic understanding of virtual environments, modules and packages, and pip.

While this tutorial focuses on dependency management, Poetry can also help you with building and packaging projects. If you want to share your work, then you can even publish your Poetry project to the Python Packaging Index (PyPI).

Free Bonus: Click here to get access to a free 5-day class that shows you how to avoid common dependency management issues with tools like Pip, PyPI, Virtualenv, and requirements files.

Take Care of Prerequisites

Before diving into the nitty-gritty of Python Poetry, you’ll take care of some prerequisites. First, you’ll read a short overview of terminology you’ll encounter in this tutorial. Next, you’ll install Poetry itself.

Relevant Terminology

If you’ve ever used an import statement in one of your Python scripts, then you’ve worked with modules. Some of these modules might have been Python files you wrote on your own. Others could have been built-in modules, like datetime. However, sometimes what Python provides isn’t enough. That’s when you might turn to external, packaged modules. When your Python code relies on external modules, you can say that these packages are dependencies of your project.

You can find packages that aren’t part of the Python standard library in PyPI. Before seeing how this works, you need to install Poetry on your system.

Python Poetry Installation

To use Poetry in your command line, you should install it system-wide. If you just want to try it out, then you can install it into a virtual environment using pip. But you should try this method with caution because Poetry will install its own dependencies, which can conflict with other packages you’re using in your project.

The recommended way to install Poetry is by using the official install-poetry script. You can either download and run this Python file manually or select your operating system below to use the appropriate command:

Windows
Linux + macOS

PS C:\> (Invoke-WebRequest -Uri https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py -UseBasicParsing).Content | python -

If you’re on Windows, then you can use the Invoke-Webrequest cmdlet with the -UseBasicParsing option to download the content of a requested URL to the standard output stream (stdout). With the pipe character (|), you’re handing over the output to the standard input stream (stdin) of python. In this case, you’re piping the content of install-poetry.py to your Python interpreter.

Note: Some users report errors on Windows 10 when they use the PowerShell command.

$ curl https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py | python3 -

With curl, you’re outputting the content of a requested URL to the standard output stream (stdout). By using a Unix pipeline with the pipe character (|), you’re handing over the output to the standard input stream (stdin) of python3. In this case, you’re piping the content of install-poetry.py to your Python interpreter.

Note: If you’re on macOS, then you may get an ssl.SSLCertVerificationError. This error can occur if you don’t have the default root certificates for the SSL module installed. You can install them by running a command script in your Python folder:

$ open "/Applications/Python 3.9/Install Certificates.command"

Depending on your installed Python version, the specific path to the Python interpeter might be different. In that case, you need to adjust the path in the above command accordingly.

After you run the command, the curl command above should work without any errors.

In the output, you should see a message that the installation is complete. You can run poetry --version in your terminal to see if poetry works. This command will display your current Poetry version. If you want to update Poetry, then you can run poetry self update.

Get Started With Python Poetry

With Poetry installed, it’s time to see how Poetry works. In this section, you’ll learn how to start a fresh Poetry project and how to add Poetry to an existing project. You’ll also see the project structure and inspect the pyproject.toml file.

Create a New Poetry Project

You can create a new Poetry project by using the new command and a project name as an argument. In this tutorial, the project is called rp-poetry. Create the project, and then move into the newly created directory:

$ poetry new rp-poetry
$ cd rp-poetry

By running poetry new rp-poetry, you create a new folder named rp-poetry/. When you look inside the folder, you’ll see a structure:

rp-poetry/
│
├── rp_poetry/
│   └── __init__.py
│
├── tests/
│   ├── __init__.py
│   └── test_rp_poetry.py
│
├── README.rst
└── pyproject.toml

Read the full article at https://realpython.com/dependency-management-python-poetry/ »

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The Real Python Podcast – Episode #90: A Python Journey: Cyber Security, Automating AWS, and TDD

2021-12-17T12:00:00+00:00

The Python community continually grows, with many users coming from different languages and backgrounds. This week on the show, we talk with developer Hugh Tipping about his Python journey. Hugh is also a member of the Real Python community.

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Host Your Django Project on Heroku

2021-12-14T14:00:00+00:00

As a novice web developer, you’ve built your portfolio app and shared your code on GitHub. Perhaps, you’re hoping to attract technical recruiters to land your first programming job. Many coding bootcamp graduates are likely doing the same thing. To differentiate yourself from the crowd and boost your chances of getting noticed, you can start hosting your Django project online.

For a hobby Django project, you’ll want a hosting service that’s free of charge, quick to set up, user-friendly, and well-integrated with your existing technology stack. While GitHub Pages is perfect for hosting static websites and websites with JavaScript, you’ll need a web server to run your Flask or Django project.

There are a few major cloud platform providers operating in different models, but you’re going to explore Heroku in this course. It ticks all the boxes—it’s free, quick to set up, user-friendly, and well-integrated with Django—and is the favorite cloud platform provider of many startups.

In this course, you’ll learn how to:

Sign up for a free Heroku account
Use the Heroku CLI (command-line interface)
Bootstrap a minimal Django project
Integrate Git with Heroku
Connect to Heroku’s PostgreSQL database
Manage configuration, make new releases and rollbacks

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Java vs Python: Basic Python for Java Developers

2021-12-13T14:00:00+00:00

Python is a general-purpose programming language. You can understand its growth in the last couple of years by considering its approachability for learning and its high suitability for data analysis, machine learning, and web development. But what kind of programming language is it? What are some differences when you compare Java vs Python? What can you do with it? And is it really as “easy to learn” as some people claim?

You’ll explore Python from a Java perspective in this tutorial. After you’ve read it, you’ll be able to decide whether Python is a viable option to solve your use cases and to appreciate when you can use Python in combination with Java for certain types of problems.

In this tutorial, you’ll learn about:

The general Python programming language syntax
The most relevant standard data types
The differences and similarities in Java vs Python
Resources for high-quality Python documentation and tutorials
Some of the Python community’s favorite frameworks and libraries
Approaches for getting started with Python programming from scratch

This tutorial is for software developers who are familiar with Java’s inner workings, concepts, terminology, classes, types, collections framework, and so on.

You don’t need to have any Python experience at all.

Free Bonus: Click here to get a Python Cheat Sheet and learn the basics of Python 3, like working with data types, dictionaries, lists, and Python functions.

Where Does Python Come From?

Python is a programming language that was developed by Guido van Rossum. He was looking for a hobby programming project that would keep him occupied during the Christmas holiday in 1989, so that’s when he started developing the Python interpreter.

Python has its origins in a number of languages: ABC, C, and Modula-3. It’s basically an object-oriented, imperative programming language.

Depending on your preference and desired functionality, it can be applied in a full object-oriented style or in a procedural programming style with functions. The object-oriented capabilities are addressed later in this tutorial.

