Python Best Practices: Tips to Optimize Your Code

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Before anything else: let’s talk indentation.In Python, indentation is not just for aesthetics it’s mandatory! So if you see someone writing code with no spaces at the beginning of each line, run away as fast as you can because they clearly don’t know what they’re doing.
Now that we’ve established the importance of indentation, docstrings. Docstrings are like little notes to your future self (or other developers) explaining what a function or class does and how it works. They’re especially helpful when you come back to code months later and have no idea why you wrote that crazy loop in the first place.
Here’s an example of a docstring:

# This function calculates the sum of all numbers passed as arguments
def calculate_sum(numbers):
    total = 0 # Initialize a variable to store the sum
    for num in numbers: # Loop through each number in the list of numbers
        total += num # Add the current number to the total sum
    return total # Return the final sum

# Example usage:
numbers = [1, 2, 3, 4, 5]
print(calculate_sum(numbers)) # Output: 15

See how that works? It’s like a mini-manual for your code. And if you ever need to update or modify it, just make sure the docstring stays current with any changes you make.
Another best practice is using type hints. Type hints are basically little notes in your code telling Python what data types should be expected from a function or class. This can help catch errors before they happen and make your code more efficient overall. Here’s an example:

# This function takes in a list of integers and returns the sum of all the numbers in the list.
def calculate_sum(numbers: List[int]) -> int:
    """Calculates the sum of all numbers passed as arguments"""
    total = 0 # Initialize a variable to store the sum of the numbers
    for num in numbers: # Loop through each number in the list
        total += num # Add the current number to the total sum
    return total # Return the final sum

# The function is now properly annotated with type hints, indicating that the function expects a list of integers as input and will return an integer as output. 
# The function also has a docstring, which provides a brief description of what the function does. 
# The variable "total" is now properly initialized to 0 before the loop, and the loop adds each number in the list to the total sum. 
# Finally, the function returns the total sum as the final output.

See how that works? The `List[int]` part tells Python to expect a list of integers, and the `-> int` part tells it what type of data should be returned. This can help catch errors if someone accidentally passes in a string or float instead of an integer list.
Finally, automated documentation generators like Sphinx and Doxygen. These tools create documentation automatically using your source code, which can save developers considerable time and effort. They’re especially helpful when working on large or complex projects with multiple contributors.
Remember: indentation is mandatory, docstrings are essential, and type hints are a must-have for any professional developer.

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