Houston  Sipes

Houston Sipes


Modular: The “Must” Foundations to Improve your Python Code and Carrer

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.”

Martin Fowler

We all know that during the rush of the development process, we are generally more focused on making our program work than making it fully readable. This situation becomes even more complicated when we face a problem never seen before and have a tight deadline to deliver the work. Sometimes we have to appeal to Stack Overflow to find a solution or take some time to read all similar questions until finding a new idea of how to work around the problem.

“When your program is a complete mess, but it does it’s job.”

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Source: kéké at tumblr

I use Stack Overflow a lot, but at least for me, the time I spent looking for a solution reduced the time (a hard and long one) I generally take to make my code cleaner and readable. If this happens to you too, maybe it’s because we are focusing more on “how to solve” than makes it accessible to other developers, well…** we want to make it work! **And even though we had time to format and document some things, who never spent a few hours trying to understand some code from years ago? The reason for this is simple, writing clean and readable code is a hard and tiring thing, but we should always think about the following sentence from the great “Uncle Bob”:

“The ratio of time spent reading versus writing is well over 10 to 1. We are constantly reading old code as part of the effort to write new code. …[Therefore,] making it easy to read makes it easier to write.”

_Robert C. Martin, _Clean Code: A Handbook of Agile Software Craftsmanship

We must put in our minds that as developers, programmers, software engineers, data scientists, and so on, our real audience is not computers, but other programmers (including ourselves). As the sentence from Uncle Bob defines, we usually spend more time reading documentation or other people code than making new ones, so why not spend more time on this part (however tiring it may be) and help you or others in the future?

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Source: Thom Holwerda at OSNews Comics

It will not only make you a better programmer, but it will also help with the scalability and maintainability of your product, also reducing the number of bugs (this is real) and the system complexity/risks reduction to changes or additions. If none of this is enough for you, I can give you one more thought to change old habits!

“Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live.”

John F. Woods

Let’s see some ways on how to do this then? Below is a summary of some methodologies to achieve high-quality and clean code.


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Source: Randall Munroe at XKCD

Refactoring is a way to restructure your code to improve its internal structure without changing its external functionality. The mindset behind this is: Did you manage to make it work? Go back to the beginning, clear, and modularize your program! It may seem like a waste of time to do this right at the beginning when you have several features to add, but doing this at steps will give you the following advantages:

  • Reduce workload in the long run;
  • Easier to maintain the code;
  • Increase reusability;
  • Decrease the time it takes to do this in the future or at new projects (the more you do, faster you will become in this activity)
  • If you try to do a better job than the previous refactoring, you will surely master this skill soon;
  • This skill is highly valuable in the job market and will highlight your profile (just look at “Desired to Have” Job Posts at LinkedIn or Indeed)

OK! I understand the advantages of refactoring, but how do I do this? It’s simple, here are some ways to achieve this:

If you want to go deeper into the topic, here is an excellent article that explains step by step how to achieve refactoring in Python, and here is a compilation of some Code Metrics available! If you prefer books, I advise the following:

Some good video lectures or workshops:

#data-science #refactoring #software-development #python #clean-code #visual studio code

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Modular: The “Must” Foundations to Improve your Python Code and Carrer
Ray  Patel

Ray Patel


top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Ray  Patel

Ray Patel


50+ Basic Python Code Examples

List, strings, score calculation and more…

1. How to print “Hello World” on Python?

2. How to print “Hello + Username” with the user’s name on Python?

3. How to add 2 numbers entered on Python?

4. How to find the Average of 2 Entered Numbers on Python?

5. How to calculate the Entered Visa and Final Grade Average on Python?

6. How to find the Average of 3 Written Grades entered on Python?

7. How to show the Class Pass Status (PASSED — FAILED) of the Student whose Written Average Has Been Entered on Python?

8. How to find out if the entered number is odd or even on Python?

9. How to find out if the entered number is Positive, Negative, or 0 on Python?

#programming #python #coding #50+ basic python code examples #python programming examples #python code

Ray  Patel

Ray Patel


Common Anti-Patterns in Python

Improve and streamline your code by learning about these common anti-patterns that will save you time and effort. Examples of good and bad practices included.

1. Not Using with to Open Files

When you open a file without the with statement, you need to remember closing the file via calling close() explicitly when finished with processing it. Even while explicitly closing the resource, there are chances of exceptions before the resource is actually released. This can cause inconsistencies, or lead the file to be corrupted. Opening a file via with implements the context manager protocol that releases the resource when execution is outside of the with block.

2. Using list/dict/set Comprehension Unnecessarily

3. Unnecessary Use of Generators

4. Returning More Than One Object Type in a Function Call

5. Not Using get() to Return Default Values From a Dictionary

#code reviews #python programming #debugger #code review tips #python coding #python code #code debugging