Python, though released over 30 years ago, is a very popular programming language that is loved by both professional developers and those learning how to code.
Both the PYPL and the TIOBE indexes rank Python as the most popular language in the world as of October 2023.
The 2022 Stack Overflow developer survey also reports that Python was the second most wanted programming language. Therefore, any developer choosing to learn and use Python stands to benefit tremendously as far as job opportunities and career growth are concerned.
However, after settling on Python as your programming language of choice, another big question arises. Should you use Python 2 or Python 3 in your projects? This is one of the questions that troubled me as a Python developer, and in case you have also been wondering what to use, then this article will help you make that decision.
What is Python 2?
Python 2 and Python 3 are the two major versions or releases of the Python programming language. Python 2.0 was first released in 2000, and it introduced features and improvements that were aimed to make learning and using Python for development easier.
Python 2 also came with the Python Enhancement Proposal(PEP), which is a design document that provides information on new Python features and acts as the primary mechanism for suggesting new features to the language.
Python 2 was very popular and extensively used by developers and companies alike. However, on January 1st, 2020, Python 2 was sunsetted and stopped being supported. After that date, no further improvements were to be made to Python 2. The final release of Python 2 was Python 2.7, which was released in 2010.
With Python 2 no longer being supported, the focus shifted to the next major release of the Python language.
What is Python 3?
Python 3, which was first released on December 3rd, 2008. Python 3 was introduced to address design flaws and security issues that were present in Python 2. Python 3 introduced sweeping changes and new features to the language to remove redundancy when coding in Python and also to make Python code more readable.
Redundancy in coding refers to the existence of repetitive or duplicate code. Python 3 came with changes to the syntax of the Python language, among other things. The changes that came in Python 3 were so drastic that Python 3 code is incompatible with Python 2.
You might expect that all companies and developers currently use Python 3, but that is not the case. In the 2022 Python Developers Survey done by JetBrains, it was found that as of 2022, seven percent of Python developers use Python 2. The survey established that Python 2 was mainly being used in data analysis, computer graphics, and DevOps.
Since developers are usually working with code, let us look at some code samples that highlight the differences in syntax between Python 2 and Python 3 before diving into the main differences between the two versions.
Syntax Differences Between Python 2 and Python 3
One of the differences between Python 2 and Python 3 is how they print to the standard output. In Python 2, print is a statement, while in Python 3, print is a function. The code samples below show the differences in printing to standard output using Python 2 and Python 3.
print "Hello, World!"
Another difference between Python 2 and Python 3 in their code syntax is in the use of Type annotations. Type annotations allow us to specify the type of a variable, parameter, or even the return type. This can help minimize errors in our code and also clearly communicate the expected types in our code.
Type annotations are supported in Python 3. However, they are not supported in Python 2. See the code sample below, which shows type annotations being used in Python 3 and also the same code without type annotations in Python 2.
In the code sample below, notice int has been used to annotate that the age variable should be an integer. str is used to annotate the argument to the greet function and also its return type.
# Type annotation - using int to indicate age is an integer
age: int = 30
# Type annotation - str using to indicate the argument type
# and the return type of the greet() function
def greet(name: str) -> str:
return "Hello, " + name
result = greet("Alice")
print("Your age is " + str(age))
Your age is 30
Notice the code has no type annotations. Also, notice how printing is done:
age = 30;
return "Hello, " + name
result = greet("Alice")
print "Your age is " + str(age)
Your age is 30
Another difference you’ll notice when writing Python 2 and Python 3 code is the result of integer division. To see this, let us do integer division in Python 2 and Python 3:
From the code above, notice that when we do integer division in Python 2, we get the whole number, and the decimal part is truncated. However, in Python 3, the result of an integer division is a float value, which contains the decimal part of the computations.
From the differences in syntax, would you rather use Python 2 or Python 3? Do you think Python 3 is an improvement to Python 2? In case you are still not sure, let us look at more differences between Python 2 and Python 3 to help you in picking between Python 2 and Python 3.
Differences Between Python 2 and Python 3
The differences between Python 2 and Python 3 are shown below:
October 16th, 2000
December 3rd, 2008
Official Support ended on January 1st, 2020
Is currently the official supported version of Python
print is a statement. For example, print “Hello, world!”
