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Efficient coding practices

Efficient coding practices

Efficient coding practices be in Efficinet shortly. Data Security Services. Efficiency Codkng, once we know our code solves the problem, we should check if it does so efficiently. They should be short and meaningful.

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Efficient coding practices -

Just some of those benefits include:. Following good practices streamlines all development processes because the whole team is on the same page about the work they are doing.

When an entire team is following solid coding practices, everyone has a better overall understanding of the project, which leads to fewer instances of a software glitch or error and a reduced need for constant fixes.

That maximizes the efficiency of everything developers code, which ultimately translates into a boost in productivity.

Peer reviews and code comments allow teams to identify bugs and problems earlier on, which allows them to work on fixes before the product goes to production. That means there will be fewer issues down the line, which will ultimately translate into more efficient code, better performance, and a more stable product that ultimately also means more robust software.

Through them, a team can have a more organized file structure, all linked with the tasks at hand. This makes it easier for developers to find what they have to work on at any given time while also helping them better organize their jobs.

All of the above increased efficiency and productivity, better workflow, and higher product quality converge into this benefit. Getting those five benefits should be enough reason to convince any developer or development team to adopt good or best coding practices.

Also, they are great for illustrating how important it is to write code the correct way. Comments are simple annotations whose only goal is to make it easier for anyone checking the code to understand exactly what the developer was trying to do. Many developers feel like it is a waste of time to write comments, but that is never, ever the case.

Even when comments feel redundant, they can serve a purpose, from reminding the developer of the logic behind a line of code to teaching beginner programmers how to write good code to illuminate the objective behind it. Another staple of good coding standards, peer review, implies that all the code written by a developer is always reviewed by someone else.

This simple step allows developers to pass their work onto a fresh set of eyes that can detect issues with the code more easily and point them out before they become bigger problems.

Peer review should be a standard process in all kinds of projects, but its importance in bigger and more complex projects cannot be understated. A pull request happens whenever a developer tells the rest of the team about changes they have worked on and are to be pushed to the main repository.

You can think of a pull-request system as a warning system in which developers tell one another that there is modified code that needs to be reviewed and discussed before being merged. One of the most neglected practices in all software development, the inclusion of tags is believe it or not highly beneficial for the process.

Thus, they can access them more efficiently while improving their overall organization. Tags can also help identify features, bug fixes, and improvements, which ultimately leads to an index of sorts of all the things covered in a particular project.

Naming conventions are useful for identifying and distinguishing classes, variables, types, and functions in source code. This also contributes to better code readability. Additionally, it provides more information to the reader, promotes clarity, and reduces ambiguity.

Repetitive code, also called duplicate code or copy and paste code, is a block of code that occurs multiple times in your codebase.

The benchmark function in the microbenchmark package does this, but also compares functions, runs them multiple times, and calculates summary statistics. Code profiling is taking time snapshots at intervals throughout the code in order to find the location of bottlenecks. Base R function Rprof does this, but it is not user friendly.

Instead, use profvis from the profvis package. Use the parallel package to parallelize your code. Tip 3: Use a matrix instead of a dataframe if possible. Matrix operations are fast because with predefined dimensions, accessing any row, col, or cell is a multiple of a dimension length.

These notes are from the DataCamp course Writing Efficient R Code. But it's important to use comments wisely, only commenting where necessary and avoiding redundant or unnecessary ones. Another way to document code is by using inline documentation. Inline documentation is embedded in the code itself and can be used to explain what a specific function or piece of code does.

Inline documentation is often used in combination with tools like JSDoc , which provides a standard for documenting code in JavaScript. Tools like Typescript can also provide automatic documentation for our codebase, which is hugely helpful. If you'd like to know more about Typescript, I wrote a beginner friendly guide a while ago.

And Lastly, tools like Swagger and Postman can be used to document APIs, providing a way to easily understand how to interact with them. If you're interested in knowing how to fully implement, test, consume and document APIs, I recently wrote two guides for REST APIs and GraphQL APIs.

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Forum Donate. Germán Cocca. Let's go! Table of Contents What does it mean to write "clean code" and why should I care? How can I assess whether a codebase is clean or not? Tips and conventions to write cleaner code Effectiveness, efficiency and simplicity Format and syntax Naming Conciseness versus clarity Re-usability Clear flow of execution Single responsibility principle Having a "single source of truth" Only expose and consume information you need Modularization Folder structures Documentation Wrapping up What Does it Mean to Write "Clean Code" and Why Should I Care?

How Can I Assess Whether a Codebase is Clean or Not? Tips and Conventions to Write Cleaner Code Effectiveness, Efficiency and Simplicity Whenever I need to think about how to implement a new feature into an already existing codebase, or how to tackle the solution of a specific problem, I always prioritize this three simple things.

Effectiveness First, our code should be effective , meaning it should solve the problem it's supposed to solve. Efficiency Second, once we know our code solves the problem, we should check if it does so efficiently. Simplicity And last comes simplicity.

