Introduction
Python is a widely used, high-level, general-purpose programming language that is known for its simplicity, readability, and versatility. Python can be used for a variety of applications, such as web development, data analysis, machine learning, automation, and more.
Python 3.9 is the latest version of Python, released on October 5, 2020. It introduces several new features and enhancements that make coding in Python more efficient, expressive, and fun. Some of these features include:
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Union operators for dictionaries: You can now merge or update dictionaries using the and = operators, instead of using methods like update() or dict().
Type hinting generics in standard collections: You can now use built-in collection types such as list, dict, set, and tuple as generic types for type hinting, instead of importing them from the typing module.
String methods to remove prefixes and suffixes: You can now use the removeprefix() and removesuffix() methods on strings to easily remove unwanted characters from the beginning or end of a string.
Flexible function and variable annotations: You can now use any expression as an annotation for functions or variables, instead of being limited to literals, names, or attribute references.
New parser based on PEG: Python 3.9 uses a new parser that is based on Parsing Expression Grammar (PEG), which is more flexible and consistent than the previous one based on LL(1) grammar.
Support for the IANA time zone database in the standard library: You can now use the zoneinfo module to access accurate and up-to-date information about time zones around the world.
New graphlib module: You can now use the graphlib module to perform operations on directed graphs, such as finding the topological order or detecting cycles.
In this article, you will learn how to download, install, and use Python 3.9 on your computer, as well as some of the benefits of upgrading to this version.
Downloading Python 3.9
The first step to using Python 3.9 is to download it from the official Python website: [ On this page, you will see a list of active Python releases for different operating systems. Choose the one that matches your system and click on the download link.
If you are using Windows, you will see two options: a 64-bit installer and a 32-bit installer. Unless you have a very old computer, you should choose the 64-bit installer, as it is faster and more secure than the 32-bit one. The installer will also check if your system supports Windows 7 or later versions, as Python 3.9 is incompatible with older versions of Windows.
If you are using Linux or macOS, you will see a source code tarball that you can download and compile yourself. Alternatively, you can use a package manager or a third-party tool to install Python 3.9 on your system. For example, on Ubuntu Linux, you can use the deadsnakes PPA to install Python 3.9 with apt[^8^ Installing Python 3.9
Once you have downloaded Python 3.9, you can proceed to install it on your computer. The installation process may vary depending on your operating system, but it is generally easy and straightforward.
Installing Python 3.9 on Windows
If you have downloaded the Windows installer, you can simply run it and follow the instructions on the screen. You will be asked to choose the installation directory, the features to install, and whether to add Python to your PATH environment variable. It is recommended that you check the option to add Python to your PATH, as it will make it easier to run Python from any command prompt or terminal window.
After the installation is complete, you can verify that Python 3.9 is working by opening a command prompt and typing python --version. You should see something like this:
C:\Users\user>python --version Python 3.9.0
You can also launch the Python interactive shell by typing python and start writing and executing Python code.
Installing Python 3.9 on Linux
If you have downloaded the source code tarball, you will need to extract it and compile it yourself. To do this, you will need some tools and libraries installed on your system, such as GCC, make, zlib, libffi, and openssl. You can check the README file in the source code for more details on the requirements and instructions.
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Alternatively, you can use a package manager or a third-party tool to install Python 3.9 on your Linux system. For example, on Ubuntu Linux, you can use the deadsnakes PPA to install Python 3.9 with apt. To do this, you need to run the following commands in a terminal window:
sudo add-apt-repository ppa:deadsnakes/ppa sudo apt update sudo apt install python3.9
After the installation is complete, you can verify that Python 3.9 is working by typing python3.9 --version. You should see something like this:
$ python3.9 --version Python 3.9.0
You can also launch the Python interactive shell by typing python3.9 and start writing and executing Python code.
Installing Python 3.9 on macOS
If you have downloaded the source code tarball, you will need to extract it and compile it yourself. To do this, you will need some tools and libraries installed on your system, such as Xcode, zlib, libffi, and openssl. You can check the README file in the source code for more details on the requirements and instructions.
Alternatively, you can use a package manager or a third-party tool to install Python 3.9 on your macOS system. For example, you can use Homebrew to install Python 3.9 with brew. To do this, you need to run the following commands in a terminal window:
brew update brew install python@3.9
After the installation is complete, you can verify that Python 3.9 is working by typing python3 --version. You should see something like this:
$ python3 --version Python 3.9.0
You can also launch the Python interactive shell by typing python3 and start writing and executing Python code.
Using Python 3.9
Now that you have installed Python 3.9 on your computer, you can start using it to write and run Python code. There are several ways to use Python 3.9, such as:
The interactive shell: This is a convenient way to test and experiment with Python code interactively. You can launch the interactive shell by typing python, python3, or python3.9, depending on your system and installation method. In the interactive shell, you can type any valid Python expression or statement and see its result immediately.
