Forem: Sreedeep

I Surveyed the Top 10 Backend Frameworks Here's What I Found

Sreedeep — Sun, 12 Jan 2025 20:27:10 +0000

While creating a new project one of the main things that clouds your mind is what framework you are going to use. Every framework has its own drawbacks and advantages we will be measuring these in this article.

The project I'm working on is called LiveAPI, which is a super convenient way to generate API documentation on a large scale. We are working to enable all web backend frameworks in LiveAPI for the creation of API documentation. We need to understand how frameworks are implemented, how routes are managed, what files are involved, dependencies, etc., in order to build this feature.

I will try to explain all the things I learned on the way into this small comparison article. This article will help you choose a framework for your SaaS projects or learn a few new things from unknown frameworks you have never used.

Let's break down the frameworks based on their use cases. First, let's look into the popular ones. These frameworks have strong community support and scalability.

Most Popular General Frameworks for Novices and Experts

The framework should handle many backend tasks like routing, authentication, database integrations, templating, etc. There are only a few such frameworks:

Django: Python framework
Spring Boot: Java framework
Ruby on Rails: Ruby programming

These frameworks are best for CRUD apps, SaaS Projects, and Restful APIs.

Django backend mainly comprises URLs, Views, and models. You need to have a good understanding of each of these to build good Django systems. URLs are used to design API routes. Views are used for API logic. And Models are for database integrations and creating migrations.

Instagram: Handles billions of user requests daily, showcasing Django's scalability. More on this HN thread.
Pinterest: Django is used for its rapid development and easy database integration.

Django is actively maintained and has great documentation along with a tutorial on how to get started.

Spring Boot simplifies Java backend development by providing a pre-configured setup. It's based on Controllers, Services, and Repositories. Controllers handle HTTP requests and routes. Services control the business logic flows. Repositories handle database operations. Check out the official spring documentation at spring.io.

Netflix: Manages its microservices architecture using Spring Boot's scalability and reliability. More on this Hackernews Discussion
Amazon Web Services (AWS): Uses Spring Boot for several internal services due to its flexibility and performance.

Ruby on Rails is called a convention-over-configuration framework . It emphasizes simplicity and readability mainly. It structures the backend around Models, Views, and Controllers (MVC), promoting DRY (Don't Repeat Yourself) principles. With features like scaffolding and built-in ORM (ActiveRecord), Rails makes it easy to develop database-driven applications quickly. Scaffolding means generating the code for a model, controller, views, routes, and even database migrations based on a single command.

Yes, Rails is awesomely fast to prototype in, and also excellent to build a long-term sustainable business.

GitHub: The world's largest code repository was initially built with Rails for its fast prototyping capabilities.
Shopify: Handles millions of online stores using Rails' robust database handling and templating features.

There are small frameworks ideal for APIs with flexibility and performance in mind. Let's look into some of them.

Microservice-Oriented Frameworks

These are lightweight frameworks designed to create salable microservices. Microservices are software composed of small independent services that communicate over well-defined APIs. These services are owned by small, self-contained teams.

Flask (Python)
Express.js (Node.js)
FastAPI (Python)

Flask uses a lightweight design, and offers the flexibility to add extensions, making it a popular choice for small-scale microservices or APIs. Airbnb uses Flask for lightweight services that support its larger infrastructure.

Express.js is a minimal and fast Node.js framework for backend development. It’s highly extensible and often used in combination with other Node.js tools to build robust microservices. Its asynchronous architecture and middleware system are ideal for handling concurrent requests in a microservice.

Uber, PayPal uses Express.js for parts of its real-time dispatch systems.

FastAPI is a modern Python framework known for its performance and simplicity. It is based on standard Python-type hints. Using them, you get automatic data validation, serialization, and documentation. Including deeply nested JSON documents. And you get editor completion and checks everywhere. Designed around the OpenAPI (Swagger) and JSON Schema standards.

It includes 2 alternative interactive API documentation systems that are generated automatically. It's OAuth2 capable from the start (including JWT). Has a Dependency Injection system, compatible with all databases (relational and NoSQL), Websockets, GraphQL, CORS, etc.

Microsoft uses FastAPI for some internal machine learning services due to its speed and support for async requests.

Next, there are frameworks tailored for large-scale production with a focus on security, performance, and enterprise-level integrations.

Enterprise-Grade Frameworks

Here are some dependable enterprise ranges, designed for large-scale production frameworks. If you joined an MNC company then you are likely to work on some of these frameworks. Security is a major player in these scenarios. Data breaches can cost millions to the company.