Note: Just for clarity, from a Java perspective, Python functions are like static methods, and you don’t necessarily need to define them within a class. Later on, you’ll see an example of a Python function definition.

Additionally, a more functional programming style is also perfectly possible. To learn more, you’ll want to explore Python’s functional programming capabilities.

In early 2021, TIOBE announced Python as the programming language of the year for the fourth time. As of the 2021 Octoverse report, Python ranks as the second most popular language on GitHub by repository contributors.

What Is the Philosophy of Python?

Soon, you’ll get hands-on with Python in the sections following this one. First, however, you’ll explore why it’s worth getting to know Python better by going through some features that you can trace back to Python’s philosophy.

Some ideas behind Java and Python are similar, but every programming language has its own unique characteristics. The philosophy of Python is captured as a collection of nineteen guiding principles, the Zen of Python. Python hides a few Easter eggs, and one of them is the Zen of Python. Consider what happens when you issue the following command in the Python read–eval–print loop (REPL):

>>>

>>> import this
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

While you shouldn’t take the statements above too literally, a few of these relate directly to the characteristics that you’ll walk through next.

Note: The Python read–eval–print loop is explained later on in this tutorial.

By considering the guiding principles of the Zen of Python, you’ll get a good idea about how you can approach working with the language.

Python Code Is Readable

If you come from a Java background and you look at a typical fragment of Python code, you might think that you’re looking at pseudo-code. There are a few factors that contribute to this:

Indentation is used for statement grouping. This makes code blocks shorter and promotes a uniform coding style. You’ll find more on this topic later on.
A few built-in high-level data structures, combined with a modest set of operator symbols, make Python very expressive.
The choice of using exceptions as the primary way to deal with errors keeps the code clean.
Python programmers prefer a coding style inspired by the concept that it’s Easier to Ask for Forgiveness than Permission (EAFP) instead of the Look Before You Leap (LBYL) concept. This style puts emphasis on the normal, happy path of your program, and you’ll figure out how any anomalies are handled afterward.

You can find a few examples of how this appears in practice during this tutorial, as well as in other linked resources.

Read the full article at https://realpython.com/java-vs-python/ »

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The Real Python Podcast – Episode #89: Solving Advent of Code Puzzles With Python

2021-12-10T12:00:00+00:00

Are you ready to break open the first days of puzzles from the annual Advent of Code challenge? Advent of Code is an advent calendar of twenty-five programming puzzles published each December. Practicing solving puzzles is a great way to build your Python skills. This week on the show, we have previous guest and Real Python author Geir Arne Hjelle to discuss his recent article titled, "Advent of Code: Solving Your Puzzles With Python."

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Binary, Bytes, and Bitwise Operators in Python

2021-12-07T14:00:00+00:00

Computers store all kinds of information as a stream of binary digits called bits. Whether you’re working with text, images, or videos, they all boil down to ones and zeros. Python’s bitwise operators let you manipulate those individual bits of data at the most granular level.

Python isolates you from the underlying bits with high-level abstractions. You’re more likely to find the overloaded flavors of bitwise operators in practice. But when you work with them in their original form, you’ll be surprised by their quirks!

In this course, you’ll learn how to:

Read binary numbers
Perform bitwise math and read truth tables
Represent fixed and arbitrary precision itegers in Python
Perform bitwise operations in Python
Use bitmasks to pack information on a single byte
Differentiate Big-Endian and Little-Endian byte orders
Overload Python bitwise operators in custom data types

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Prettify Your Data Structures With Pretty Print in Python

2021-12-06T14:00:00+00:00

Dealing with data is essential for any Pythonista, but sometimes that data is just not very pretty. Computers don’t care about formatting, but without good formatting, humans may find something hard to read. The output isn’t pretty when you use print() on large dictionaries or long lists—it’s efficient, but not pretty.

The pprint module in Python is a utility module that you can use to print data structures in a readable, pretty way. It’s a part of the standard library that’s especially useful for debugging code dealing with API requests, large JSON files, and data in general.

By the end of this tutorial, you’ll:

Understand why the pprint module is necessary
Learn how to use pprint(), PrettyPrinter, and their parameters
Be able to create your own instance of PrettyPrinter
Save formatted string output instead of printing it
Print and recognize recursive data structures

Along the way, you’ll also see an HTTP request to a public API and JSON parsing in action.

Free Bonus: Click here to get a Python Cheat Sheet and learn the basics of Python 3, like working with data types, dictionaries, lists, and Python functions.

Understanding the Need for Python’s Pretty Print

The Python pprint module is helpful in many situations. It comes in handy when making API requests, dealing with JSON files, or handling complicated and nested data. You’ll probably find that using the normal print() function isn’t adequate to efficiently explore your data and debug your application. When you use print() with dictionaries and lists, the output doesn’t contain any newlines.

Before you start exploring pprint, you’ll first use urllib to make a request to get some data. You’ll make a request to {JSON} Placeholder for some mock user information. The first thing to do is to make the HTTP GET request and put the response into a dictionary:

>>>

>>> from urllib import request
>>> response = request.urlopen("https://jsonplaceholder.typicode.com/users")
>>> json_response = response.read()
>>> import json
>>> users = json.loads(json_response)

Here, you make a basic GET request and then parse the response into a dictionary with json.loads(). With the dictionary now in a variable, a common next step is to print the contents with print():

