Difference Between Python 2 and 3

One of the programming languages that has taken the world of technology to a whole new level is Python. The general-purpose programming language has found its applications in a plethora of fields like Data Science, Natural Language Processing, Artificial Intelligence, Software Engineering, etc.

The two major versions of Python that were introduced to the world were Python 2 and Python 3. Although they are both just different versions of the same programming language, surprisingly, there are striking differences between the two and it would be extremely exciting to take a look at the differences between Python 2 and Python 3. In the past, there has been a lot of debate around the fact of which one of the two versions is better to use.

What is Python 2?

Python 2.0 was introduced to the tech world in the year 2000. Created by the BeOpen Python Labs team, the purpose of the introduction of Python 2 was to make programming simple and easy to learn for the common masses.

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Python 2 was successful in implementing the technical details of the Python Enhancement Proposal (PEP). However, after the introduction of Python 3, Python 2 could not find a lot of its usage in the tech world and the year 2020 marked the end of Python 2’s legacy with Python 2.7 being its latest version. Given below is a timeline of the release of the various versions of the Python 2.X series:

• Python 2.0 – October 16, 2000
• Python 2.1 – April 17, 2001
• Python 2.2 – December 21, 2001
• Python 2.3 – July 29, 2003
• Python 2.4 – November 30, 2004
• Python 2.5 – September 19, 2006
• Python 2.6 – October 1, 2008
• Python 2.7-July 3, 2010

What is Python 3?

Released in the year 2008, Python 3 was not just another version of Python 2 after debugging. The introduction of Python was mostly surrounded by the motive that redundancy – writing repetitive code or writing the same piece of code again and again – should be removed from coding. Python 3 is backwards incompatible and aims at eliminating the problems which new programmers face while learning a programming language.

Given below is a timeline of the release of the various versions of the Python 3.X series:

• Python 3.0 – December 3, 2008
• Python 3.1 – June 27, 2009
• Python 3.2 – February 20, 2011
• Python 3.3 – September 29, 2012
• Python 3.4-March 16, 2014
• Python 3.5 – September 13, 2015
• Python 3.6- October 2016
• Python 3.7- June 2018.

Why Are There Different Versions of Python?

There were a variety of reasons as to why there were different versions of Python available. Firstly, a lot of industry code had been already written in Python 2, and therefore, completely migrating from Python 2 to Python 3 would have turned out to be a very time-consuming and difficult job.

Moreover, in order to work with configuration management tools like Puppet or Ansible, knowledge of both Python 2 and Python 3 was required. However, over the course of time, Python 3 has been developed in a way to is suitable for a broad variety of fields like web development, data science, analytics scripting, etc. Python 3 has a lot of rich libraries and can easily be integrated with other languages. Therefore, the need for both versions of Python can be easily understood. In the end, efforts were made to make Python 3 support a lot of major functionalities which Python 2 offered, and in 2020, Python 2 saw its demise.

Difference Between Python 2 and 3

Now that we have a solid understanding of the history of both the major versions of Python, let us take a look at the major difference between these two, that is, let us dive deep and understand which version wins in the competition: Python 2 vs. Python 3.

Python 2 vs. Python 3 Example Code

Now that we have a good understanding of the differences between Python 2 and Python 3, let us take a look at a sample code in both these versions to print a statement out:

Python 2

def main(): print "Hi! This is Python 2" if __name__== "__main__": main()

Python 3

def main(): print ("Hi! This is Python 3") if __name__== "__main__": main()

Python 2 or 3: Which Python Version is Best?

One of the most natural questions which must come to everyone’s mind after having read this article till this point is Which Python Version is Better? Python 2 or Python 3? Well, if you have been paying attention till now, the answer to this question seems pretty clear. It is definitely Python 3 that is the victorious version.

First of all, Python 2 is no longer in use since 2020 as Python 3 felt like the safest choice, especially for budding programmers who were unsure as to what programming specialization they wanted to pursue. Python 3 is definitely more readable, easier to grasp, and popular than Python 2. Python 2 has definitely run out of steam and one should learn Python 2 if and only if some legacy code has been written in Python 2 or if a company needs the developer to migrate the Python 2 code into Python 3.

The picture given below shows the clear trends in the fact that Python 2 has lost the interest of programmers over time and how Python 3 has won the race between Python 2 and Python 3. Hence, we can safely say that as of 2023, the question: “Which Python Version is Best?” has a clear winner – Python 3.

Conclusion

So, in conclusion, we would like to say that Python is one of the most in-demand languages in today’s times as it is being heavily used in a large number of fields. Promising fields of the future like Artificial Intelligence, Data Science, etc. have seemed to heavily rely on Python and its libraries and frameworks like Numpy, Pandas, etc.

Hence, if any budding programmer today wants to start his or her coding career, learning Python might be a great choice for him or her. Also, through this article, we wish to clear out the differences between the two major versions of Python – Python 2 and Python 3 and establish why Python 3 is the version for the future.

Frequently Asked Questions(FAQs)

Q.1: What is the difference between print in Python 2 and 3?

Ans: In Python 2, print is treated as a statement whereas, in Python 3, print is treated as a function. Hence, we do not need to wrap the text to be printed in parentheses, although we can if we want. However, this can lead to confusion as most of the other actions in Python use functions that require the arguments to be placed inside parentheses.

Unexpected outcomes can also be seen if we put parentheses around a comma-separated list of items that need to be printed by us. In Python 3, since the print is treated as a function, we have to pass the items which we need to print to the function in parentheses in the standard way, or we will get a syntax error.

Q.2 Which is faster: Python 2 or 3?

Ans: Python 3 is usually faster than Python 2.

