Writing a code that Machines can understand is important, but what is more important than that – “Writing a code that Humans can Understand”. When you write code for your college projects I know it doesn’t seem that necessary but when you enter the corporate world it becomes an integral part of your job to write code in such a manner that your team and colleagues can understand. In this article, we will be discussing 8 Best Code Practices that make your code clean and efficient.
If you simply follow the basic principles that are defined below, it makes your job really easy to make your code efficient.
Table of Contents
Best Code Practices
1. Descriptive Variable Names
This practice sounds so simple, yet so effective. Whenever naming your variable names, try to make it as much meaningful as possible. Instead of cryptic abbreviations, opt for descriptive names that convey the purpose of the variable. This not only enhances code readability but also makes debugging and collaboration more efficient.
For instance, you need to write a variable for the temperature of Delhi. So, instead of writing “temp” you can write “delhi_temperature”. It looks super readable and anyone who sees this variable name will quickly get the purpose of that particular variable name.
2. Add Comments and Documentation
Not only do names need to be descriptive but also proper comments and documentation need to be maintained. Writing explanatory comments and documentation is essential for code practices. Always make sure to document your code’s functionality, inputs, outputs, and any potential gotchas. Clear comments provide insights to other developers (including your future self) and foster better collaboration.
But, don’t overdo it. People generally think that they need to add comments on every line of code that write. It’s not like you only need to write comments where there is necessary and you think that it requires a bit more description than just a variable name.
Here is a properly commented piece of code that validates a password in Python:
Validate a user password.
This function checks whether a password meets the following criteria:
- Minimum length of 8 characters.
- Contains at least one uppercase letter, one lowercase letter, and one digit.
password (str): The password to be validated.
bool: True if the password is valid, False otherwise.
# Check password length
if len(password) < 8:
return False # Password is too short
# Check for uppercase, lowercase, and digit
has_upper = any(char.isupper() for char in password)
has_lower = any(char.islower() for char in password)
has_digit = any(char.isdigit() for char in password)
if not (has_upper and has_lower and has_digit):
return False # Missing required character types
3. Maintain spaces and empty lines
Spaces in code add much more area for developers’ eyes to ease out the scanning process. When there are no spaces in the written code, it becomes really difficult to read as it looks like cluttered pieces. When writing code, it’s common to have distinct logical blocks that perform different tasks. Aim for a balance that provides a clear visual structure without overwhelming the reader.
4. Modularization and DRY Principles
When you divide your code into modules, each module serves a distinct purpose. This approach simplifies understanding, debugging, and updating your codebase. You can focus on one module at a time, making it easier to spot errors and implement changes. Modularized code promotes reusability. Once you create a module to perform a certain function, you can easily use it in different parts of your application or even in future projects. This not only saves time but also ensures consistent and reliable functionality.
Copying and pasting code increases the risk of inconsistencies and errors. If you fix a bug or improve functionality in one place, you need to remember to do the same in all duplicate instances. DRY i.e., Don’t Repeat Yourself minimizes these chances, making your code more reliable. When a requirement changes or an improvement is needed, updating a single instance of code is faster and less error-prone than updating several instances
5. Avoid Deep Nesting
Deeply nested code structures, characterized by multiple layers of indentation within loops, conditional statements, or function calls, can make code difficult to read and understand. This practice is often referred to as “code-nesting hell.” While some level of nesting is inevitable, excessive nesting should be avoided to maintain code clarity and simplify debugging.
Deep nesting makes it harder to identify the origin of bugs or unexpected behavior. Code with excessive nesting is more challenging to modify and maintain. Small changes might require navigating through multiple layers of indentation, increasing the likelihood of introducing new bugs or overlooking side effects.
Here’s an example where we are developing a program to calculate the total price of items in a shopping cart, so rather than doing this:
total_price = 0
for category in cart_items:
for item in category:
for sub_item in item:
total_price += sub_item.price
We should do this:
total_price = 0
for category in cart_items:
for item in category:
total_price += calculate_item_price(item)
return sum(sub_item.price for sub_item in item)
We all can agree that the latter one is a much easier to debug and more efficient way to approach this program.
6. Follow the Principle of Least Astonishment (POLA)
The Principle of Least Astonishment, often abbreviated as POLA, is a crucial concept in software design. It suggests that the behavior of a system or piece of code should be intuitive and unsurprising to the user or developer. In other words, the way your code functions should align with what users or fellow developers would naturally expect. This principle helps reduce confusion, misunderstandings, and potential errors.
7. The Principle of Single Responsibility
The Single Responsibility Principle or SRP emphasizes that functions should have a single, well-defined purpose or responsibility. In other words, each function should do only one thing and do it well. Code that adheres to the single responsibility principle is inherently more readable. When functions have clear and focused purposes.
Moreover, Functions designed with a single responsibility are naturally more modular. They can be reused in different parts of your codebase without carrying unnecessary baggage.
8. Testing and Test-Driven Development (TDD):
TDD is a specific methodology that emphasizes writing tests before writing the actual code. Testing serves as a safety net for your code. It helps you catch bugs, validate functionalities, and ensure that your software behaves as intended.
There are several levels of testing that you can implement:
- Unit Testing: This involves testing individual units or components of your code in isolation. Unit tests focus on a specific function, method, or class to ensure that each piece of code functions correctly on its own.
- Integration Testing: Integration tests examine how different components of your software interact with each other. These tests ensure that the integrated parts work seamlessly as a whole and that data flows correctly between them.
- End-to-end Testing: End-to-end tests simulate real user scenarios and interactions with your software. They verify that the entire application functions as expected from start to finish.
To sum up, these were the Best 8 Code Practices that you need to follow if you’re working towards being an efficient programmer. As we grow up, the world of technology is becoming dynamic, and code practices evolve with time. It becomes important to learn these code practices when you work at a bigger scale, at that time the project will not be solely dependent on you but on team members as well, and if you don’t write code that is neat, your work buddies may suffer.
What are the best practices that you follow? Let us know in the comment section below!