>>>

>>> print(users)
[{'id': 1, 'name': 'Leanne Graham', 'username': 'Bret', 'email': 'Sincere@april.biz', 'address': {'street': 'Kulas Light', 'suite': 'Apt. 556', 'city': 'Gwenborough', 'zipcode': '92998-3874', 'geo': {'lat': '-37.3159', 'lng': '81.1496'}}, 'phone': '1-770-736-8031 x56442', 'website': 'hildegard.org', 'company': {'name': 'Romaguera-Crona', 'catchPhrase': 'Multi-layered client-server neural-net', 'bs': 'harness real-time e-markets'}}, {'id': 2, 'name': 'Ervin Howell', 'username': 'Antonette', 'email': 'Shanna@melissa.tv', 'address': {'street': 'Victor Plains', 'suite': 'Suite 879', 'city': 'Wisokyburgh', 'zipcode': '90566-7771', 'geo': {'lat': '-43.9509', 'lng': '-34.4618'}}, 'phone': '010-692-6593 x09125', 'website': 'anastasia.net', 'company': {'name': 'Deckow-Crist', 'catchPhrase': 'Proactive didactic contingency', 'bs': 'synergize scalable supply-chains'}}, {'id': 3, 'name': 'Clementine Bauch', 'username': 'Samantha', 'email': 'Nathan@yesenia.net', 'address': {'street': 'Douglas Extension', 'suite': 'Suite 847', 'city': 'McKenziehaven', 'zipcode': '59590-4157', 'geo': {'lat': '-68.6102', 'lng': '-47.0653'}}, 'phone': '1-463-123-4447', 'website': 'ramiro.info', 'company': {'name': 'Romaguera-Jacobson', 'catchPhrase': 'Face to face bifurcated interface', 'bs': 'e-enable strategic applications'}}, {'id': 4, 'name': 'Patricia Lebsack', 'username': 'Karianne', 'email': 'Julianne.OConner@kory.org', 'address': {'street': 'Hoeger Mall', 'suite': 'Apt. 692', 'city': 'South Elvis', 'zipcode': '53919-4257', 'geo': {'lat': '29.4572', 'lng': '-164.2990'}}, 'phone': '493-170-9623 x156', 'website': 'kale.biz', 'company': {'name': 'Robel-Corkery', 'catchPhrase': 'Multi-tiered zero tolerance productivity', 'bs': 'transition cutting-edge web services'}}, {'id': 5, 'name': 'Chelsey Dietrich', 'username': 'Kamren', 'email': 'Lucio_Hettinger@annie.ca', 'address': {'street': 'Skiles Walks', 'suite': 'Suite 351', 'city': 'Roscoeview', 'zipcode': '33263', 'geo': {'lat': '-31.8129', 'lng': '62.5342'}}, 'phone': '(254)954-1289', 'website': 'demarco.info', 'company': {'name': 'Keebler LLC', 'catchPhrase': 'User-centric fault-tolerant solution', 'bs': 'revolutionize end-to-end systems'}}, {'id': 6, 'name': 'Mrs. Dennis Schulist', 'username': 'Leopoldo_Corkery', 'email': 'Karley_Dach@jasper.info', 'address': {'street': 'Norberto Crossing', 'suite': 'Apt. 950', 'city': 'South Christy', 'zipcode': '23505-1337', 'geo': {'lat': '-71.4197', 'lng': '71.7478'}}, 'phone': '1-477-935-8478 x6430', 'website': 'ola.org', 'company': {'name': 'Considine-Lockman', 'catchPhrase': 'Synchronised bottom-line interface', 'bs': 'e-enable innovative applications'}}, {'id': 7, 'name': 'Kurtis Weissnat', 'username': 'Elwyn.Skiles', 'email': 'Telly.Hoeger@billy.biz', 'address': {'street': 'Rex Trail', 'suite': 'Suite 280', 'city': 'Howemouth', 'zipcode': '58804-1099', 'geo': {'lat': '24.8918', 'lng': '21.8984'}}, 'phone': '210.067.6132', 'website': 'elvis.io', 'company': {'name': 'Johns Group', 'catchPhrase': 'Configurable multimedia task-force', 'bs': 'generate enterprise e-tailers'}}, {'id': 8, 'name': 'Nicholas Runolfsdottir V', 'username': 'Maxime_Nienow', 'email': 'Sherwood@rosamond.me', 'address': {'street': 'Ellsworth Summit', 'suite': 'Suite 729', 'city': 'Aliyaview', 'zipcode': '45169', 'geo': {'lat': '-14.3990', 'lng': '-120.7677'}}, 'phone': '586.493.6943 x140', 'website': 'jacynthe.com', 'company': {'name': 'Abernathy Group', 'catchPhrase': 'Implemented secondary concept', 'bs': 'e-enable extensible e-tailers'}}, {'id': 9, 'name': 'Glenna Reichert', 'username': 'Delphine', 'email': 'Chaim_McDermott@dana.io', 'address': {'street': 'Dayna Park', 'suite': 'Suite 449', 'city': 'Bartholomebury', 'zipcode': '76495-3109', 'geo': {'lat': '24.6463', 'lng': '-168.8889'}}, 'phone': '(775)976-6794 x41206', 'website': 'conrad.com', 'company': {'name': 'Yost and Sons', 'catchPhrase': 'Switchable contextually-based project', 'bs': 'aggregate real-time technologies'}}, {'id': 10, 'name': 'Clementina DuBuque', 'username': 'Moriah.Stanton', 'email': 'Rey.Padberg@karina.biz', 'address': {'street': 'Kattie Turnpike', 'suite': 'Suite 198', 'city': 'Lebsackbury', 'zipcode': '31428-2261', 'geo': {'lat': '-38.2386', 'lng': '57.2232'}}, 'phone': '024-648-3804', 'website': 'ambrose.net', 'company': {'name': 'Hoeger LLC', 'catchPhrase': 'Centralized empowering task-force', 'bs': 'target end-to-end models'}}]

Oh dear! One huge line with no newlines. Depending on your console settings, this might appear as one very long line. Alternatively, your console output might have its word-wrapping mode on, which is the most common situation. Unfortunately, that doesn’t make the output much friendlier!

If you look at the first and last characters, you can see that this appears to be a list. You might be tempted to start writing a loop to print the items:

for user in users:
    print(user)

This for loop would print each object on a separate line, but even then, each object takes up way more space than can fit on a single line. Printing in this way does make things a bit better, but it’s by no means ideal. The above example is a relatively simple data structure, but what would you do with a deeply nested dictionary 100 times the size?

Sure, you could write a function that uses recursion to find a way to print everything. Unfortunately, you’ll likely run into some edge cases where this won’t work. You might even find yourself writing a whole module of functions just to get to grips with the structure of the data!

Enter the pprint module!

Working With `pprint`

pprint is a Python module made to print data structures in a pretty way. It has long been part of the Python standard library, so installing it separately isn’t necessary. All you need to do is to import its pprint() function:

>>>

>>> from pprint import pprint

Then, instead of going with the normal print(users) approach as you did in the example above, you can call your new favorite function to make the output pretty:

>>>

>>> pprint(users)

This function prints users—but in a new-and-improved pretty way:

>>>

>>> pprint(users)
[{'address': {'city': 'Gwenborough',
              'geo': {'lat': '-37.3159', 'lng': '81.1496'},
              'street': 'Kulas Light',
              'suite': 'Apt. 556',
              'zipcode': '92998-3874'},
  'company': {'bs': 'harness real-time e-markets',
              'catchPhrase': 'Multi-layered client-server neural-net',
              'name': 'Romaguera-Crona'},
  'email': 'Sincere@april.biz',
  'id': 1,
  'name': 'Leanne Graham',
  'phone': '1-770-736-8031 x56442',
  'username': 'Bret',
  'website': 'hildegard.org'},
 {'address': {'city': 'Wisokyburgh',
              'geo': {'lat': '-43.9509', 'lng': '-34.4618'},
              'street': 'Victor Plains',
              'suite': 'Suite 879',
              'zipcode': '90566-7771'},
  'company': {'bs': 'synergize scalable supply-chains',
              'catchPhrase': 'Proactive didactic contingency',
              'name': 'Deckow-Crist'},
  'email': 'Shanna@melissa.tv',
  'id': 2,
  'name': 'Ervin Howell',
  'phone': '010-692-6593 x09125',
  'username': 'Antonette',
  'website': 'anastasia.net'},

 ...