Spring Boot (Java)
ASP.NET Core (C#)
NestJS (Node.js)

ASP.NET Core is a modern, cross-platform framework from Microsoft designed for building web applications, APIs, and cloud-based systems.

Its performance and reliability make it a great choice for enterprise-grade systems. The framework supports dependency injection and has excellent integration with Azure for cloud solutions. It excels in performance and integration with Microsoft tools.

Dependency Injection in ASP.NET provides required objects (dependencies) to a class automatically, making the code simpler, modular, and easier to test.

Stack Overflow and Microsoft Teams Uses ASP.NET Core for its high-performance backend to serve millions of users.

NestJS is a progressive framework for Node.js that incorporates TypeScript for building efficient, reliable, and scalable server-side applications. Inspired by Angular’s architecture, NestJS uses decorators and modules to simplify development. Its support for microservices and GraphQL makes it a go-to choice for enterprise solutions in the JavaScript ecosystem.NestJS is ideal for teams familiar with JavaScript/TypeScript and building modern APIs.

Adidas and Capgemini: Uses NestJS for creating scalable and efficient backend services and for developing robust APIs in enterprise projects

Now, let's do a comparison of frameworks based on performance, usability, community support, flexibility, and security to guide you to take informed decisions.

Evaluation Criteria And Benchmarks

Here is a tabular representation of the different criteria used to differentiate these frameworks. We did not look into the popularity of the frameworks, since it is relative to the type of people using these.

Framework	Performance	Ease of Use	Community Support	Flexibility	Security Features
Django	High scalability but slightly slower for real-time apps	Moderate learning curve with strong documentation	Large and active community with many libraries	Highly flexible; supports plugins and third-party libraries	Comprehensive security features out-of-the-box
Spring Boot	Excellent for high-performance enterprise apps	Challenging for beginners; excellent for experienced Java developers	Extensive support in the enterprise Java ecosystem	Very flexible; integrates well with various tools and databases	Robust security with enterprise-grade solutions
Ruby on Rails	Good for CRUD apps; less suited for high concurrency	Beginner-friendly with conventions over configuration	Strong community with many open-source gems	Moderately flexible; relies on conventions for simplicity	Good security features but requires developer awareness
Flask	Lightweight, great for small services but not ideal for large-scale apps	Very easy for small projects; limited features	Active but smaller community compared to Django	Highly flexible; requires manual integration for features	Basic security features; requires extensions for advanced needs
Express.js	Handles high concurrency well; ideal for real-time apps	Easy to learn and widely used; minimal configuration needed	Very large community with extensive Node.js ecosystem	Extremely flexible; middleware system allows customization	Basic security features; relies on middleware for customization
FastAPI	Fast due to async support; great for APIs and microservices	Beginner-friendly with type hints and strong documentation	Growing community; very active in the Python space	Flexible with async support and integrations	Strong security features with type-safety advantages
ASP.NET Core	High-performance framework with native multithreading	Moderate learning curve; great tooling for .NET developers	Strong support from Microsoft and .NET developers	Highly flexible; strong integration with Azure and third-party tools	Built-in security for authentication and authorization
NestJS	Good performance with support for modern async workflows	Moderate learning curve; easier for those familiar with Angular	Fast-growing community with active contributions	Moderately flexible; modular design supports modern workflows	Good security with decorators and modules for sensitive data

Conclusion

I hope this article helped you to learn about frameworks and their advantages. Thanks for the read. If you need API documentation for any of these frameworks feel free to try out LiveAPI, we would like to hear your experiences.

How to make money contributing to Open-Source

Sreedeep — Tue, 31 Dec 2024 19:16:26 +0000

A great new year to all the readers 🎉. In this article I will explain on how to make money contributing to opensource repos. Many companies have funds to maintain opensource repos. If you are need of some extra exposure to the field, learn more programming by making impact on big project you are at the right place.

There is a community called Algora.io. Here you can see a list of projects with their bounty listings.

Filter by programming language or your interested niche. There are 100+ projects and a lot of issues. They also have an active Discord channel. You can select the issues you want to work for from github. First, add a comment on the issue informing them that you are working on it.

If you are new to contributions to opensource project I got you covered. First create a fork. Make your changes that will fix the issue or implement a new feature based on the issue you took. Next create an PR (Pull request) with appropriate information on the changes, a video describing the change is better. Some projects have some contribution guidelines For example: signing every commit etc. Then you are good to go.