Q.3: Can I install both Python 2 and 3?

Ans: Yes, we can install both Python 2 and Python 3. We can easily maintain separate environments for Python 2 programs and Python 3 programs on the same computer and not worry about the programs interacting with each other.

Q.4: Is Python 3 the same as Python?

Ans: Python3 is usually installed alongside Python 2 because a few applications might still be dependent on Python 2. Therefore, the term Python usually refers to version 2.x.x and Python 3 usually refers to version 3.

Q.5: Is Python 3 a CPython?

Ans: Yes, CPython is the original Python implementation.

​​Q.6: Can I use Python 2 and 3 together?

Ans: Yes, we can install both Python 2 and Python 3. We can easily maintain separate environments for Python 2 programs and Python 3 programs on the same computer and not worry about the programs interacting with each other.

Additional Resources

• Learn Python
• Python MCQ
• Python Interview Questions
• How to become a Python Developer
• Python Projects
• Python Frameworks
• Python Developer Salary
• Features of Python
• Python IDE
• Python Books
• Python Developer Resume
• Python Developer Skills
• Python Libraries
• Python vs Java

Should I Learn Python 2 or 3? (and Why It Matters)

If you’re wondering whether you should learn Python 2 or Python 3, you’re not alone.

This is one of the questions we hear most often at Dataquest, where we teach Python as part of our Data Science curriculum.

Spoiler: at Dataquest, we only teach Python 3. If you’re ready to start learning now, enroll in the Introduction to Python course at no charge!

If you’re still on the fence or just want more information, keep reading. This post gives some context behind the question, explains our position, and tells you which version you should learn.

If you want the short answer, here it is: You should learn Python 3 because it’s the version most relevant to today’s data science projects. Plus, it’s easy to learn, and there are few compatibility issues to worry about.

Need a more thorough explanation? Let’s start by taking a brief look at the history behind the Python 2 versus 3 debate.

2008: The Birth of Python 3.0

No, that’s not a typo. Python 3 was released way back in 2008.

If you’re new to the Python 2-3 controversy, take note that this squabble has been brewing for nearly a decade and a half! That alone should tell you what a huge deal it is.

The Backwards Incompatible Release of 2008

Python released its version 3.0 on December 3, 2008. What was special (read: infuriating) about this release is that it was a backwards incompatible release.

As a result of this backwards incompatibility, migrating projects over from Python 2.x to 3.x would require large changes. This included not only individual projects and applications, but also all the libraries that form part of the Python ecosystem.

Python 3 Backlash

At the time, the change was seen as extremely controversial. Thus, many projects resisted the pain of moving over, especially in the scientific Python community. For example, it took two whole years for the main numeric library NumPy to release its first 3.x release!

Other projects started to release 3.x compatible versions in the years that followed. By 2012, a lot of libraries had support for 3.x, but most were still being written in 2.x. Over time, tools were released that made porting code across easier, but there was still a great resistance to move.

In the few years that followed, several tools were released to help the transition of older codebases from Python 2 to Python 3.

Originally, Python had scheduled the “end of life” date for Python 2.x for 2015. In 2014, though, they announced they would extend the termination date to 2020. This was done, in part, to relieve worries for those users who could not yet migrate to Python 3.

Still, it became clear Python 2’s days were limited. In 2017, the popular web-framework Django announced that their new 2.0 version would not support Python 2.x.

In addition, numerous packages began announcing the end of support for 2.x. Even scientific libraries made a commitment to stop supporting 2.x by 2020 or sooner.

Fast-Forward to Today: Why Is This Still a Question?

Today, there are very few libraries that do not support Python 3.

But if Python 2.x isn’t supported anymore, then why is there still confusion surrounding the Python 2 versus 3 issue?

For one, there are a lot of older, free resources online to learn Python that are based in Python 2. This includes most MOOC courses from platforms like Coursera, Udemy, and edX.

Since data science students are always looking to save a buck, these free resources are tempting.

Plus, Zed Shaw’s extremely popular Learn Python the Hard Way was written in Python 2.x. And he didn’t write a book about Python 3 until 2017 — almost a full decade after its release!

Until recently, I thought this was just because Zed had been too lazy to update his course for all of those years. But then I found his controversial article: The Case against Python 3.

Despite Eevee’s excellent rebuttal For Python 3, Zed’s diatribe took its toll. Of course, the number of people who agree with Zed are in the extreme minority today. But the entire controversy slowed the transition from Python 2 to 3. And it also muddied the waters for a lot of newcomers to the field.

So Which Python Should I Learn?

With all the debate over Python 2 versus 3, you’d think the decision to learn one or the other would be a difficult one. In reality, though, it’s pretty straightforward.

Python 3 Is the Clear Winner

Python 3.x is the future, and with Python 2.x support dwindling, you should spend your time learning the version that will endure.

And if you’re worried about compatibility issues, don’t be. I’ve used Python 3.x exclusively and rarely run into compatibility issues.

Very occasionally (maybe once every 3-4 months), I’ll find I’m trying to run something that requires Python 2 support. In these rare cases, Python’s virtualenv allows me to instantly create a 2.x environment on my machine to run that piece of legacy software.

Don’t Waste Your Time with Python 2

Let’s be clear: Python 2 is outdated. There will be no future security or bug fixes for Python 2.x, and your time is better spent learning 3.x.

In the unlikely event that you end up working with a legacy Python 2 code base, tools like Python-Future will make it easy for you to use having only learned Python 3.

Dataquest is the best online platform for learning to be a Data Scientist using Python (3.x, of course!).We have graduates working at SpaceX, Amazon, and more. If that interests you, you can sign up and complete our first course for free at Dataquest.io.

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