 {'address': {'city': 'Lebsackbury',
              'geo': {'lat': '-38.2386', 'lng': '57.2232'},
              'street': 'Kattie Turnpike',
              'suite': 'Suite 198',
              'zipcode': '31428-2261'},
  'company': {'bs': 'target end-to-end models',
              'catchPhrase': 'Centralized empowering task-force',
              'name': 'Hoeger LLC'},
  'email': 'Rey.Padberg@karina.biz',
  'id': 10,
  'name': 'Clementina DuBuque',
  'phone': '024-648-3804',
  'username': 'Moriah.Stanton',
  'website': 'ambrose.net'}]

Read the full article at https://realpython.com/python-pretty-print/ »

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The Real Python Podcast – Episode #88: Discussing Type Hints, Protocols, and Ducks in Python

2021-12-03T12:00:00+00:00

There seem to be three kinds of Python developers: those unaware of type hints or have no opinion, ones that embrace them, and others who have an allergic reaction at the mention of them. Python is famously a dynamically typed language, but there are advantages to adding type hints to your code. This week on the show, we have Luciano Ramalho to discuss his recent talk titled, "Type hints, protocols, and good sense."

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Advent of Code: Solving Your Puzzles With Python

2021-12-01T14:00:00+00:00

Advent of Code is an online Advent calendar where you’ll find new programming puzzles offered each day from December 1st to the 25th. While you can solve the puzzles at any time, the excitement when new puzzles unlock is really something special. You can participate in Advent of Code in any programming language—including Python!

This tutorial will help you get started with solving puzzles and earning your first golden stars.

In this tutorial, you’ll learn:

What an online Advent calendar is
How solving puzzles can advance your programming skills
How you can participate in the Advent of Code
How you can organize your code and tests when solving Advent of Code puzzles
How test-driven development can be used when solving puzzles

Advent of Code puzzles are designed to be approachable by anyone with an interest in problem-solving. You don’t need a heavy computer science background to participate. Instead, Advent of Code is a great arena for learning new skills and testing out new features of Python.

Free Bonus: Click here to get a Python Cheat Sheet and learn the basics of Python 3, like working with data types, dictionaries, lists, and Python functions.

Puzzling in Programming?

Working on puzzles may seem like a waste of your available programming time. After all, it seems like you’re not really producing anything useful and you’re not advancing your current projects forward.

However, there are several advantages to taking some time off to practice with programming puzzles:

Programming puzzles are usually better specified and more contained than your regular job tasks. They offer you the chance to practice logical thinking on problems that are less complex than the ones you typically need to handle in your day job.
You can often challenge yourself with several similar puzzles. This allows you to build procedural memory, much like muscle memory, and get experience with structuring certain kinds of code.
Puzzles are often designed with an eye towards a solution. They allow you to learn about and apply algorithms that are tried and tested and are an important part of any programmer’s toolbox.
For some puzzle solutions, even the greatest supercomputers can be too slow if the algorithm is inefficient. You can analyze the performance of your solution and get experience to help you understand when a straightforward method is fast enough and when a more optimized procedure is necessary.
Most programming languages are well-suited for solving programming puzzles. This gives you a great opportunity to compare different programming languages for different tasks. Puzzles are also a great way for getting to know a new programming language or trying out some of the newest features of your favorite language.

On top of all of this, challenging yourself with a programming puzzle is often pretty fun! When you add it all up, setting aside some time for puzzles can be very rewarding.

Exploring Options for Solving Programming Puzzles Online

Luckily, there are many websites where you can find programming puzzles and try to solve them. There are often differences in the kinds of problems these websites present, how you submit your solutions, and what kind of feedback and community the sites can offer. You should therefore take some time to look around and find those that appeal the most to you.

In this tutorial, you’ll learn about Advent of Code, including what kind of puzzles you can find there and which tools and tricks you can employ to solve them. However, there are also other places where you can get started solving programming puzzles:

Exercism has learning tracks in many different programming languages. Each learning track offers small tutorials about different programming concepts, coding challenges, and mentors that give you feedback on your solutions.
Project Euler has been around for a long time. The site offers hundreds of puzzles, usually formulated as math problems. You can solve the problems in any programming language, and once you’ve solved a puzzle, you get access to a community thread where you can discuss your solution with others.
Code Wars offers tons of coding challenges, which they call katas. You can solve puzzles in many different programming languages with their built-in editor and automated tests. Afterward, you can compare your solutions to others’ and discuss strategies in the forums.
HackerRank has great features if you’re looking for a job. They offer certifications in many different skills, including problem-solving and Python programming, as well as a job board that lets you show off your puzzle-solving skills as part of your job applications.

There are many other sites available where you can practice your puzzle-solving skills. In the rest of this tutorial, you’ll focus on what Advent of Code has to offer.

Preparing for Advent of Code: 25 Fresh Puzzles for Christmas

It’s time for Advent of Code! It was started by Eric Wastl in 2015. Since then, a new advent calendar of twenty-five new programming puzzles has been published every December. The puzzles have gotten more and more popular over the years. More than 170,000 people have solved at least one of the puzzles from 2020.

Note: Traditionally, an Advent calendar is a calendar used to count the days of Advent while waiting for Christmas. Over the years, Advent calendars have become more commercial and have lost some of their Christian connection.

Most Advent calendars start on December 1st and end on December 24th, Christmas Eve, or December 25th, Christmas Day. Nowadays, there are all kinds of Advent calendars available, including LEGO calendars, tea calendars, and cosmetics calendars.

In traditional Advent calendars, you open one door every day to reveal what’s inside. Advent of Code mimics this by letting you open one puzzle each day from December 1st to December 25th. For each puzzle you solve, you’ll earn golden stars that are yours to keep.

In this section, you’ll get more familiar with Advent of Code and see a glimpse of your first puzzle. Later, you’ll look at the details of how you can solve these puzzles and practice solving a few of the puzzles yourself.

Advent of Code Puzzles

Advent of Code is an online Advent calendar where a new puzzle is published every day from December 1st to December 25th. Each puzzle becomes available at midnight, US Eastern Time. An Advent of Code puzzle has a few typical characteristics:

Each puzzle consists of two parts, but the second part isn’t revealed until you finish the first part.
You’ll earn one golden star (⭐) for each part that you finish. This means you can earn two stars per day and fifty stars if you solve all the puzzles for one year.
The puzzle is the same for everyone, but you need to solve it based on personalized input that you get from the Advent of Code site. This means that your answer to a puzzle will be different from someone else’s, even if you use the same code to calculate it.

