Name layers in this context refers to an organizational structure typically used in coding, to make codes more readable, structured and easy to understand. Name layers also improve efficiency in code execution due to their planned systematic structure. To get the full understanding of how name layers work in Python, let’s dive into the root of the problem.
The common issue people encounter while coding in Python (or any language to be honest) is the mishmash structure of their system, making the application code hard to follow, difficult to debug, and even more difficult to test or maintain in the long run. To solve this, coding requires high organizational strategies that can compartmentalize codes into sections, creating hierarchical and categorical infrastructures within the code itself. Python makes use of these layers by organizing classes, libraries, functions, modules, etc., in a structured, easy-to-follow manner.
Python Code for Name Layers
The structuring of code can be understood with Python. The Python language offers a relevant level of abstraction to the users which is instrumental in creating clear and understandable code.
We first take a sample case where no name layers are used and it seems difficult to understand the flow of the code. Then we’ll refactor the same code with name layers to actually observe the difference and simplification that occurs.
def loop(numbers): sum = 0 for number in numbers: if number % 2 == 0: square = number * number sum += square return sum print(loop([1, 2, 3, 4, 5]))
The above code works perfectly fine, but it’s slightly difficult to understand what the function ‘loop’ does just by a quick look.
Refactoring the Code Structure.
Let’s now refactor the code and reintroduce it with name layers. Here, we will break the code into different functions, each performing a single operation.
def square(number): return number * number def sum_of_squares(numbers): sum = 0 for number in numbers: if number % 2 == 0: sum += square(number) return sum print(sum_of_squares([1, 2, 3, 4, 5]))
In the refactored code, it’s clear what each function does and it’s easier to read and understand. We have formed a few functional layers inside our code.
Using Python Libraries
Python provides a huge number of libraries that are pre-defined to perform various functions. They help in reducing the complexity of the code to a considerable extent. For example, if you want to perform complex array operations, you can use the NumPy library.
Python libraries become an essential part of name layers by dividing functions into different libraries or using existing ones.
In conclusion, name layers in Python are an effective method of bringing clarity, order, and efficiency to your code. By splitting your code into distinct layers based on functionality, you improve the readability and maintainability of your software, making it easier for others (and your future self) to understand the code, debug, test and even improve further.