Better performance and is faster than Python 2 in almost all benchmark tests
It has better performance and is faster than Python 2 in almost all benchmark tests
Simpler syntax that is easy to read and understand with little to no redundancy
Strings are stored as ASCII by default
Strings are stored as UNICODEby default
Dividing two integers yields an integer truncating the decimal part. For instance, 5/2 == 2
Dividing two integers yields a float value. For instance, 5/2 == 2.5
print is a “unction. For example, print(“Hello, world!”)
print is a sisn’tent. For example, print “Hello, world!”
Has no built-in support for type annotations
Has built-in support for type annotations, allowing you to specify the type of variables, return values, and function parameters.
iteration is done using the xrange() function
iteration is done using the range() function which is more efficient than xrange()
Has built-in support for type annotations allowing you to specify the type of variables, return values, and function parameters.
Many Python 3 libraries are designed to only work with Python 3 with no backward compatibility with Python 2. Offers better stand libraries
No longer widely used since it is not supported
Is widely used by developers and companies. It is currently the most popular version of Python.
How To Migrate From Python 2 to Python 3
Since Python 3 has better security and performance, a clearer and more readable syntax with very little redundancy, and is also the officially supported version of Python, it makes sense to migrate from Python 2 to Python 3.
However, that is easier said than done. Python 3 is not backward compatible with Python 2. Migrating a project from Python 2 to Python 3 can be very challenging and will require a lot of time and effort, depending on the size of the project.
For instance, Dropbox with Guido van Rossum, the creator of the Python language working for them, took about three years to successfully migrate from Python 2 to Python 3.
To migrate from Python 2 to Python 3, first ensure you clearly understand the differences between the two versions and evaluate the cost of the migration and what your application stands to gain. Once that is done, ensure you have a version control system in place such that you can roll back your application to an earlier working version in case of errors that break the application.
Look at the dependencies that your application relies on and find out whether they are compatible with Python 3 since many libraries have moved to Python 3, select dependencies that are compatible with Python 3.
The next step should be working on your code base to change the existing code from Python 2 to Python 3. This is the hardest part. However, as much as you can do it manually, Python provides a tool called 2to3 which reads Python 2 code and transforms it into Python 3. Use this tool to speed up the migration.
As you migrate, it is important to test and fix any issues that arise in your code. From the reports generated by 2to3, evaluate all the issues in your application and fix them. During this process, using automated testing tools is beneficial to speed up the testing process and get high test coverage.
Throughout the migration process, make sure to document the process. Additionally, take an iterative approach in the migration. If you have a large codebase, rather than working to migrate the entire codebase to Python 3, make the process gradual, migrating different modules in the application in different iterations.
Factors to Consider While Choosing Between Python 2 and Python 3 for Your Project
When working with Python, there are several considerations that you should make when it comes to deciding whether to work with Python 2 or Python 3.
Some of these considerations include:
Level of experience – If you are a developer learning how to code with Python, use Python 3, as this is what you’re likely to use when working. You’ll also have access to more learning resources. If you are an experienced Python developer who clearly understands the different versions and the deliverables expected in a project, you can use either Python 2 or Python 3. Pick a version that best suits your project and is understood by most members of your team.
Legacy Code – As a developer, you might find yourself working on large codebases that were extensively written in Python 2. In certain scenarios, the cost of migrating the codebase to Python 3 might outweigh the benefits. As a result, it might make sense to work with Python 2.
Library Compatibility – Some old Python 2 libraries have not yet been fully updated to work with Python 3. If you’re working on projects that heavily rely on such libraries, you might be better off using Python 2.
Performance – if you are building an application that requires very high performance, you should use Python 3. Python 3 is more performant than Python 2 and also offers features that lead to more performant applications. Therefore, if high performance is required in your application, use Python 3, just like Instagram and Dropbox do.
Long-term viability – Python 2 reached its end of life in 2020 and is no longer officially supported. Therefore, if you’re starting a new project or maintaining an existing one, it makes the most sense to use Python 3 as a safer and future-proof version. This is because it will continue receiving updates and security patches.
Ideally, in all your projects, you want to work with Python 3 because it is the officially supported version. Additionally, it offers tons of features to enhance the development and performance of applications.
Only use Python 2 in very special cases, such as when the project you are working on is a legacy project that has extensive Python 2 code or projects that have specific requirements that make Python 2 ideal for them.
As a Python developer, almost all of my Python projects have been done using Python 3. The improved design, better performance, better security, and cleaner syntax with less redundancy make Python 3 a clear winner between the two versions.
Considering that Python 3 is also the officially supported version and the future of the Python language, you should be using Python 3 in your projects and also when you’re learning how to code.
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