You can participate in a global race to be the first to solve each puzzle. However, this is usually pretty crowded with highly skilled, competitive programmers. Advent of Code is probably going to be more fun if you use it as practice for yourself or if you challenge your friends and coworkers to a small, friendly competition.

Read the full article at https://realpython.com/python-advent-of-code/ »

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Data Visualization Interfaces in Python With Dash

2021-11-30T14:00:00+00:00

In the past, creating analytical web applications was a task for seasoned developers that required knowledge of multiple programming languages and frameworks. That’s no longer the case. Nowadays, you can make data visualization interfaces using pure Python. One popular tool for this is Dash.

Dash gives data scientists the ability to showcase their results in interactive web applications. You don’t need to be an expert in web development. In an afternoon, you can build and deploy a Dash app to share with others.

In this course, you’ll learn how to:

Create a Dash application
Use Dash core components and HTML components
Customize the style of your Dash application
Use callbacks to build interactive applications
Deploy your application on Heroku

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Building a Neural Network & Making Predictions With Python AI

2021-11-23T14:00:00+00:00

If you’re just starting out in the artificial intelligence (AI) world, then Python is a great language to learn since most of the tools are built using it. Deep learning is a technique used to make predictions using data, and it heavily relies on neural networks. This course will show you how to build a neural network from scratch.

In a production setting, you would use a deep learning framework like TensorFlow or PyTorch instead of building your own neural network. That said, having some knowledge of how neural networks work is helpful because you can use it to better architect your deep learning models.

In this course, you’ll learn:

What artificial intelligence is
How both machine learning and deep learning play a role in AI
How a neural network functions internally
How to build a neural network from scratch using Python

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Python Community Interview With Eric Wastl

2021-11-22T14:00:00+00:00

This week, we’re joined by Eric Wastl, a Senior Architect at TCGPlayer and the founder of Advent of Code (AoC). Join us as we discuss the inception of AoC, how to avoid common pitfalls when solving code challenges in AoC, and what Eric gets up to in the “3.8 seconds” of free time he has per year.

If you’re looking forward to participating in Advent of Code after reading this interview, then you might be interested in a practical guide to puzzling with Advent of Code.

Ricky: Thanks for joining me, Eric. You’re perhaps most well known for being the founder of Advent of Code, which we’ll talk about shortly, but you’re also the Senior Architect at TCGPlayer. Tell us a little about your day-to-day life there and what interesting problems you get to solve.

Eric: I’ve been with TCGPlayer for about a year. The work I do ranges from tricky algorithms, Kubernetes, vendor selection, and infrastructure scaling to training, architecture planning, technical candidate assessment, and running big internal hackathons.

Read the full article at https://realpython.com/interview-eric-wastl/ »

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The Real Python Podcast – Episode #87: Building a Content Aggregator and Working With RSS in Python

2021-11-19T12:00:00+00:00

Have you wanted to work with RSS feeds in Python? Maybe you're looking for a new project to build for your portfolio that uses Django, unit tests, and custom commands. This week on the show, we have Real Python author Ricky White to talk about his recent step-by-step project titled, "Build a Content Aggregator in Python."

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Python News: What's New From October 2021?

2021-11-17T14:00:00+00:00

A culmination of great work done by volunteers worldwide, the release of Python 3.10 dominated the Python community’s news cycle in October 2021. At the same time that this release was making new features available, Python got recognition as the top programming language for the month in the TIOBE Programming Community index.

There are also some new opportunities for you to support the community by participating in the Python Developer Survey and answering the PyCon US 2022 Call for Proposals.

Let’s dive into the biggest Python news from the past month!

Free Bonus: Click here to get a Python Cheat Sheet and learn the basics of Python 3, like working with data types, dictionaries, lists, and Python functions.

The Python 3.10 Release

New versions of Python are now released annually. We can look forward to the core developers sharing a lovely goody bag with the rest of us every October. With Python 3.10, which came out of beta on October 4th, everyone had something exciting to anticipate.

Each release of Python has a release manager who’s responsible for coordinating all changes and for building and preparing the files for distribution. The release manager for Python 3.10 and 3.11 is Pablo Galindo Salgado. In a first for Python, he built and released Python live on YouTube.

Python 3.10 Highlights

The new release includes lots of improvements to the language. Among our favorites are improved error messages, simplified syntax for type unions, and structural pattern matching.

Improved error messages will make your life easier, whether you’re a new Python developer or an experienced one. In particular, the feedback that you get when your code isn’t valid Python is more pointed and actionable in Python 3.10 than in previous versions. As an example, consider the following code, where there’s no closing bracket at the end of the first line:

news = ["errors", "types", "patterns"
print(", ".join(news))

In Python 3.9 and earlier, you’ll see the following if you try to run this code:

  File "errors.py", line 2
    print(", ".join(news))
        ^
SyntaxError: invalid syntax

Read the full article at https://realpython.com/python-news-october-2021/ »

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Building Lists With Python's .append()

2021-11-16T14:00:00+00:00

Adding items to a list is a fairly common task in Python, so the language provides a bunch of methods and operators that can help you out with this operation. One of those methods is .append(). With .append(), you can add items to the end of an existing list object. You can also use .append() in a for loop to populate lists programmatically.

In this course, you’ll learn how to:

Work with .append()
Populate lists using .append() and a for loop
Replace .append() with list comprehensions
Work with .append() in array.array() and collections.deque()

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Securely Deploy a Django App With Gunicorn, Nginx, & HTTPS

2021-11-15T14:00:00+00:00

Taking a Django app from development to production is a demanding but rewarding process. This tutorial will take you through that process step by step, providing an in-depth guide that starts at square one with a no-frills Django application and adds in Gunicorn, Nginx, domain registration, and security-focused HTTP headers. After going over this tutorial, you’ll be better equipped to take your Django app into production and serve it to the world.

In this tutorial, you’ll learn:

How you can take your Django app from development to production
How you can host your app on a real-world public domain
How to introduce Gunicorn and Nginx into the request and response chain
How HTTP headers can fortify your site’s HTTPS security

To make the most out of this tutorial, you should have an introductory-level understanding of Python, Django, and the high-level mechanics of HTTP requests.

You can download the Django project used in this tutorial by following the link below:

Get Source Code: Click here to get the companion Django project used in this tutorial.

Starting With Django and WSGIServer

You’ll use Django as the framework at the core of your web app, using it for URL routing, HTML rendering, authentication, administration, and backend logic. In this tutorial, you’ll supplement the Django component with two other layers, Gunicorn and Nginx, in order to serve the application scalably. But before you do that, you’ll need to set up your environment and get the Django application itself up and running.

Setting Up a Cloud Virtual Machine (VM)

First, you’ll need to launch and set up a virtual machine (VM) on which the web application will run. You should familiarize yourself with at least one infrastructure as a service (IaaS) cloud service provider to provision a VM. This section will walk you through the process at a high level but won’t cover every step in detail.