The script mode: This is a way to write and execute Python code in a file with a .py extension. You can create a script file using any text editor of your choice, such as Notepad or VS Code. In the script file , you can write any valid Python code and save the file. To run the script file, you can use the python, python3, or python3.9 command followed by the name of the file. For example, if you have a script file named hello.py that prints "Hello, world!", you can run it by typing python hello.py in a terminal window.
The integrated development environment (IDE): This is a way to write and execute Python code in a graphical user interface that provides various tools and features to help you code better and faster. There are many IDEs available for Python, such as PyCharm, VS Code, Spyder, Thonny, and more. You can choose the one that suits your needs and preferences. In an IDE, you can create, edit, run, debug, and test Python code in a convenient and interactive way.
Whichever way you choose to use Python 3.9, you will be able to access its new features and improvements by using the appropriate syntax and modules. For example, to use the new union operators for dictionaries, you can write something like this:
# Create two dictionaries dict1 = "a": 1, "b": 2 dict2 = "c": 3, "d": 4 # Merge them using the operator dict3 = dict1 dict2 print(dict3) # 'a': 1, 'b': 2, 'c': 3, 'd': 4 # Update dict1 using the = operator dict1 = dict2 print(dict1) # 'a': 1, 'b': 2, 'c': 3, 'd': 4
To use the new type hinting generics in standard collections, you can write something like this:
# Import the typing module from typing import List, Dict, Set, Tuple # Use built-in collection types as generic types def count_words(text: str) -> Dict[str, int]: words: List[str] = text.split() counts: Dict[str, int] = for word in words: counts[word] = counts.get(word, 0) + 1 return counts # Use type hints to check the function signature text: str = "This is a sample text with some repeated words" counts: Dict[str, int] = count_words(text) print(counts) # 'This': 1, 'is': 1, 'a': 1, 'sample': 1, 'text': 1, 'with': 1, 'some': 1, 'repeated': 1, 'words': 1
To use the new string methods to remove prefixes and suffixes, you can write something like this:
# Create a string string = "Hello_world.txt" # Remove the prefix "Hello_" using the removeprefix() method string = string.removeprefix("Hello_") print(string) # world.txt # Remove the suffix ".txt" using the removesuffix() method string = string.removesuffix(".txt") print(string) # world
To use any expression as an annotation for functions or variables, you can write something like this:
# Import the math module import math # Use any expression as an annotation def area_of_circle(radius: "positive number") -> math.pi * radius 2: return math.pi * radius 2 # Use type hints to check the function signature radius: "positive number" = 5 area: math.pi * radius 2 = area_of_circle(radius) print(area) # 78.53981633974483
To use the new parser based on PEG, you don't need to do anything special. The parser is an internal component of Python that is responsible for parsing your code and converting it into an abstract syntax tree (AST). The new parser is more flexible and consistent than the previous one based on LL(1) grammar. It allows for some new syntax features that were not possible before, such as assignment expressions in lambda functions or decorators with arguments.
To use the IANA time zone database in the standard library, you can use the zoneinfo module. This module provides access to accurate and up-to-date information about time zones around the world. You can use it to create datetime objects that are aware of their time zone and perform various operations on them. For example, you can write something like this:
# Import the zoneinfo module import zoneinfo # Create datetime objects with different time zones dt1 = datetime.datetime(2023, 6, 20, 9, 52, 8, tzinfo=zoneinfo.ZoneInfo("America/New_York")) dt2 = datetime.datetime(2023, 6, 20, 9, 52, 8, tzinfo=zoneinfo.ZoneInfo("Asia/Tokyo")) # Print the datetime objects print(dt1) # 2023-06-20 09:52:08-04:00 print(dt2) # 2023-06-20 09:52:08+09:00 # Compare the datetime objects print(dt1
To use the new graphlib module, you can use the graphlib module. This module provides a class called TopologicalSorter that can perform operations on directed graphs, such as finding the topological order or detecting cycles. A topological order is a linear ordering of the nodes of a graph such that for every edge from node A to node B, node A appears before node B in the order. A cycle is a path of edges that starts and ends at the same node. For example, you can write something like this:
# Import the graphlib module import graphlib # Create a directed graph as a dictionary of sets graph = "A": "B", "C", "B": "D", "E", "C": "F", "D": "G", "E": "G", "F": "G", "G": set(), # Create a TopologicalSorter object ts = graphlib.TopologicalSorter(graph) # Find the topological order of the graph order = list(ts.static_order()) print(order) # ['A', 'C', 'F', 'B', 'E', 'D', 'G'] # Check if the graph has a cycle cycle = ts.prepare() print(cycle) # None
Benefits of Python 3.9
Python 3.9 is a major release that brings many new features and improvements to the Python language and its standard library. By using Python 3.9, you can enjoy the following benefits:
Better performance and stability: Python 3.9 is faster and more reliable than previous versions of Python, thanks to various optimizations and bug fixes. For example, Python 3.9 uses vectorcall, a new calling protocol for C functions that reduces the overhead of calling functions and methods. Python 3.9 also uses a more efficient garbage collection algorithm that reduces memory usage and fragmentation.
