In this quick overview, we're going to talk about Python 3.12 and its new amazing features as well as my personal thoughts on each upgrade/downgrade. My thoughts are specified with the "IMO" (In My Opinion) keyword at the beginning of the quotes.

Nested F-Strings

In Python 3.12, you can have nested f-string phrases. Check the following example.

phrase = f"Hello {f"{name}"}"
# Hello Sadra

IMO: It seems to be quite hard in term of understanding a nested f-string phrase as it might not be as practical as the simple f-strings. I would personally regret using this new feature.

Multiline F-Strings

One cool feature that's been brought to the new 3.12 version is that you can have multiline f-strings.

phrase = f"Hello {
    name # User.name
}"
# Hello Sadra

IMO: This is a handy one. As you can see, you can expand your f-strings as well as document them via comments. That's amazing!

Tokenization is Re-written in C

Since Python 3.11, the tokenizer module has been in Python analyzing your Python lexical and keywords. From now on, due to the new nested and multiline f-strings, this module has been updated and re-written in C and it's almost 40% faster than before. With this huge improvement, all the linting and formatting tools that make use of this module can get a huge performance improvement over this update.

IMO: Now I can run my CI worklfows way faster!!

Distutils is Depricated

There's always been a struggle among the Python community members about setuptools against distutils and the reason that everyone prefers the setuptools (which is a fork of distutils) over the official distutils. That's actually because setuptools is better with lots of more features and functionalities. That's why they decided to remove the distutils standard library and depreciate that.

What's more, pip actually uses setuptools for building the distributions. If you make a venv with python<=3.11 and pip<=22.1 you'll see that the setuptools is already installed there.

$ pip list
Package    Version
---------- -------
pip        23.2.1
setuptools 68.0.0    <--
wheel      0.41.1

The setuptools package is not a standard library. It just uses distutils. Since distutils is no more available and pip>=22.1 is not dependent on setuptools, we'll never have a distributing tool inside a freshly installed Python environment.

The setuptools package has dropped its dependency on the virtualenv package as well. It means even if you install the setuptools, you won't be able to create a virtual environment or even run the following command.

$ python -m venv venv
# ERROR: venv module is not found.

The distutils package has become another whole third-party package. In order to have access to both virtualenv and setuptools, you have to install them separately.

IMO: This deprication has made lots of changes. You won't have acces to any distributing tool anymore. No more distutils, setuptools or virtualenv by default. In fact, this quick change ensures you from a real isolated venv and that's a positive point. From now on, if you make a virtual environment, nothing is installed there except pip.

**kwargs Type Hinting

In the new update, lots of changes have happened to the typing module. I used to use typing.Any for type hinting the **kwargs of my functions and method. That was actually quite a deal but in Python 3.12, you can give it a more precise type annotation using typing.TypedDict.

from typing import TypedDict, Unpack

class Values(TypedDict):
    name: str
    age: int

def main(**kwargs: Unpack[Values]): ...

IMO: I'd prefer to keep kwargs un-annotated for now.

@override Type Hinting

There's a new @override type-annotation included in the typing module. It actually helps you to specify the methods that are meant to be overridden in the OOP design. Using this feature helps the typing tools such as mypy debugging your code in another sense.

from typing import override

class A:
    def greet(): ...

class B(A):
    @override
    def greet(): ...

For instance, in the above example, if you make a typo issue and change B.greet to B.great, your mypy would most likely return a non-zero output in the STDOUT meaning the method that's meant to be overridden is not defined in the base class.

IMO: I find this little trick quite useful actually. Also including a mypy execution in your CI pipelines would help you catch such issues.

New type Defining

There has been a new syntax added to the new Python version. This new convention helps you define the `Type Aliases` easier.

• Before:

    from typing import TypeAlias
  
    Students: TypeAlias = list[str]
  
    def list_students(students: Students) -> None: ...
  

• After:

    type Students = list[str]
  
    def list_students(students: Students) -> None: ...
  

This new convention has changed how functions and methods look in Python as you can design your function scopes as follows.

• Before:

    def list_students(students: List[str], grades: List[float]) -> None: ...
  

• After:

    type Students = List[str]
    type Grades = List[float]
  
    def greet[Students, Grades](students: Students, grades: Grades) -> None: ...
  

The new pattern of the function definition is like def NAME[*TYPES](*ARGS: TYPE) -> TYPE. Keep in mind that the types that are included in front of the name of the function are limited to the function scope.

IMO: I think this feature just violates the readability of the new function. I'd prefer them in the old way if declaration. Highlighting tools might change my mind though. We have see how they're going to deal with these new syntaxes and keywords.

Per-Interpreter GIL

In the new update, we'll have full control over the GIL utilization in the sub-interpreters that we make. As the official docs say..

This (Per-Interpreter GIL) allows Python programs to take full advantage of multiple CPU cores.

We'll be talking about this new integration soon in another blog post. It seems to be a decent improvement over the performance manner.

Conclusion

In this blog post, we talked about the major features and updates that are about to happen in Python3.12 and the new syntaxes that help us code in a cleaner way. Lots of new features are coming from the Typing module meaning the lining and formatting tools have to work harder in the incoming months to release a compatible version with the new Python patch.