Hello World! The Pythonic Way

Python has exploded in popularity in recent years to become one of the most beloved and widely used programming languages today. It ranked #2 on the TIOBE Index as of June 2021, up from #3 a year ago, and was the #1 most wanted technology in Stack Overflow‘s 2021 Developer Survey for the fifth year running.[^1]

Much of Python‘s appeal lies in its elegant, expressive syntax and expansive ecosystem of powerful frameworks and libraries. But just as important is the language‘s strong culture of best practices and idioms that Pythonistas simply call "Pythonic" code.

The Zen of Python

At the core of Pythonic philosophy is a set of 19 guiding principles laid out in PEP 20, colloquially known as the "Zen of Python".[^2] Let‘s look at a few of the most important:

• Explicit is better than implicit. Pythonic code is clear and unambiguous. It doesn‘t rely on "magic" or hidden behavior.
• Flat is better than nested. Pythonic code avoids excessive nesting and indentation. Flat data structures and control flow are preferred.
• Readability counts. Pythonic code is meant to be read by humans, not just compilers. Clarity and simplicity are paramount.
• There should be one– and preferably only one –obvious way to do it. Pythonic code leverages common idioms and patterns. It doesn‘t reinvent the wheel.
• Now is better than never. Although never is often better than right now. Pythonic code is practical. It balances the need for expedience with the dangers of premature optimization.

Let‘s see how these principles play out in practice with the classic "Hello World!" example.

A Tale of Two Hello Worlds

Here‘s a very un-Pythonic way to write "Hello World!":

if __name__ == "__main__":
    i = 0
    while i < 1:
        foo = "Hello"
        bar = "World"
        i += 1
        if i == 1:
            print("%s %s" % (foo, bar))
            break

Yuck! The code is needlessly convoluted, with pointless variables and control flow. Contrast that with this:

print("Hello World!")

Ah, much better. In one line we accomplish the same thing as the first example in a clear, concise way. No wasted motion, no unnecessary indirection. That‘s Pythonic code.

Batteries Included

Another key aspect of Pythonic programming is leveraging Python‘s "batteries included" standard library and rich third-party ecosystem. Want to parse some JSON? Just use the built-in json module:

import json

data = json.loads(‘{"name": "Alice", "age": 30}‘)
print(f"Hello {data[‘name‘]}!")

Need to make a quick HTTP request? The popular requests library has you covered:

import requests

response = requests.get("https://api.github.com/zen")
print(response.text)

Python‘s vast collection of high-quality, well-maintained packages mean Pythonic code rarely starts from scratch. It builds on the solid foundations laid by the Python community.

NumPy, Pandas, SciPy and Matplotlib for data science and scientific computing. Django, Flask, and FastAPI for web development. Pytest, unittest, and Hypothesis for testing. The list goes on. A Pythonic programmer knows their way around the ecosystem and reaches for the right tool for the job.

Pythonic Idioms

Idiomatic Python also makes frequent use of certain language features and patterns. List comprehensions are a great example:

# Non-Pythonic
squares = []
for x in range(10):
    squares.append(x**2)

# Pythonic
squares = [x**2 for x in range(10)]

The Pythonic version is more concise and expressive. It says what it means directly, without extraneous looping logic.

Context managers are another powerful Pythonic feature:

# Non-Pythonic 
file = open("hello.txt", "w")
file.write("Hello World!")
file.close()

# Pythonic
with open("hello.txt", "w") as file:
    file.write("Hello World!")

The with statement ensures the file is properly closed after use, even if an exception is raised. It‘s a cleaner, safer way to manage resources.

Generators are yet another Pythonic idiom that allow for memory-efficient iteration:

# Non-Pythonic 
def squares(n):
    result = []
    for i in range(n):
        result.append(i**2)
    return result

# Pythonic
def squares(n):
    for i in range(n):
        yield i**2

The generator version returns an iterator, avoiding the need to create a full list in memory. For large sequences this can lead to substantial performance gains.

Zen and the Art of Python Maintenance

So why bother writing Pythonic code? Yes, it‘s often more concise and aesthetically pleasing. But the real benefits are practical: Pythonic code is easier to read, understand, and maintain.

In a professional software development context, code is read much more often than it is written. A Pythonic codebase is accessible to a wide range of developers, not just the original author. It‘s self-documenting, with clear intention and a minimum of surprises.

Pythonic code is modular and testable by default. Functions are small and focused. State is managed carefully. Testing is a first-class concern. Debugging and tracing through a Pythonic system is a straightforward process.

Bringing new developers up to speed on a Pythonic project is also easier. There‘s a shared language and set of conventions to build upon. Developers already familiar with the idioms of Python will feel right at home, even if the specific domain is new to them.

Keeping It Pythonic

Of course, just writing code in Python doesn‘t automatically make it Pythonic. It takes practice and discipline to deeply learn and apply Pythonic principles. Luckily, there are a number of great tools to help keep your Python code squeaky clean and idiomatic:

• Pylint is a popular linter that checks your code against a wide range of best practices and potential errors. It‘s highly configurable and can be integrated into most IDEs.[^4]
• Black is an uncompromising code formatter that ensures a consistent, Pythonic style across your codebase. It‘s a great way to avoid bikeshedding on minor stylistic issues.[^5]
• Mypy is a static type checker that can catch a wide range of bugs and improve the maintainability of your code. Used judiciously, type annotations make your intention clear without sacrificing Python‘s dynamism.[^6]

Integrating these tools into your development workflow and CI/CD pipeline can help ensure new code meets a high Pythonic standard.

Pythonic Mastery

Ultimately, writing truly Pythonic code is a mindset as much as a technical skill. It‘s a way of approaching problems with a spirit of clarity, simplicity, and pragmatism.

The good news is that this mindset can be learned. Like any skill, Pythonic programming improves with practice and exposure. Read high-quality Python code. Contribute to open source projects. Pair with experienced Python developers. With time, Pythonic idioms that once felt foreign will become second nature.

Embrace Python‘s "one obvious way" ethos and strive to make your code as clean and readable as possible. Don‘t settle for code that just works. Aim for code that‘s elegant, even beautiful in its simplicity.

When you find yourself stuck on a gnarly problem, remember the Zen: "Simple is better than complex." Breathe. Step back. Refactor. Revel in the joy of clean, Pythonic code. Your teammates (and your future self) will thank you.

References

[^1]: Stack Overflow. (2021). Stack Overflow Developer Survey 2021. https://insights.stackoverflow.com/survey/2021
[^2]: Peters, T. (2004). PEP 20 — The Zen of Python. Python.org. https://www.python.org/dev/peps/pep-0020/
[^4]: Pylint. (n.d.). Pylint – code analysis for Python. https://pylint.pycqa.org/
[^5]: Black. (n.d.). Black: The uncompromising code formatter. https://black.readthedocs.io/
[^6]: Mypy. (n.d.). Mypy – Optional Static Typing for Python. https://mypy.readthedocs.io/