The payment is through Stripe, you just need to connect your account with Stripe and get payouts.

You can do a global search for bounties in the GitHub search to find similar opportunities but be vigilant, I didn't try any of those, many pay in crypto.

Happy hacking everyone ~ 🥳

How to Start Solving Problems, Build Solutions, and Validate Your Idea Without Spending a Dollar

Sreedeep — Sun, 29 Dec 2024 18:53:26 +0000

Starting something new can be both exciting and daunting. Whether it's launching a business, building a product, or offering a service, the key lies in solving real world problems people face. Let’s break this down into actionable steps and address two common fears that hold people back.

Step 1: Find a Problem You Can Solve

Every great idea starts with a problem. Look around—what are people complaining about? What’s something you or your friends struggle with? These are golden opportunities.

Do parents often stress about meal prep for their kids?
Are freelancers overwhelmed by managing their invoices?

Make a list of problems people frequently mention. The simpler the problem, the better! Don’t overthink this step; the goal is to identify something solvable.

Step 2: Craft an Irresistible Solution And Do Your Research!

Once you’ve identified the problem, it’s time to dream up a solution. Your solution doesn’t have to be perfect; it just has to make the problem less painful.

Now, do some research. Check out forums, social media groups, or Reddit threads where people discuss this issue. How are they solving it now? What are their frustrations with existing solutions?

Armed with this knowledge, refine your idea to offer something unique.

A meal-prep guide tailored to picky eaters.
A simple invoicing tool with reminders for freelancers.

Step 3: Validate Without Spending Money

Before you invest time or money, test your idea. The easiest way? Talk to people! Share your solution with potential customers and see how they respond. Social media polls, free prototypes, or casual conversations work wonders.

Example:
Create a free PDF or simple tool and share it with your network.
Ask, “Would you pay for this?” and see their reactions.

You’re not aiming for perfection—just proof that people care enough to take action.

Overcoming the Two Big Fears

Fear 1: The Fear of Starting

Starting anything new is scary. What if it fails? What if people laugh? These thoughts can paralyze you. The solution is to start small.

Spend an hour researching the problem.
Talk to three people about your idea.

Small wins build momentum. Repeat these experiments consistently, and you’ll gain confidence over time.

Fear 2: The Fear of Asking

Many of us dread asking for feedback or pitching our ideas because we fear rejection. “What if they say no?” But here’s a reframe: rejection is a gift. It’s free feedback that sharpens your idea.

Treat rejection as desirable. If someone says, “This isn’t for me,” ask why. Their answer could help you improve or pivot.

Conclusion

Starting something new doesn’t have to be overwhelming or expensive. Focus on finding a problem, crafting a solution, and testing it quickly. Don’t let fear of starting or fear of asking hold you back. Remember, small steps lead to big results, and every rejection gets you closer to success.

Hi , my name is Sreedeep CV , these insights are from the book Million Dollar Weekend, I am also working on my small but impactful product called LiveAPI which is for automatic API docs generation in scale, do check this out.

5 CSS Tricks That Will Save You a Lot of Time

Sreedeep — Sat, 28 Dec 2024 19:32:23 +0000

Working with CSS is always a nightmare for back-end developers. Here lets conspire against those front end dev's and lean some CSS tricks that even frontend developers miss.

1. Centering Trick in Flexbox

Let's start with the famous centering divs problem. Here we will make use of a flexbox. No need to set absolute positioning or work with margins, do this:

  .flex-center-demo {
    display: flex;
    justify-content: center;
    align-items: center;
  }

2. Quick Grid Auto-Placement

You will need this if you are designing navbars or dashboard. If you have some collection of items and you need to place them together then use this.


.auto-grid-demo {
  display: grid;
  grid-template-columns: repeat(auto-fill, minmax(120px, 1fr));
  gap: 1rem;
}

It Automatically fills rows with boxes at a minimum width of 120px.

3. Adjacent Sibling Selector

This is useful when you have adjacent elements, elements that come after a heading for example author's name below the heading.

h2 + p {
    font-style: italic;
    color: blue;
  }

Here is an image:

4. Make Use of Pseudo-Class not()

When you are designing some element and once element you need to design differently for instance then use this. Here is an example of collection of boxes , apply the CSS except for the third one which belong to special class.

.box:not(.special) {
    background-color: #3498db;
    color: #fff;
    margin: 0.5rem;
    padding: 1rem;
    border-radius: 4px;
  }

5. Nail CSS animation like a pro

Getting CSS animations right around first time is a bit problamaic use these key-frame to simplify complex animations into a single rule that’s easy to adjust or reuse.

