#api automation framework

[blackjackkent]

Programming object lesson of the day:

A couple days ago, one of the side project apps I run (rpthreadtracker.com) went down for no immediately obvious reason. The issue seems to have ended up being that the backend was running on .NET Core 2.2, which the host was no longer supporting, and I had to do a semi-emergency upgrade of all the code to .NET Core 6, a pretty major update that required a lot of syntactic changes and other fixes.

This is, of course, an obvious lesson in keeping an eye on when your code is using a library out of date enough not to be well supported anymore. (I have some thoughts on whether .NET Core 2.2 is old enough to have been dumped like this, but nevertheless I knew it was going out of LTS and could have been more prepared.) But that's all another post.

What really struck me was how valuable it turned out to be that I had already written an integration test suite for this application.

Historically, at basically every job I've worked for and also on most of my side projects, automated testing tends to be the thing most likely to fall by the wayside. When you have 376428648 things you want to do with an application and only a limited number of hours in the day, getting those 376428648 things to work feels very much like the top priority. You test them manually to make sure they work, and think, yeah, I'll get some tests written at some point, if I have time, but this is fine for now.

And to be honest, most of the time it usually is fine! But a robust test suite is one of those things that you don't need... until you suddenly REALLY FUCKING NEED IT.

RPTT is my baby, my longest running side project, the one with the most users, and the one I've put the most work into. So in a fit of side project passion and wanting to Do All The Right Things For Once, I actively wrote a massive amount of tests for it a few years ago. The backend has a full unit test suite that is approaching 100% coverage (which is a dumb metric you shouldn't actually stress about, but again, a post for another day). I also used Postman, an excellently full-featured API client, to write a battery of integration tests which would hit all of the API endpoints in a defined order, storing variables and verifying values as it went to take a mock user all the way through their usage life cycle.

And goddamn was that useful to have now, years later, as I had to fix a metric fuckton of subtle breakage points while porting the app to the updated framework. With one click, I could send the test suite through every endpoint in the backend and get quick feedback on everywhere that it wasn't behaving exactly the way it behaved before the update. And when I was ready to deploy the updated version, I could do so with solid confidence that from the front end's perspective, nothing would be different and everything would slot correctly into place.

I don't say this at all to shame anyone for not prioritizing writing tests - I usually don't, especially on my side projects, and this was a fortuitous outlier. But it was a really good reminder of why tests are a valuable tool in the first place and why they do deserve to be prioritized when it's possible to do so.

[futureofwebdevwithgenerativeai]

The Evolution of Web Development: A Journey Through the Years

Web development is the work involved in developing a website for the Internet (World Wide Web) or an intranet .

Origin/ Web 1.0:

Tim Berners-Lee created the World Wide Web in 1989 at CERN. The primary goal in the development of the Web was to fulfill the automated information-sharing needs of academics affiliated with institutions and various global organizations. Consequently, HTML was developed in 1993.

Web 2.0:

Web 2.0 introduced increased user engagement and communication. It evolved from the static, read-only nature of Web 1.0 and became an integrated network for engagement and communication. It is often referred to as a user-focused, read-write online network.

Web 3.0:

Web 3.0, considered the third and current version of the web, was introduced in 2014. Web 3.0 aims to turn the web into a sizable, organized database, providing more functionality than traditional search engines.

This evolution transformed static websites into dynamic and responsive platforms, setting the stage for the complex and feature-rich web applications we have today.

Static HTML Pages (1990s)

Introduction of CSS (late 1990s)[13]

JavaScript and Dynamic HTML (1990s - early 2000s)[14][15]

AJAX (1998)[16]

Rise of Content management systems (CMS) (mid-2000s)

Mobile web (late 2000s - 2010s)

Single-page applications (SPAs) and front-end frameworks (2010s)

Server-side javaScript (2010s)

Microservices and API-driven development (2010s - present)

Progressive web apps (PWAs) (2010s - present)

JAMstack Architecture (2010s - present)

WebAssembly (Wasm) (2010s - present)

Serverless computing (2010s - present)

AI and Machine Learning Integration (2010s - present)

Reference:

[elsa16744]

Harnessing the Power of Data Engineering for Modern Enterprises

In the contemporary business landscape, data has emerged as the lifeblood of organizations, fueling innovation, strategic decision-making, and operational efficiency. As businesses generate and collect vast amounts of data, the need for robust data engineering services has become more critical than ever. SG Analytics offers comprehensive data engineering solutions designed to transform raw data into actionable insights, driving business growth and success.