Using a VM to serve a web app is an example of IaaS, where you have full control over the server software. Other options besides IaaS do exist:

A serverless architecture allows you to compose the Django app only and let a separate framework or cloud provider handle the infrastructure side.
A containerized approach allows multiple apps to run independently on the same host operating system.

For this tutorial, though, you’ll use the tried-and-true route of serving Nginx and Django directly on IaaS.

Two popular options for virtual machines are Azure VMs and Amazon EC2. To get more help with launching the instance, you should refer to the documentation for your cloud provider:

For Azure VMs, follow their quickstart guide for creating a Linux virtual machine in the Azure portal.
For Amazon EC2, learn how to get set up.

The Django project and everything else involved in this tutorial sit on a t2.micro Amazon EC2 instance running Ubuntu Server 20.04.

One important component of VM setup is inbound security rules. These are fine-grained rules that control the inbound traffic to your instance. Create the following inbound security rules for initial development, which you’ll modify in production:

Reference	Type	Protocol	Port Range	Source
1	Custom	TCP	8000	`my-laptop-ip-address/32`
2	Custom	All	All	`security-group-id`
3	SSH	TCP	22	`my-laptop-ip-address/32`

Now you’ll walk through these one at a time:

Rule 1 allows TCP over port 8000 from your personal computer’s IPv4 address, allowing you to send requests to your Django app when you serve it in development over port 8000.
Rule 2 allows inbound traffic from network interfaces and instances that are assigned to the same security group, using the security group ID as the source. This is a rule included in the default AWS security group that you should tie to your instance.
Rule 3 allows you to access your VM via SSH from your personal computer.

You’ll also want to add an outbound rule to allow outbound traffic to do things such as install packages:

Type	Protocol	Port Range	Source
Custom	All	All	`0.0.0.0/0`

Tying that all together, your initial AWS security rule set can consist of three inbound rules and one outbound rule. These, in turn, come from three separate security groups—the default group, a group for HTTP access, and a group for SSH access:

From your local computer, you can then SSH into the instance:

Read the full article at https://realpython.com/django-nginx-gunicorn/ »

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The Real Python Podcast – Episode #86: The Legacy of OLPC and Charismatic Pitfalls in Teaching Programming

2021-11-12T12:00:00+00:00

Do you remember the One Laptop Per Child program? What went wrong, and what can we learn from the program's failure? What are the potential pitfalls of charismatic technology, and how can we avoid them when introducing students to programming? This week on the show, former guest Al Sweigart and author Morgan Ames are here to talk about her book "The Charisma Machine - The Life, Death, and Legacy of One Laptop per Child."

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Advanced Visual Studio Code for Python Developers

2021-11-10T14:00:00+00:00

Visual Studio Code, or VS Code for short, is a free and open source code editor by Microsoft. You can use VS Code as a lightweight code editor to make quick changes, or you can configure it as an integrated development environment (IDE) through the use of third-party extensions. In this tutorial, you’re going to look at how to get the most out of VS Code for Python development.

During this tutorial, you’ll learn how you can configure, extend, and optimize VS Code for a more effective and productive Python development environment. After finishing this tutorial, you’ll have a variety of tools to help you be more productive using VS Code. It can be a powerful tool for rapid Python development.

In this tutorial, you’ll learn how to:

Customize your user interface
Run and monitor Python tests
Lint and format your code automatically
Leverage type annotations and Pylance to write code faster with higher accuracy
Configure and utilize both local and remote debugging
Set up data science tools

As usual, this tutorial is full of links, tips, and tricks to help you on your way.

If you haven’t already installed Visual Studio Code or the Python extension, you’ll need both for this tutorial. If you’re just getting started with VS Code, you might want to check out Jon Fincher’s tutorial on Python development in Visual Studio Code before continuing with this one.

Free Bonus: 5 Thoughts On Python Mastery, a free course for Python developers that shows you the roadmap and the mindset you’ll need to take your Python skills to the next level.

Mastering the Visual Studio Code User Interface

By default, VS Code’s user interface is designed for everyone—whether you’re writing C++, doing front-end development with JavaScript and CSS, or using data science tools like Jupyter Notebooks. In this first section, you’ll explore how to tailor VS Code to support how you work.

Keyboard Shortcuts

For almost everything that you do in VS Code, you can do it directly from the keyboard. You can map all activities in VS Code, whether they’re built-in or provided via extensions, to a keyboard shortcut.

A small subset of built-in commands is already mapped in Keyboard Shortcuts. If you want to learn these default shortcuts, print out the PDF for Windows, macOS, or Linux and pin it next to your monitor.

As a Python developer, a lot of the commands you’ll use in Visual Studio Code are provided from extensions, similar to the Python extension that you already installed. These don’t come with shortcuts mapped by default, but you can configure them using VS Code’s Keyboard Shortcuts editor.

Using the Keyboard Shortcuts Editor

Open the Keyboard Shortcuts editor by going to File → Preferences → Keyboard Shortcuts or Code → Preferences → Keyboard Shortcuts on macOS:

In this editor, you can see a list of all the existing shortcuts along with their details:

Command: The command or action to be run
Keybinding: The sequence of keys to press to trigger this command, with a blank indicating that there’s no mapping
When: Conditions that need to be met for this keybinding to work, with a minus sign (-) indicating that there are no requirements
Source: Where this binding was configured, either defined by Default, User, or Extension, the last one indicating that you provided it by installing a keymap extension

To override an existing binding, right-click on the existing action and click Change Keybinding. To assign a keybinding to a command that has no binding, double-click on it. If the key sequence you press is already assigned to something else, VS Code will warn you with a link to see which commands are mapped to this keybinding.

As an example, type python create terminal in the search box at the top. If no results come up, make sure you have the Python extension installed. Press Enter to assign a keybinding, like Ctrl+Alt+T, and then hit Enter again.

To assign that shortcut to only work when you’re editing Python code, right-click on the shortcut and select Change When Expression. Enter the expression editorLangId == 'python':

There are more conditional operators to choose from if you need something more specific. Here are some examples to get you started:

Use resourceFilename == '__init__.py' when the file you’re editing is __init__.py
Use editorLangId == 'python' when working with Python. If needed, you can also replace 'python' with another language identifier.
Use editorHasSelection for when you’re inside the editor.

Once you’ve configured this extension, open up a Python file in the editor to try it out by pressing your newly assigned keyboard shortcut Ctrl+Alt+T to open up a Python terminal.

Read the full article at https://realpython.com/advanced-visual-studio-code-python/ »

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Using plt.scatter() to Visualize Data in Python

2021-11-09T14:00:00+00:00

An important part of working with data is being able to visualize it. Python has several third-party modules you can use for data visualization. One of the most popular modules is Matplotlib and its submodule pyplot, often referred to using the alias plt. Matplotlib provides a very versatile tool called plt.scatter() that allows you to create both basic and more complex scatter plots.

