Installing the Alpha/Beta Version

To experience the latest features of Python 3.10, you'll need to install the alpha or beta version. Since these versions are not stable, it's wise not to replace your default Python installation. Instead, you can install Python 3.10 alongside your existing interpreter using the following method:

After executing the above command, you’ll be welcomed by the Python 3.10 Alpha IDLE, ready for exploration.

Type Checking Enhancements

If you're a fan of type checking, you'll be pleased to learn about the numerous enhancements in Python 3.10. One significant improvement is the introduction of the Type Union Operator, which offers a more streamlined syntax:

In addition to type annotations, this enhancement can also be applied with the isinstance() and issubclass() functions.

Type Aliases Syntax Update

Previously, type aliases in Python allowed the creation of aliases for user-defined types. In versions prior to Python 3.10, this was accomplished as follows:

Here, FileName serves as an alias for the basic Python string type. However, in Python 3.10, the syntax for defining type aliases has changed to the following:

This modification simplifies the distinction between regular variable assignments and type aliases for both developers and type checkers. Importantly, this change is backward compatible, meaning you won't need to revise existing code that employs type aliases.

In addition to these changes, the typing module has received further enhancements, particularly with Parameter Specification Variables in PEP 612. While these may not be commonplace in most Python codebases, they are useful for forwarding parameter types from one callable to another, such as in decorators. If this applies to your situation, be sure to review the aforementioned PEP.

Population Count

Python 3.10 introduces the int.bit_count() method, which allows you to calculate the number of ones in the binary representation of an integer, also known as the Population Count:

While this feature is undoubtedly handy, implementing it requires merely a single line of code:

Nonetheless, it adds to Python's appeal by providing useful functionalities out of the box.

Deprecation of Distutils

As new features are introduced, others are deprecated or removed. The distutils package is one such example, being deprecated in Python 3.10 and set for removal in 3.12. This package has been supplanted by setuptools and packaging, so if you are utilizing either, you should be in good shape. However, it's advisable to review your code for any instances of distutils and prepare to phase it out soon.

Context Manager Syntax Improvement

Context managers in Python are invaluable for managing resources such as file operations and database connections. Python 3.10 enhances their syntax, allowing parenthesized context managers to extend across multiple lines, which is particularly useful when you wish to declare several context managers within a single with statement:

As illustrated, you can even reference variables created by one context manager in subsequent ones!

These are just a couple of the various new formatting options available in Python 3.10. The updated syntax offers great flexibility, so you can likely expect it to accommodate most of your needs seamlessly.

Performance Enhancements

As with recent Python releases, 3.10 brings several performance improvements. One of the key enhancements is the optimization of the str(), bytes(), and bytearray() constructors, which are now approximately 30% faster:

Another notable optimization, particularly for those using type annotations, is that function parameters and their annotations are now computed at compile-time rather than at runtime, resulting in function creation being around twice as fast.

Additionally, further optimizations have been made across various parts of the Python core. For detailed information, refer to the following issues in the Python bug tracker: bpo-41718, bpo-42927, and bpo-43452.

Structural Pattern Matching

One of the standout features in Python 3.10 is Structural Pattern Matching. This introduces a match statement similar to the case statements found in other programming languages. However, Python enhances this concept with powerful additional functionalities worth exploring.

In its simplest form, pattern matching consists of the match keyword followed by an expression, which is then evaluated against patterns specified in successive case statements:

In this straightforward example, the variable day serves as the expression, which is compared with individual string literals in the case statements. Notably, the last case employs the _ wildcard, functioning similarly to the default keyword in other languages. This wildcard case can be omitted, resulting in a no-op where None is returned.

Additionally, as shown, the | operator allows for the combination of multiple literals.

The new pattern matching extends beyond basic syntax, offering advanced features such as matching complex patterns:

In the snippet above, we match against a tuple. However, any iterable can be used. As demonstrated, the _ wildcard can also be employed within complex patterns, not just standalone.

If you prefer using classes instead of plain tuples or lists, you can rewrite the matching process as follows:

This method enables matching against class attributes with patterns resembling class constructors. Using this approach, individual attributes are captured into variables, similar to the earlier tuple example.

The first case statement also showcases a guard condition that follows the pattern, which can be beneficial when simple value matching is insufficient, requiring additional conditional checks. The remaining cases illustrate that both keyword arguments (e.g., name=name) and positional arguments function with this constructor-like syntax, along with the _ wildcard.

Pattern matching also supports nested patterns. In such complex cases, capturing sub-patterns into variables for further processing can be achieved using the as keyword, as shown in the second case above.

Finally, the * operator allows for "unpacking" variables in patterns, which also works with the _ wildcard in the *_ pattern.

For additional examples and a complete tutorial, refer to PEP 636.

Closing Thoughts

Python 3.10 introduces many intriguing new features. However, as this is an alpha (soon to be beta) release, it's still not fully tested or ready for production use. Therefore, it’s advisable to refrain from using it just yet. It’s probably best to wait for the full release in October, while keeping an eye on the "What's New In Python 3.10" page for any last-minute updates.

Nonetheless, if you're eager to upgrade, consider downloading the first beta release (anticipated in June) and testing it to ensure your existing codebase is compatible with the upcoming changes, deprecations, or removals of functions/modules.

This video explores the new features in Python 3.10 that developers should be aware of.

This video provides an overview of the new capabilities in Python 3.10.