@keyframes fadeIn {
  0% {
    opacity: 0;
  }
  100% {
    opacity: 1;
  }
}

.fade-in-demo {
  animation: fadeIn 3s forwards;
  background-color: #e67e22;
  color: #fff;
  padding: 1rem;
  text-align: center;
  border-radius: 4px;
}

Bonus tip!

Here is some extra CSS debugging trick that I always use. If you think you messed up the CSS and have no idea whats wrong, try to get this boxes around every element you have. This was very useful in debugging CSS for me.

/* Debug: Outline every element with a red border */
* {
  outline: 1px solid red !important;
}

I hope you find this article useful. My name is Sreedeep and I am working on a tool called LiveAPI - Helping people generate API docs efficiently with AI.

GoLang beyond basics : Escape analysis

Sreedeep — Thu, 26 Dec 2024 10:28:44 +0000

Lets understand how Golang handles variables and what this Escape Analysis is. Golang have 2 types of memory allocation datatypes used in go runtime environment called stack and heap.

The stack is faster for doing operations on(in and out). Variables inside a function that are accessed within it go to this stack. Eg:

package main

import "fmt"

func stackExample() int {
    a := 10        // Variable `a` is allocated on the stack
    b := 20        // Variable `b` is allocated on the stack
    result := a + b // `result` is also allocated on the stack
    return result   // All stack variables are popped off when the function exits
}

func main() {
    result := stackExample() // Function call happens, variables are pushed to the stack
    fmt.Println(result)      // Print the result
}

This is how the stack works in GoLang. Next is a heap. It's a dynamic memory ie, its size can be adjusted based on the requirements. Here is a simple example of heap allocation.

package main

import "fmt"

func heapExample() *int {
    num := 42           // Variable `num` is created inside the function
    return &num         // Returning the address of `num`, which escapes the function
}

func main() {
    ptr := heapExample() // The value pointed to by `ptr` is allocated on the heap
    fmt.Println(*ptr)    // Accessing the heap-allocated variable through the pointer
}

Here since the function returns a pointer to num, the Go runtime detects that num will be accessed outside of the function's scope. As a result, it allocates num on the heap instead of the stack.

A Heap is used to store variables that are beyond the scope of a function or a goroutine. Sometimes when there value of a variable is very huge it's stored in a heap.

After understanding these two it's time to jump into escape analysis. There’s no way of knowing which variables will be allocated to the heap simply by reading the Go code. We can understand this with an 'Escape Analysis'. By escape, we mean whether the variable escapes the scope of a function determining whether it will be stored on a heap or stack.

Run the build command of the go code like this

go build -gcflags '-m -l'

-m - Flag to show escape analysis.
-l - Disable inlining to keep stack traces accurate.

Take this code:

package main

func escapeExample() *int {
    x := 42
    return &x // x escapes because its address is returned
}

func noEscapeExample() int {
    y := 100
    return y // y does not escape
}

func main() {
    _ = escapeExample()
    _ = noEscapeExample()
}

The results are something like these:

./main.go:4:10: &x escapes to heap
./main.go:12:13: main escapes to heap

So, why do we do all these? This analysis can prove to be useful when you are debugging for performance issues. Variables are better stored in a stack rather than in a heap. You can find where variables escape to the heap and refactor the code for better efficiency.

Hope you learned something new today.
I am currently building LiveAPI which is a tool for API document generation do try that out.

Thanks for reading.

🔍 3 Hidden Linux Logs You’ve Never Heard About! 🐧 (Uncover the Secrets!)

Sreedeep — Mon, 23 Dec 2024 19:42:22 +0000

Log files can provide great insights into operations, user activity, and potential threats. Understanding these log files, wtmp, utmp, btmp, and auth.log, was a game-changer for me.

In this article, we’ll explore these logs, their practical applications, and how you can use them to diagnose issues.

1. `wtmp`: Login and Logout Records

The wtmp log tracks historical login and logout events on a Linux system. This binary log, stored in /var/log/wtmp, helps administrators review access patterns and pinpoint login anomalies. To analyse its contents, you can use the last command.

$ last

This command reveals the history of user sessions, including start and end times, terminal IDs, and host information.

2. `utmp`: Active Users

Its stored in /var/run/utmp, this log tracks currently logged-in users and their active sessions. Use the who command to display this information in real-time

$ who

Its essential for administrators to monitor active sessions and ensure system integrity.