In this course, you’ll learn how to:

Create a scatter plot using plt.scatter()
Use the required and optional input parameters
Customize scatter plots for basic and more advanced plots
Represent more than two dimensions on a scatter plot

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Build a Command-Line To-Do App With Python and Typer

2021-11-08T14:00:00+00:00

Building an application to manage your to-do list can be an interesting project when you’re learning a new programming language or trying to take your skills to the next level. In this tutorial, you’ll build a functional to-do application for the command line using Python and Typer, which is a relatively young library for creating powerful command-line interface (CLI) applications in almost no time.

With a project like this, you’ll apply a wide set of core programming skills while building a real-world application with real features and requirements.

In this tutorial, you’ll learn how to:

Build a functional to-do application with a Typer CLI in Python
Use Typer to add commands, arguments, and options to your to-do app
Test your Python to-do application with Typer’s CliRunner and pytest

Additionally, you’ll practice your skills related to processing JSON files by using Python’s json module and managing configuration files with Python’s configparser module. With this knowledge, you’ll be ready to start creating CLI applications right away.

You can download the entire code and all the additional resources for this to-do CLI application by clicking the link below and going to the source_code_final/ directory:

Get Source Code: Click here to get the source code you’ll use to build a to-do app for your command line using Python and Typer.

Demo

In this step-by-step project, you’ll build a command-line interface (CLI) application to manage a to-do list. Your application will provide a CLI based on Typer, a modern and versatile library for creating CLI applications.

Before you get started, check out this demo of how your to-do application will look and work once you get to the end of this tutorial. The first part of the demo shows how to get help on working with the app. It also shows how to initialize and configure the app. The rest of the video demonstrates how to interact with the essential features, such as adding, removing, and listing to-dos:

Nice! The application has a user-friendly CLI that allows you to set up the to-do database. Once there, you can add, remove, and complete to-dos using appropriate commands, arguments, and options. If you ever get stuck, then you can ask for help using the --help option with proper arguments.

Do you feel like kicking off this to-do app project? Cool! In the next section, you’ll plan out how to structure the layout of the project and what tools you’ll use to build it.

Project Overview

When you want to start a new application, you typically start by thinking about how you want the app to work. In this tutorial, you’ll build a to-do app for the command line. You’ll call that application rptodo.

You want your application to have a user-friendly command-line interface that allows your users to interact with the app and manage their to-do lists.

To start off, you want your CLI to provide the following global options:

-v or --version shows the current version and exits the application.
--help shows the global help message for the entire application.

You’ll see these same options in many other CLI applications out there. It’s a nice idea to provide them because most users who work with the command line expect to find them in every app.

Regarding managing a to-do list, your application will provide commands to initialize the app, add and remove to-dos, and manage the to-do completion status:

Command	Description
`init`	Initializes the application’s to-do database
`add DESCRIPTION`	Adds a new to-do to the database with a description
`list`	Lists all the to-dos in the database
`complete TODO_ID`	Completes a to-do by setting it as done using its ID
`remove TODO_ID`	Removes a to-do from the database using its ID
`clear`	Removes all the to-dos by clearing the database

These commands provide all the functionality you need to turn your to-do application into a minimum viable product (MVP) so that you can publish it to PyPI or the platform of your choice and start getting feedback from your users.

To provide all these features in your to-do application, you’ll need to complete a few tasks:

Build a command-line interface capable of taking and processing commands, options, and arguments
Select an appropriate data type to represent your to-dos
Implement a way to persistently store your to-do list
Define a way to connect that user interface with the to-do data

These tasks relate well to what is known as the Model-View-Controller design, which is an architectural pattern. In this pattern, the model takes care of the data, the view deals with the user interface, and the controller connects both ends to make the application work.

Read the full article at https://realpython.com/python-typer-cli/ »

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The Real Python Podcast – Episode #85: Exploring Django Templates, Tags, and Filters

2021-11-05T12:00:00+00:00

Are you getting the most out of the Django framework? It's a powerful web framework if you're not interested in reinventing the wheel. Django includes a useful template system with inheritance for composing reusable HTML. This week on the show, we have previous guest and Real Python author Christopher Trudeau to talk about his recent articles and courses about Django.

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Build a Content Aggregator in Python

2021-11-03T14:00:00+00:00

In this project-based tutorial, you’ll build a content aggregator from scratch using Python and the popular framework Django.

With so much content coming out online daily, it can be time consuming to go to multiple sites and sources to consume information about your favorite subjects. This is why content aggregators are so popular and powerful, as you can use them to view all the latest news and content in one place.

Whether you’re looking for a portfolio project or ways in which to extend future projects beyond simple CRUD capabilities, this tutorial will have something for you.

In this tutorial, you’ll learn:

How to work with RSS feeds
How to create a Django custom management command
How to run your custom command automatically on a schedule
How to use unit tests to test your Django app’s functionality

Click the link below to download the code for this project and follow along as you build your own content aggregator:

Get Source Code: Click here to get the source code you’ll use to build a content aggregator with Django and Python in this tutorial.

Demo: What You’ll Build

You’ll build your own podcast content aggregator in Python named pyCasts! by following this tutorial from start to finish.

The application will be a single web page displaying the latest Python podcast episodes from The Real Python Podcast and the Talk Python to Me Podcast. After completing this tutorial, you can practice what you’ve learned by adding more podcast feeds to the application.

Here’s a quick demo video of how it will look in action:

There are many moving parts behind the scenes that make this work efficiently and effectively in an automated fashion. You’ll learn about all of them in this tutorial. Get ready to delve in.

Project Overview

In order to be able to display the content to the end user, you have several steps to follow:

Set up the project
Build the podcast model
Create the homepage view
Parse a podcast RSS feed
Create a Django custom command
Add additional feeds
Schedule tasks with django-apscheduler

You’ll walk through each of these over the course of this tutorial. Now you’ll look at which technologies and frameworks you’re going to use for the above steps.

In order to fetch the podcast RSS feeds into your application and parse them, you’ll learn how to use the feedparser library. You’ll use this library to extract only the newest episode data from the feed, which you’ll marshall into an Episode model and save to the database with the Django ORM.

You could add this code to a script and manually run it periodically, but that would defeat the point of having an aggregator to save time. Instead, you’ll learn how to use a built-in Django tool called a custom management command. To parse and save the data, you’ll run your code from within Django itself.

With help from the django-apscheduler library, you’ll set a schedule for your function calls, which are also called jobs. You can then use the Django admin panel to view which jobs ran and when. This will ensure that the fetching and parsing of your feed will happen automatically without needing admin intervention.

You’ll then use the Django template engine to show the user the queried context—in other words, the latest episodes.

