Python 3 vs Python 2 [Key Differences]

In this tutorial, I have explained Python 3 vs Python 2 with key differences and migration considerations. Someone asked me this question in a Python webinar, and I decided to do an article on this. Let us get into the topic.

Python has evolved with two major versions still in use today: Python 2 and Python 3. These versions have key differences that affect how programmers write and run code.

Python 3 is the current standard and recommended version for new projects. It offers improved features and better performance. Python 2 reached its end of life in 2020, meaning it no longer receives updates or security patches.

While Python 3 is the future, some older systems and libraries still rely on Python 2. This can create challenges for developers working on projects or transitioning between versions.

Read How to Use Single and Double Quotes in Python

Evolution of Python

Python has grown from a simple scripting language to a powerful programming tool. Its journey spans decades and includes major changes that shaped how developers use it today.

Origins of Python and Foundational Differences

Guido van Rossum created Python in the late 1980s. He wanted to make a language that was easy to read and write. Python 1.0 came out in 1994. It had basic features like functions and modules.

Python 2.0 arrived in 2000. This version added new tools like list comprehensions and garbage collection. It made writing code faster and easier.

Python 3.0 was launched in 2008. It fixed old problems and broke backward compatibility. This big change upset some users but improved the language.

Read How to Check if a Variable Exists in Python

Syntactical Differences

Python 3 brought significant changes to the language’s syntax. These updates aimed to make code more readable and consistent. Let’s look at some key differences between Python 2 and 3 syntax.

Print Statement vs. Print Function

Python 2 used a print statement. It didn’t need parentheses:

print "Hello, World!"

Python 3 changed this to a print function. It requires parentheses:

print("Hello, World!")

This change allows for more flexible printing options. Python 3’s print function can take multiple arguments:

print("Hello", "World", sep=", ")

This prints: “Hello, World”

Read Python Hello World Program

Different Syntax for Integer Division

Python 2 used the ‘/’ operator for integer division. This could lead to unexpected results:

5 / 2  # Result: 2

Python 3 changed this behavior. The ‘/’ operator now always returns a float:

5 / 2  # Result: 2.5

For integer division in Python 3, use the ‘//’ operator:

5 // 2  # Result: 2

Read Convert Int to Bytes in Python

Exception Handling Variations

Python 3 made changes to exception handling syntax. In Python 2, the syntax was:

try:
    # Some code
except ValueError, e:
    print e

Python 3 uses the ‘as’ keyword for exception handling:

try:
    # Some code
except ValueError as e:
    print(e)

This new syntax is clearer and more consistent with other parts of the language.

Python 3 also requires parentheses for the ‘raise’ statement with exception arguments:

raise ValueError("This is an error message")

These changes make exception handling more explicit and easier to read.

Read end in Python

Data Types and Structures

Python 3 brought major changes to data types and structures. These updates improved Unicode support, enhanced list comprehensions, and added new iteration tools.

Unicode Support and ASCII Changes

Python 3 uses Unicode for all strings by default. This makes working with non-English text much easier. In Python 2, you had to add a “u” prefix for Unicode strings.

Python 3 also introduced a new bytes type for handling binary data. This replaced the old str type in Python 2, which could hold both text and binary data.

The print function in Python 3 now outputs Unicode text directly. This is a big help when working with international character sets.

List Comprehensions and Iterations Enhancements

Python 3 improved list comprehensions. It added support for multiple if conditions. This makes complex filtering easier in a single line of code.

The new version also keeps variables created in list comprehensions locally. In Python 2, these variables leaked into the surrounding scope.

Python 3 changed how the range() function works. It now returns an iterable object instead of a list. This saves memory when working with large ranges.

Ranges and Iteration Tools

Python 3 removed the xrange() function. The range() function now acts like xrange() did in Python 2. It creates an iterable object instead of a list.

The new version added the zip() function as a built-in. This function creates an iterator of tuples from multiple iterables.

Python 3 also introduced new iteration tools like itertools.combinations(). These help with tasks like generating all possible pairs from a Python list.

Read Difference Between = and == in Python

Performance and Efficiency

Python 3 offers key improvements in speed and resource usage compared to Python 2. These changes make Python 3 faster and more efficient for many tasks.

Improvements in Garbage Collection

Python 3’s garbage collector works better than Python 2’s. It cleans up unused memory more quickly and smoothly. This means Python 3 programs often run faster and use less memory.

Python 3 also added a generational garbage collector. This type focuses on newer objects first, which are more likely to be unused.

For big programs, these changes can make a big difference. They help Python 3 handle large amounts of data more easily than Python 2.

Read How to Get the Index of an Element in a List in Python?

Optimization of Python Libraries

Python 3 comes with many updated libraries. These work faster and use less memory than their Python 2 versions.

The standard library got a big upgrade. Many functions now use better algorithms. This makes common tasks quicker. For example, sorting lists is faster in Python 3.

Science and data libraries like NumPy and Pandas work better in Python 3. They can handle bigger datasets more quickly. These libraries also have new features that only work in Python 3.

Python 3’s math functions are more accurate. They give better results for complex calculations. This is great for scientific computing and machine learning.

Read How to Merge Lists Without Duplicates in Python?

Python 3 Coding Standards and Conventions

PEP 8 outlines key coding standards for Python 3. It covers naming conventions, indentation, and line length limits. Variable names use lowercase with underscores. Class names use CapWords. Constants are in ALL_CAPS.

Proper indentation is crucial. Use 4 spaces per level. Avoid mixing tabs and spaces. Keep lines under 79 characters for better readability.

Type hinting improves code clarity:

def greet(name: str) -> str:
    return f"Hello, {name}!"

Use docstrings to document functions and classes. This helps other developers understand your code:

def add(a: int, b: int) -> int:
    """Add two integers and return the sum."""
    return a + b

Read How to Create an Empty Tuple in Python?

Python 3 vs Python 2 – Summary

Python 2 and Python 3 are two major versions of the Python programming language. Here’s a table summarizing their key differences:

Python 3 includes updates in areas like data science, artificial intelligence, and natural language processing. These improvements have expanded Python’s use in various fields.

Read How to Access Tuple Elements in Python?

Frequently Asked Questions

Python 2 and Python 3 have some key differences that programmers should know about. These include changes in syntax, function behavior, and overall language design.

Read Python Dictionary Count

Conclusion

In this tutorial, I helped you to learn Python 3 vs Python 2 with key differences. I explained the evolution of Python along with the origins of Python and foundational differences, and some syntactical differences of print statement vs. print function and different syntax for integer division.

We discussed all the topics mentioned below, exception handling variations, data types and structures, Unicode support and ASCII changes, list comprehensions and iterations enhancements, ranges and iteration tools, Performance and Efficiency, Improvements in garbage collection, Optimization of Python libraries, Python 3 coding standards and conventions.

You may also like to read:

• Access Modifiers in Python
• Create an Empty Array in Python
• Interfaces in Python

Bijay Kumar

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

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