6 Tips to write Better Python Code
Writing better Python code involves following best practices and guidelines that have been established by the Python community. Adhering to these standards can make your code more readable, maintainable, and efficient.
This article will show some tips to help you write better Python code:
Follow the PEP 8 style guide
PEP 8 is the official style guide for Python code. It provides a set of guidelines for formatting your code, such as how to indent, how to use whitespace, and how to name variables. Following these guidelines will make your code more consistent and easier to read. Below mentioned some for you.
1. Adhere to PEP 8 Naming Conventions
Python PEP 8 (Python Enhancement Proposal 8) offers some suggestions on how Python code should be formatted or styled. You should try to follow these styling conventions if you want to write Pythonic code (In short, “pythonic” describes a coding style that leverages Python’s unique features to write code that is readable and beautiful).
Let’s look at some of the strategies that you should follow when writing code:
- Variable names — variable names should only contain lowercase letters, with any two words in the name being separated by an underscore. For example, if you want to name a variable “ employee names,” here are some ways to do it
- Function names — Function names should only contain lowercase letters separated by an underscore if there is more than one word. Do not include any uppercase letters
- Class names — As stated in PEP 8, all class names should start with an uppercase letter. If you have two words in the name, use the Cap-Words convention. This means that you should start each word with an uppercase letter. They should not be spaces between the words
- Maximum line length — Your code should easily be readable, so unnecessarily long lines of code should be avoided. PEP 8 suggests that your code lines should not exceed 79 characters.
For further on PEP 8 information, go with this link-PEP 8 style guide.
2. Use descriptive and meaningful variable names
One of the keys to writing readable code is to use descriptive and meaningful variable names. This will make it easier for others to understand your code, and for you to remember what each variable represents when you come back to your code later.
In Python, we specify variables for our objects.
Easily put, a variable is a pointer to an object. Calling the variable provides us access to an object. In Python, we can create different types of variable names if they will not generate an error. Because a variable name does not cause an error does not imply that using it is the best practice.
Since variables serve as references to objects, it is best practice for their names to be descriptive of the objects they hold. For example, if you have a list of employee names, it may be convenient and easy to give the variable the name “x,” but that is not good practice. See the code below:
Although this code executes without a tackle, it is bad programming practice because “x” does not specify the type of object that the variable is holding. It will be tough for you to figure out what object variable “x” is pointing to if your script has a lot of code.
This method of naming variables makes it difficult to debug programs. The name of the variable should attempt to identify the type of object it is pointing to. Given that it identifies the information in the list, the name “ employee_names” as a variable name is largely self-explanatory. It is more descriptive than the name “x.” Look at the code below:
3. Use inline comments sparingly
While comments can be useful for explaining complex or confusing code, it’s important not to overuse them. Too many comments can make your code cluttered and harder to read. Instead, try to make your code self-explanatory by using clear and concise variable names and writing clean and well-structured code.
The following example illustrates an inline comment:
4. Use List Comprehension
Let’s say you have a list of numbers, and you want to return all the divisible numbers by 2; you can use a for-loop statement or list comprehension.
Let’s explain this with code. We are going to start with a for-loop statement.
Now, let’s apply this solution with a list comprehension.
Have you noticed above that list comprehension only needs one line of code to achieve the same task?
With list comprehension, we did not have to generate an empty list or use the list method, append(). List comprehension is concise, making our code more readable. In most cases, it is also more efficient than the conventional for-loop statement
5. Use Join() Method to join strings
You have two choices if you have a list of strings you want to join — You can use the concatenation “+” operator or the string method “join.”
In the below code, we use the “+” operator to bring together a list of strings
As we iterate over the list, the “+” operator is applied in the code above to concatenate a list of strings to a new_string variable. To merge spaces between the strings, we concatenate an empty string (“”) at the end.
You can see that the code works just well. This approach, however, is not memory efficient.
This is because of the kind of strings. Since strings are immutable, any attempt to combine their results in the creation of a new object. Every time we call the “+” operator, memory must be allocated to the created object. This makes the method uninteresting and slows for larger strings.
Yet, this is not the case with the join() method. This is because the join() method only assigns memory to the final object. This makes this method quicker when joining bigger strings. As a result, the code below is generally quicker and more concise.
6. Use descriptive function and method names
Similar to using descriptive variable names, using descriptive function and method names can make your code easier to understand and maintain. This is especially important if you have long or complex functions that might be difficult to understand without some context
By following these tips, you can write better Python code that is easier to read, maintain, and understand. Remember to always strive for simplicity and clarity in your code, and to follow established best practices and guidelines.
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