Prerequisites

To get the most out of this tutorial, you should be comfortable with the following concepts and technologies:

Python basics
Virtual environment setup and usage
A basic level of HTML and CSS
Django fundamentals, such as its folder structure, URL routing, migrations, and how to create a project and app

You might also find it helpful to have some experience with Bootstrap 4.

Read the full article at https://realpython.com/build-a-content-aggregator-python/ »

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Reading Input and Writing Output in Python

2021-11-02T14:00:00+00:00

You often need to set up a program to communicate with the outside world by obtaining input data from the user and displaying data back to the user. This course will introduce you to reading input and writing output in Python.

By the end of this course, you’ll know how to:

Take user input from the keyboard with the built-in function input()
Display output to the console with the built-in function print()

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The Real Python Podcast – Episode #84: Creating and Manipulating PDFs in Python With borb

2021-10-29T12:00:00+00:00

Have you wanted to generate PDFs from your Python project? Many of the current libraries require designing the document down at the pixel level. Would you be interested in a tool that lets you specify the page layout while it handles the specific details of laying out the text? This week on the show, we talk with Joris Schellekens about his library for creating and manipulating PDFs named borb.

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Writing Idiomatic Python

2021-10-26T14:00:00+00:00

What programming idioms are unique to Python? This course is both a short overview for people coming from other languages as well as an introduction for programming beginners to the idiomatic practices within Python.

In this course, you’ll learn:

How to access and interpret The Zen of Python
How to set up a script
How to test truth values
How to swap variables in-place
How to create Pythonic for loops

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The Real Python Podcast – Episode #83: Ready to Publish Your Python Packages?

2021-10-22T12:00:00+00:00

Are you interested in sharing your Python project with the broader world? Would you like to make it easily installable using pip? How do you create Python packages that share your code in a scalable and maintainable way? This week on the show, Real Python author and former guest Dane Hillard returns to talk about his new book, "Publishing Python Packages."

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Python Assignment Expressions and Using the Walrus Operator

2021-10-19T14:00:00+00:00

Each new version of Python adds new features to the language. For Python 3.8, the biggest change is the addition of assignment expressions. Specifically, the := operator gives you a new syntax for assigning variables in the middle of expressions. This operator is colloquially known as the walrus operator.

This course is an in-depth introduction to the walrus operator. You’ll learn some of the motivations for the syntax update and explore some examples where assignment expressions can be useful.

In this course, you’ll learn how to:

Identify the walrus operator and understand its meaning
Understand use cases for the walrus operator
Avoid repetitive code by using the walrus operator
Convert between code using the walrus operator and code using other assignment methods
Understand the impacts on backward compatibility when using the walrus operator
Use appropriate style in your assignment expressions

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

The Real Python Podcast – Episode #82: Welcoming the CPython Developer in Residence

2021-10-15T12:00:00+00:00

Earlier this year, the Python Software Foundation announced the creation of the Developer in Residence role. The first Visionary Sponsors of the PSF have provided funding for this new role for one year. What development responsibilities does this job address? This week on the show, we talk to previous guest Łukasz Langa about becoming the first CPython Developer in Residence.

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Using Pygame to Build an Asteroids Game in Python

2021-10-12T14:00:00+00:00

Do you want to create your own computer games but like Python too much to abandon it for a career as a game developer? There’s a solution for that! With the Pygame module, you can use your amazing Python skills to create games, from the basic to the very complex. Below, you’ll learn how to use Pygame by making a clone of the Asteroids game!

In this course, you’ll learn how to build a complete game, including:

Loading images and displaying them on the screen
Handling user input in order to control the game
Moving objects according to the game logic
Detecting collisions between objects
Displaying text on the screen
Playing sounds

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

The Real Python Podcast – Episode #81: Exploring the New Features of Python 3.10

2021-10-08T12:00:00+00:00

Python 3.10 is here! This week on the show, two former guests and Real Python authors return to talk about the new version. Geir Arne Hjelle's article was posted to the site Monday, and it's titled "Python 3.10: Cool New Features for You to Try". Christopher Trudeau's video course came out on Tuesday, and it covers the topics from the article with multiple visual examples of Python 3.10 code.

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Real Python

Dependency Management With Python Poetry

Take Care of Prerequisites

Relevant Terminology

Python Poetry Installation

Get Started With Python Poetry

Create a New Poetry Project

The Real Python Podcast – Episode #90: A Python Journey: Cyber Security, Automating AWS, and TDD

Host Your Django Project on Heroku

Java vs Python: Basic Python for Java Developers

Where Does Python Come From?

What Is the Philosophy of Python?

Python Code Is Readable

The Real Python Podcast – Episode #89: Solving Advent of Code Puzzles With Python

Binary, Bytes, and Bitwise Operators in Python

Prettify Your Data Structures With Pretty Print in Python

Understanding the Need for Python’s Pretty Print

Working With pprint

The Real Python Podcast – Episode #88: Discussing Type Hints, Protocols, and Ducks in Python

Advent of Code: Solving Your Puzzles With Python

Puzzling in Programming?

Exploring Options for Solving Programming Puzzles Online

Preparing for Advent of Code: 25 Fresh Puzzles for Christmas

Advent of Code Puzzles

Data Visualization Interfaces in Python With Dash

Building a Neural Network & Making Predictions With Python AI

Python Community Interview With Eric Wastl

The Real Python Podcast – Episode #87: Building a Content Aggregator and Working With RSS in Python

Python News: What's New From October 2021?

The Python 3.10 Release

Python 3.10 Highlights

Building Lists With Python's .append()

Securely Deploy a Django App With Gunicorn, Nginx, & HTTPS

Starting With Django and WSGIServer

Setting Up a Cloud Virtual Machine (VM)

The Real Python Podcast – Episode #86: The Legacy of OLPC and Charismatic Pitfalls in Teaching Programming

Advanced Visual Studio Code for Python Developers

Mastering the Visual Studio Code User Interface

Keyboard Shortcuts

Using the Keyboard Shortcuts Editor

Using plt.scatter() to Visualize Data in Python

Build a Command-Line To-Do App With Python and Typer

Demo

Project Overview

The Real Python Podcast – Episode #85: Exploring Django Templates, Tags, and Filters

Build a Content Aggregator in Python

Demo: What You’ll Build

Project Overview

Prerequisites

Reading Input and Writing Output in Python

The Real Python Podcast – Episode #84: Creating and Manipulating PDFs in Python With borb

Writing Idiomatic Python

The Real Python Podcast – Episode #83: Ready to Publish Your Python Packages?

Python Assignment Expressions and Using the Walrus Operator

The Real Python Podcast – Episode #82: Welcoming the CPython Developer in Residence

Using Pygame to Build an Asteroids Game in Python

The Real Python Podcast – Episode #81: Exploring the New Features of Python 3.10

Working With `pprint`