How To Write Code Effectively In Python

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How To Code Effectively?

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Now that we have some brief knowledge on why it is essential to write code effectively, in this section, we will focus on understanding how it is possible for us to achieve this task. We will cover both the technical and practical aspects of the main requirements for writing the most efficient code for solving all your programs, tasks, and projects.

1. Effective Documentation:

Approach-1:

def treat():
"""
Creating the function for manipulating the motion of the turtle object as desired.
"""
speed(0)
penup()
goto(-140, 140)

For getting started, one of the best practices to follow is to ensure that you document your code. The more I started to code and work on numerous projects, the more I realized the significance of effective documentation. While programming, it is a common practice to get lost in your world of coding until you obtain the perfect solution to the particular problem or project you are encountering.

However, while being so deeply immersed in your code, it is often a noticeable issue that you don’t pay much attention to documenting or explaining your code by commenting on the different functions that you are utilizing throughout the program. The main issue is the problems it causes when you decide to exit the particular task and re-visit it after a few weeks or months.

Without proper documentation and understanding of the type of purpose of the particular code blocks or pieces of code, it becomes nearly impossible to determine what was the exact task you are trying to accomplish. And more importantly, how exactly were you trying to accomplish the task.

Hence, with effective documentation, not only do you help yourself who is reading the code after a long time, but you also help other people who want to read and understand your code. So, it is a good practice to input some lines of comments explaining the purpose of the codes, especially when publishing on a platform for others to view the code.

Approach-2:if __name__ == "__main__":
# create a GUI window
gui = Tk()
# set the background colour of GUI window
gui.configure(background="light green")
# set the title of GUI window
gui.title("Simple Calculator")

2. Making Your Code More Pythonic:

One of the ways to achieve the best results for your programs is by making them more pythonic. By making the appropriate changes in your style of coding to suit a more Python way of programming, you can make your code more readable, presentable, and much more efficient.

Some of the best practices that you can follow include making use of variables to assign a particular statement, and then ensuring that these variables perform a particular operation. Instead of hard coding an if statement with the particular condition, try to assign the following to two variables instead and compute the following accordingly.

The other best practices include making use of default arguments for functions in case the authenticated user does not wish to pass any particular command and ensure that the described function will return a value. Make use of the underscore variable (_) for throwaway variables so that you can filter out the unnecessary elements as and when required.

There are several improvements and adjustments that can be made to your respective Python code. The important aspect to keep in mind is how efficient will your modified code be and how pythonic is it. There are several more factors and advancements for making your code pythonic apart from the provided examples. We will look at the following in further depth in a future article.

3. Using Anonymous Functions:

Functions play a critical role in the construction of most major Python projects. Functions are usually used for repeatability and create structure to your Python programs. Functions are defined using the keyword ‘def,’ which can be called with defined or undefined parameters. When you call the particular the particular function, then whatever the value is to be returned is interpreted by the python compiler.

In Python, an anonymous function is a function that is defined without a name. While normal functions are defined using the def keyword in Python, anonymous functions are defined using the lambda keyword. The main advantage of using the lambda function is executing a lambda function that evaluates its expression and then automatically returns its result.

Below is one of the examples that shows us how to solve the problem statement for printing only the even numbers for a list of elements. Both the approaches with and without anonymous functions are explained and it is easy to notice which of the following approaches is better.

Approach-1:def even(a):
new_list = []
for i in a:
if i%2 == 0:
new_list.append(i)
return(new_list)

a = [1,2,3,4,5]
even(a)

Below is the second method with advanced functions. Note that the output provided by both the code blocks will result in the same values.

Approach-2:a = [1, 2, 3, 4, 5]
even = list(filter(lambda x: (x%2 == 0), a))
print(even)

For a complete guide and understanding of the concept of advanced functions in Python with complete codes and examples, refer to the following article reference provided below. It covers most of the essential concepts that are required for you to get started with the use of these advanced functions in your code blocks to optimize them and make them more efficient.

4. Try And Test Alternatives:

When you are working on a program, and you successfully accomplish the complex task at hand, it is amazing to give yourself a pat on the back and feel exhilarated. Once your excitement has boiled down, take a look into your code once again and try to analyze what you could have done better.

Upon further inspection and a closer look at your programming, you can figure out some minute or major changes that you can add to your program to make it much more efficient and compatible with the particular task. It becomes crucial to analyze the best changes that you can make either by yourself, with a friend, or with an expert.

Sometimes when you are on a tight schedule, you just want to be able to achieve the most reliant solution in the fastest possible way. In such scenarios, it is mostly fine to follow the conventional methods that will land you up with the most ideal solutions.

However, once you are done with your computation and your project, make sure that you re-visit the topic to optimize your code further for future references.

5. Practice Rigorously:

Now that we have a brief understanding of some of the most principle concepts and a basic idea on how to code effectively, the next critical step is to practice rigorously. With perfect practice techniques and repeating these adapted methods in every program or coding problem that you take up, you can achieve the best possible results.

Another essential point to note is that you must learn to consistently integrate some of the newer techniques that you constantly learn throughout your upgrading coding learnings. If you keep this procedure up for every single project, task, or simple question that you work on, you will eventually start to figure out the immense improvements in your style of writing code.

For a more extensive explanation of this point, please refer to the article below where I have thoroughly explained why it is significant for every programmer to code daily as a data scientist.

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