More expressive and concise code: Python 3.9 introduces several new syntax features and enhancements that make coding in Python more efficient, expressive, and concise. For example, you can use the new union operators for dictionaries to merge or update dictionaries in one line of code. You can also use the new string methods to remove prefixes and suffixes from strings without slicing or indexing. You can also use any expression as an annotation for functions or variables, which gives you more flexibility and creativity in documenting your code.
More consistent and compatible code: Python 3.9 uses a new parser that is based on Parsing Expression Grammar (PEG), which is more flexible and consistent than the previous one based on LL(1) grammar. The new parser allows for some new syntax features that were not possible before, such as assignment expressions in lambda functions or decorators with arguments. The new parser also makes Python more compatible with other languages that use PEG parsers, such as JavaScript and Rust.
More accurate and up-to-date data: Python 3.9 supports the IANA time zone database in the standard library, which provides accurate and up-to-date information about time zones around the world. You can use the zoneinfo module to create datetime objects that are aware of their time zone and perform various operations on them. You can also use the calendar module to access information about calendars from different cultures and regions.
More powerful and useful tools: Python 3.9 introduces a new module called graphlib that provides a class for performing operations on directed graphs, such as finding the topological order or detecting cycles. This can be useful for solving problems that involve dependencies, scheduling, or ordering. Python 3 .9 also improves some existing modules, such as math, random, ast, csv, and more. For example, the math module now supports the GCD and LCM functions for multiple arguments, the random module now supports the randbytes() function for generating random bytes, the ast module now supports the unparse() function for converting an AST back to source code, and the csv module now supports dialects with different delimiters.
Conclusion
In this article, you have learned how to download, install, and use Python 3.9 on your computer, as well as some of the benefits of upgrading to this version. Python 3.9 is a major release that brings many new features and improvements to the Python language and its standard library. By using Python 3.9, you can write better, faster, and more consistent code that can handle various tasks and challenges.
If you have any questions or feedback about Python 3.9, you can visit the official Python website: [ or join the Python community on various platforms, such as Reddit, Stack Overflow, Discord, or Twitter. You can also check out the official documentation for Python 3.9: [ or read the What's New in Python 3.9 guide: [
I hope you enjoyed this article and found it useful. Happy coding with Python 3.9!
Frequently Asked Questions
Here are some of the common questions and answers about Python 3.9:
Is Python 3.9 backward compatible with previous versions of Python?
Yes, Python 3.9 is backward compatible with previous versions of Python 3.x, meaning that most code written in Python 3.x will run without errors or warnings in Python 3.9. However, Python 3.9 is not backward compatible with Python 2.x, meaning that code written in Python 2.x will not run in Python 3.9 without modifications or using a tool like 2to3.
How can I upgrade to Python 3.9 from an older version of Python?
You can upgrade to Python 3.9 from an older version of Python by following the same steps as downloading and installing Python 3.9, as described in this article. However, before you upgrade, you should make sure that your existing code and dependencies are compatible with Python 3.9, or that you have a backup of your code and data in case something goes wrong.
How can I use multiple versions of Python on my computer?
You can use multiple versions of Python on your computer by using a tool like pyenv, which allows you to easily switch between different versions of Python and manage virtual environments for each version. Pyenv is available for Windows, Linux, and macOS.
What are some of the best resources to learn more about Python 3.9?
Some of the best resources to learn more about Python 3.9 are:
The official documentation for Python 3.9: [
The What's New in Python 3.9 guide: [
The official tutorial for beginners: [
The official blog posts about Python 3.9: [
The Real Python website: [
The YouTube channel of Corey Schafer: [
How can I contribute to the development of Python?
You can contribute to the development of Python by reporting bugs, suggesting features, writing documentation, translating messages, reviewing code, testing releases, or writing patches for issues on the official GitHub repository: [ ). You can also join the Python community on various platforms, such as Reddit, Stack Overflow, Discord, or Twitter, and participate in discussions, ask questions, answer questions, or share your projects and ideas. You can also donate to the Python Software Foundation, which is a non-profit organization that supports the development and promotion of Python: [
This is the end of the article. I hope you found it helpful and informative. Thank you for reading and have a great day! 44f88ac181
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