3. `btmp`: Invalid Login Attempts

The btmp log records failed login attempts, providing critical insights into potential brute force attacks or unauthorized access attempts. Analyze it with the lastb command:

$ sudo lastb

This helps identify the source and frequency of failed login attempts, enabling quick response to possible threats.

Bonus 1: `boot.log`

The boot.log file contains messages from the boot process. It’s a valuable resource for diagnosing slow boot times or identifying failing services.

Here is what I found in my system which helped me debug slow boot time.

Bonus 2: `utmpdump`

For binary logs like wtmp or btmp, tools such as utmpdump convert the contents into readable text. Example:

$ utmpdump /var/log/wtmp

This output reveals detailed session information, including event types, user IDs, and timestamps.

Hello, I forgot to introduce myself. I am Sreedeep, I am building LiveAPI. Its a Super Convenient API Documentation solution for startups.

In LiveAPI we added a new feature in which you can see high level back-end logs which will help you debug the issues while generating API documentation. Tryout our free trial.

Breaking the Myth: Object Detection Isn't Hard as Thought

Sreedeep — Sun, 03 Dec 2023 14:48:00 +0000

Hearing about AI and object detection can create an illusion among developers that doing such things is far beyond the reach of traditionally trained programmers.

But that's not the case. Object detection is easy to set up and only requires a few minutes of your time.

It's a computer vision technique that works to identify and locate objects within an image or video. For example, traffic surveillance systems, self-driving cars, and facial recognition systems all employ this technology to track down vehicles, faces, and other objects of interest.

This article will use YOLO (You Only Look Once) for performing the object detection tasks.

Object Detection with YOLO

Introduction to YOLOV8

YOLOv8 (You Only Look Once) is an open-source Computer Vision AI model released on January 10th, 2023. It’s called YOLO because it detects everything inside an image in a single pass. The new version can perform image detection, classification, instance segmentation, tracking, and pose estimation tasks.

The new v8 has better performance and flexibility. This is pre-trained on COCO (Common Objects in Context) and ImageNet datasets.

Using YOLO: An Example

YOLO can be used for a wide variety of applications and use cases. Here is an example of borderless table detection. A detailed section on implementation is presented at the end of the article.

For the full article and the practical part visit our blogpost https://journal.hexmos.com/yolo-object-detection/

Point, Shoot, and Detect: Object Detection with PyTorch Mobile

Sreedeep — Sun, 19 Nov 2023 20:39:10 +0000

In this article we will set up a Mobile Application for Object Detection. We will use PyTorch Mobile to optimize and run the YOLOv5 on an Android app.

AI mobile app development Challenges

Developing AI applications in mobile is difficult due to slow loading speeds and scalability problems. They heavily rely on cloud infrastructure, In addition, certain AI frameworks or designs can't be used on mobile devices, limiting their access and usefulness.

Larger AI systems need cloud connections, making them costly. Developers need to make algorithms compatible with mobile devices. We should be able to execute our AI locally on the phone instead of using the cloud as a Service. This will contribute to making AI more accessible and efficient in mobile applications. In this article, we will introduce you to PyTorch Mobile and setup a basic app for testing out this framework.

PyTorch

PyTorch is a machine learning framework based on the Torch library. People use PyTorch's tools to make neural networks and machine learning algorithms. PyTorch defines a class called Tensor (torch.Tensor) to store and operate on homogeneous multidimensional rectangular arrays of numbers. PyTorch Tensors are similar to NumPy Arrays, but can also be operated on a CUDA-capable NVIDIA GPUs.

About PyTorch mobile

Running machine learning algorithms on mobile devices for prediction is crucial in today's tech landscape. The move to edge computing is not about speed. It's also about protecting user privacy and enabling new interactive experiences.
PyTorch Mobile helps connect training and deployment in the PyTorch environment. This platform streamlines the journey from model inference in mobile applications. PyTorch Mobile is in beta and gaining popularity for widespread production use. This software has APIs that will make mobile based machine learning better in the future.

Next, we will focus on trying out an Android app to test PyTorch Mobile capabilities.

Setting up the Demo App

YOLOv5 Vision AI

YOLO is one of the popular open-source vision AI. YOLOv5 is a great object detection algorithm that uses Deep Convolution Neural Networks(DCNN). This helps to predict object classes instantaneously.YOLOv5 can detect people, vehicles, and animals in various environments. Its full form is "You only look once". This indicates that it takes the input photo and spits it into grids. Then it assigns bounding boxes and probabilities to each grid. The current v5 works on a complex architecture called the EfficientDet network, which improves its capability to detect objects smoothly.

