Table of Contents
1. Type hints in Python
2. Python virtual environment and package management
3. New Python syntax
4. Python testing
Home Backend Development Python Tutorial Four Key Points for Modern Python Programming in 2022

Four Key Points for Modern Python Programming in 2022

Apr 16, 2023 pm 06:22 PM
python programming language

Four Key Points for Modern Python Programming in 2022

As a programming language that has been around for more than 30 years, the popularity of Python has experienced explosive growth in recent years. To make it easier for everyone to better adopt Python and take advantage of all the new and powerful features in the language; InfoWorld has summarized some of the key concepts developers need to understand when writing modern Python in 2022. There are four aspects in total, as follows:

1. Type hints in Python

Python’s recently introduced type hint syntax allows linters and third-party code quality tools to analyze your code before running. and detect possible errors. The more Python code you create is shared with others, the more likely everyone will benefit from using type hints. Each subsequent version of Python introduced more complex and powerful type annotations. If you make a habit of learning how to use type annotations in the short term, you'll be better able to take advantage of each new type hint innovation. It's important to remember that type hints are optional, not required. Not every project requires them. Type hints can make your larger projects easier to understand, but they are not necessary for smaller projects. It's worth noting that while type hints are not enforced at runtime, you can use Pydantic to make it possible. Many widely used Python projects, such as FastAPI, make extensive use of Pydantic.

2. Python virtual environment and package management

For simple projects and less demanding development work, you can usually just use Python's built-in venv tool to separate the project and its requirements. But the latest advances in Python tools provide developers with more choices:

Pyenv: If you need to install multiple Python versions (3.8, 3.9, 3.10) to meet different project requirements, Pyenv allows you to Switch between them globally on a per-project basis. It's worth noting that it has no official Windows support, but an unofficial Windows port does exist.

Pipenv: Dubbed the “Python dev workflow for humans,” Pipenv is designed to manage virtual environments as well as all of a project’s dependencies. It also ensures that dependencies are deterministic - you get the specific versions you want, and they work in the combination you ask for. However, Pipenv doesn't involve any form of packaging, so it's not ideal for projects that you eventually want to upload to PyPI or share with others.

Poetry: Poetry extends Pipenv’s toolset not only to manage projects and requirements, but also to easily deploy projects to PyPI. It also manages virtual environments for you independent of the project directory.

PDM: PDM (short for "Python Development Master") is the latest cutting-edge project in this regard. Like Poetry and Pipenv, PDM provides you with a single interface for setting up a project, managing its dependencies, and building distribution artifacts from it. PDM also uses the PEP 582 standard to store packages locally into projects, eliminating the need to create a virtual environment for each project. But this tool is relatively new, so make sure it works temporarily before adopting it in production.

3. New Python syntax

The development of Python means that the language itself has added many new features. The latest versions of Python have added some useful syntax constructs to make it more powerful and simpler to program. Some recent additions include: Pattern matching The biggest recent addition is structural pattern matching, which appeared in Python 3.10. It's more than just a so-called "switch/case for Python" and lets you make control flow decisions based on the content or structure of an object. The 'walrus operator', named for its appearance (:=), was added in Python 3.8 and introduced assignment expressions, a way to assign a value to a variable and then A method to test this variable in one step. It can reduce verbose code in many common situations, such as checking the return value of a function while retaining the result. Positional-only parameters A small but useful recent addition to Python syntax, positional-only parameters allow you to specify which function arguments must be specified as positional arguments, rather than keyword arguments. The rationale for doing this often includes improving the clarity of the codebase and simplifying future development of the codebase, which is also the goal that many other new features of Python focus on.

4. Python testing

Python has its own built-in testing framework Unittest. Although Unittest is not bad as the default setting, its design and behavior are outdated. The Pytest framework has become a common alternative, is more flexible (you can declare tests on any part of the code, not just a subset), and requires far fewer templates to be written. In addition, Pytest has a large number of add-ons to extend its functionality (for example, for testing asynchronous code).

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