But some guidelines we can follow are: Can you easily understand what the program does at each line? Do functions and variables have names that clearly represent their responsibilities? Is the code indented correctly and spaced with the same format all along the codebase? Is there any documentation available for the code?

Are comments used to explain complex parts of the program? How quick can you identify in which part of the codebase are certain features of the program? Does the code follow a modular approach, with different features separated in components?

Is code reused when possible? Are the same architecture, design, and implementation decisions followed equally all along the codebase? Format and Syntax Using consistent formatting and syntax throughout a codebase is an important aspect of writing clean code.

Naming Naming variables and functions clearly and descriptively is an important aspect of writing clean code. log y ; } ab 5, 3 ; In this example, we have a function that takes two parameters, adds them to a hardcoded value of 10, and logs the result to the console.

log totalWithTax ; } calculateTotalWithTax 50, 20 ; In this example, we have a function that calculates the total price of a product including tax. Conciseness vs Clarity When it comes to writing clean code, it's important to strike a balance between conciseness and clarity.

length; console. log countVowels "hello world" ; This example uses a concise arrow function and regex to count the number of vowels in a given string. match vowelRegex []; return matches. length; } console. log countVowels "hello world" ; This example uses a traditional function and regex to count the number of vowels in a given string, but does so in a way that is clear and easy to understand.

Reusability Code reusability is a fundamental concept in software engineering that refers to the ability of code to be used multiple times without modification. log circleArea, rectangleArea, triangleArea ; This example defines three functions that calculate the area of a circle, rectangle, and triangle, respectively.

log circleArea, rectangleArea, triangleArea ; This example defines a single function calculateArea that takes a shape argument and a variable number of arguments.

Clear Flow of Execution Having a clear flow of execution is essential for writing clean code because it makes the code easier to read, understand, and maintain. log discountedPrice ; } As we can see, example 1 follows a clear and logical structure, with a function that takes in the necessary parameters and returns the calculated result.

Single Responsibility Principle The Single Responsibility Principle SRP is a principle in software development that states that each class or module should have only one reason to change, or in other words, each entity in our codebase should have a single responsibility.

This principle helps to create code that is easy to understand, maintain, and extend. connect ; db. saveOrder order, total ; } In this example, the processOrder function handles several responsibilities: it validates the order, calculates the total, applies discounts, and saves the order to a database.

quantity; } ; return total; } applyDiscounts total { if this. saveOrder this. order, this. save ; } In this example, the processOrder function has been split into two classes that follow the SRP: OrderProcessor and OrderSaver.

Having a "Single Source of Truth" Having a "single source of truth" means that there is only one place where a particular piece of data or configuration is stored in the codebase, and any other references to it in the code refer back to that one source.

js import { getCurrentWeather } from '. Only Expose and Consume Data You Need One important principle of writing clean code is to only expose and consume the information that is necessary for a particular task.

com' Modularization Modularization is an essential concept in writing clean code. Using modularization provides several benefits such as: Re-usability: Modules can be reused in different parts of the application or in other applications, saving time and effort in development.

Encapsulation: Modules allow you to hide the internal details of a function or object, exposing only the essential interface to the outside world.

This helps to reduce coupling between different parts of the code and improve overall code quality. Scalability: By breaking down large code into smaller, modular pieces, you can easily add or remove functionality without affecting the entire codebase.

toFixed 2 ; In the above example, the calculatePrice function is used to calculate the total price of an item given its quantity, price, and tax rate. toFixed 2 ; In the above example, the calculatePrice function has been broken down into two smaller functions: calculateSubtotal and calculateTotal.

Folder Structures Choosing a good folder structure is an essential part of writing clean code. js In this example, the project structure is organized around file types, such as components, containers, and pages. ico In this example, the project structure is organized around features, such as components, pages, and utils.

Documentation Documentation is an essential part of writing clean code. And Lastly, tools like Swagger and Postman can be used to document APIs, providing a way to easily understand how to interact with them If you're interested in knowing how to fully implement, test, consume and document APIs, I recently wrote two guides for REST APIs and GraphQL APIs.

Wrap ping Up Well everyone, as always, I hope you enjoyed the article and learned something new.

Fat-burning cardio workouts clean and efficient Efficient coding practices is the hallmark of a skilled developer. Learn how to work Effjcient way Efficient coding practices writing practtices code. Cofing great, high-performing software application with no bugs and Efficient coding practices pactices that the code behind it is squeaky clean. For developers, the code that they write is the foundation of a much bigger picture. Making sure that all chunks of code are clean is a surefire way to have a well-developed software product. Writing efficient code is paramount for any developer or aspiring developer. Clean and efficient code enhances readability and maintainability and improves the performance and scalability of software projects. Efficient coding practices This section explains how to Ecficient code run Joint maintenance support. The Efficient coding practices basic practice in efficient coding is Efficient coding practices keep your R, RStudio, practoces package versions up to date. Check you version from the version global list object. RStudio closes for the update. Once updated, RStudio should default to using the new version of R too. Benchmarking is the capture of the performance time for comparison to alternative solutions.

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