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Python 3.9 is here!


On October 5th Python 3.9 was officially out of beta and realized to everyone. Here I’m gonna describe some important and cool changes that come with Python 3.9.

Simpler Updating of Dictionaries

Merge (|) and update (|=) operators have been added to the built-in dict class. These complement the existing dict.update and {**d1, **d2} methods of merging dictionaries.

One advantage of using | is that it works on different dictionary-like types and keeps the type through the merge:

You can use a defaultdict when you want to effectively handle missing keys. Note that | preserves the defaultdict, while {**europe, **africa} does not.

Type Hinting Generics in Standard Collections

In type annotations, you can now use built-in collection types such as list and dict as generic types instead of importing the corresponding capitalized types (e.g. List or Dict) from typing. Some other types in the standard library are also now generic, for example queue.Queue.



The zoneinfo module brings support for the IANA time zone database to the standard library. It adds zoneinfo.ZoneInfo, a concrete datetime.tzinfo implementation backed by the system’s time zone data.


As a fall-back source of data for platforms that don’t ship the IANA database, the tzdata module was released as a first-party package – distributed via PyPI and maintained by the CPython core team.

A More Powerful Python Parser

One of the coolest features of Python 3.9 is one that you won’t notice in your daily coding life. A fundamental component of the Python interpreter is the parser. In the latest version, the parser has been reimplemented.

Since its inception, Python has used a basic LL(1) parser to parse source code into parse trees. You can think of an LL(1) parser as one that reads one character at a time and figures out how to interpret the source code without backtracking.

One advantage of using a simple parser is that it’s fairly straightforward to implement and reason about. A disadvantage is that there are hard cases that you need to circumvent with special hacks.

In a series of blog posts, Guido van Rossum—Python’s creator—investigated PEG (parsing expression grammar) parsers. PEG parsers are more powerful than LL(1) parsers and avoid the need for special hacks. As a result of Guido’s research, a PEG parser was implemented in Python 3.9. See PEP 617 for more details.

The goal is for the new PEG parser to produce the same abstract syntax tree (AST) as the old LL(1) parser. The latest version actually ships with both parsers. While the PEG parser is the default, you can run your program using the old parser by using the -X oldparser command-line flag:

$ python -X oldparser

Alternatively, you can set the PYTHONOLDPARSER environment variable.

The old parser will be removed in Python 3.10. This will allow for new features without the limitations of an LL(1) grammar. One such feature currently being considered for inclusion in Python 3.10 is structural pattern matching, as described in PEP 622.

Having both parsers available is great for validating the new PEG parser. You can run any code on both parsers and compare it at the AST level. During testing, the whole standard library as well as many popular third-party packages were compiled and compared.

You can also compare the performance of the two parsers. In general, the PEG parser and the LL(1) perform similarly. Over the whole standard library, the PEG parser is slightly faster, but it also uses slightly more memory. In practice, you shouldn’t notice any change in performance, good or bad, when using the new parser.

Should you upgrade?

Well, in my opinion always where it is possible. I am always building my projects on the newest versions of software. It keeps me updated with news and it’s supported the longest.


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