These are the steps we take to setup YOLO for mobile:

Optimizing the YOLO for the Android App

Clone repo and install requirements.txt in a Python>=3.8.0 environment

git clone https://github.com/ultralytics/yolov5
cd yolov5
pip install -r requirements.txt

Create an optimized model for mobile

python export.py --weights yolov5s.pt --include torchscript --optimize

You will get a yolov5s.torchscript which is a mobile-optimized version of the model. Then we move it to the app directory and import it at ObjectDetection/app/src/main/assets/yolov5s.torchscript.

Setting up the Android App

We will use an app from the PyTorch example repository to demonstrate PyTorch Mobile.

This is the repository here

For setup download the latest Android Studio from here

Setup the Android Studio SDK from the SDK tools menu:

Connect to a phone using wireless debugging.

Run the gradle script with the --stacktrace option to show more debug information.

./gradlew installDebug --stacktrace

This will create a prompt on your phone to install the app.

Results

Conclusion

This concludes our exploration of PyTorch Mobile. We got to know how to run algorithms in a mobile Android app and set up basic object detection. Hope this article was useful for you.

React native expo tenor search Component

Sreedeep — Sun, 14 May 2023 11:27:43 +0000

Recently we needed to integrate tenor gifs into our product, due to tenor apis up-scaling to v2 we couldn't find any opensource package , hence we created this expo-tenor-search package for react native .

expo-tenor-search

the main features are simple

you can search gifs
display gif categories

For easy integration into your apps there is this function handleGifSelect which you can define your logic on what to do with the selected gif.

This is how it looks in code

import { GifSearch } from 'expo-tenor-search'

export default function GifScreen() {
  const handleGifSelect = (data) => {
    console.log(`Selected GIF: ${data}`)
  }

  const styles = {
    searchbox: {
      searchContainer: {
        height: 45
      }
    },
    gifbox: {
      img: {
        borderRadius: '10px'
      }
    }
  }
  return (
    <GifSearch
      tenorkey={'xxx-xxx-xxx-xxx'}
      MediaFilter={'minimal'}
      onGifSelect={handleGifSelect}
      styles={styles}
    />
  )
}

you can pass custom css into this with which you can control the UI .
there are selectors like searchContainer , closeButton,button , img etc using which you can manipulate the styles .

The results produced are :-

If you find this useful and want to know more about its implementation give this an up vote.

Will be posting more stuff here soon.

Follow me here twitter for updates.

Forem: Sreedeep

I Surveyed the Top 10 Backend Frameworks Here's What I Found

Most Popular General Frameworks for Novices and Experts

Microservice-Oriented Frameworks

Enterprise-Grade Frameworks

Evaluation Criteria And Benchmarks

Conclusion

How to make money contributing to Open-Source

How to Start Solving Problems, Build Solutions, and Validate Your Idea Without Spending a Dollar

Step 1: Find a Problem You Can Solve

Step 2: Craft an Irresistible Solution And Do Your Research!

Step 3: Validate Without Spending Money

Overcoming the Two Big Fears

Conclusion

5 CSS Tricks That Will Save You a Lot of Time

1. Centering Trick in Flexbox

2. Quick Grid Auto-Placement

3. Adjacent Sibling Selector

4. Make Use of Pseudo-Class not()

5. Nail CSS animation like a pro

Bonus tip!

GoLang beyond basics : Escape analysis

🔍 3 Hidden Linux Logs You’ve Never Heard About! 🐧 (Uncover the Secrets!)

1. wtmp: Login and Logout Records

2. utmp: Active Users

3. btmp: Invalid Login Attempts

Bonus 1: boot.log

Bonus 2: utmpdump

Breaking the Myth: Object Detection Isn't Hard as Thought

Object Detection with YOLO

Introduction to YOLOV8

Using YOLO: An Example

Point, Shoot, and Detect: Object Detection with PyTorch Mobile

AI mobile app development Challenges

PyTorch

About PyTorch mobile

Setting up the Demo App

YOLOv5 Vision AI

Optimizing the YOLO for the Android App

Setting up the Android App

Results

Conclusion

React native expo tenor search Component

1. `wtmp`: Login and Logout Records

2. `utmp`: Active Users

3. `btmp`: Invalid Login Attempts

Bonus 1: `boot.log`

Bonus 2: `utmpdump`