The Importance of Data Engineering

Data engineering is the foundational process that involves designing, building, and managing the infrastructure required to collect, store, and analyze data. It is the backbone of any data-driven enterprise, ensuring that data is clean, accurate, and accessible for analysis. In a world where businesses are inundated with data from various sources, data engineering plays a pivotal role in creating a streamlined and efficient data pipeline.

SG Analytics’ data engineering services are tailored to meet the unique needs of businesses across industries. By leveraging advanced technologies and methodologies, SG Analytics helps organizations build scalable data architectures that support real-time analytics and decision-making. Whether it’s cloud-based data warehouses, data lakes, or data integration platforms, SG Analytics provides end-to-end solutions that enable businesses to harness the full potential of their data.

Building a Robust Data Infrastructure

At the core of SG Analytics’ data engineering services is the ability to build robust data infrastructure that can handle the complexities of modern data environments. This includes the design and implementation of data pipelines that facilitate the smooth flow of data from source to destination. By automating data ingestion, transformation, and loading processes, SG Analytics ensures that data is readily available for analysis, reducing the time to insight.

One of the key challenges businesses face is dealing with the diverse formats and structures of data. SG Analytics excels in data integration, bringing together data from various sources such as databases, APIs, and third-party platforms. This unified approach to data management ensures that businesses have a single source of truth, enabling them to make informed decisions based on accurate and consistent data.

Leveraging Cloud Technologies for Scalability

As businesses grow, so does the volume of data they generate. Traditional on-premise data storage solutions often struggle to keep up with this exponential growth, leading to performance bottlenecks and increased costs. SG Analytics addresses this challenge by leveraging cloud technologies to build scalable data architectures.

Cloud-based data engineering solutions offer several advantages, including scalability, flexibility, and cost-efficiency. SG Analytics helps businesses migrate their data to the cloud, enabling them to scale their data infrastructure in line with their needs. Whether it’s setting up cloud data warehouses or implementing data lakes, SG Analytics ensures that businesses can store and process large volumes of data without compromising on performance.

Ensuring Data Quality and Governance

Inaccurate or incomplete data can lead to poor decision-making and costly mistakes. That’s why data quality and governance are critical components of SG Analytics’ data engineering services. By implementing data validation, cleansing, and enrichment processes, SG Analytics ensures that businesses have access to high-quality data that drives reliable insights.

Data governance is equally important, as it defines the policies and procedures for managing data throughout its lifecycle. SG Analytics helps businesses establish robust data governance frameworks that ensure compliance with regulatory requirements and industry standards. This includes data lineage tracking, access controls, and audit trails, all of which contribute to the security and integrity of data.

Enhancing Data Analytics with Natural Language Processing Services

In today’s data-driven world, businesses are increasingly turning to advanced analytics techniques to extract deeper insights from their data. One such technique is natural language processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language.

SG Analytics offers cutting-edge natural language processing services as part of its data engineering portfolio. By integrating NLP into data pipelines, SG Analytics helps businesses analyze unstructured data, such as text, social media posts, and customer reviews, to uncover hidden patterns and trends. This capability is particularly valuable in industries like healthcare, finance, and retail, where understanding customer sentiment and behavior is crucial for success.

NLP services can be used to automate various tasks, such as sentiment analysis, topic modeling, and entity recognition. For example, a retail business can use NLP to analyze customer feedback and identify common complaints, allowing them to address issues proactively. Similarly, a financial institution can use NLP to analyze market trends and predict future movements, enabling them to make informed investment decisions.

By incorporating NLP into their data engineering services, SG Analytics empowers businesses to go beyond traditional data analysis and unlock the full potential of their data. Whether it’s extracting insights from vast amounts of text data or automating complex tasks, NLP services provide businesses with a competitive edge in the market.

Driving Business Success with Data Engineering

The ultimate goal of data engineering is to drive business success by enabling organizations to make data-driven decisions. SG Analytics’ data engineering services provide businesses with the tools and capabilities they need to achieve this goal. By building robust data infrastructure, ensuring data quality and governance, and leveraging advanced analytics techniques like NLP, SG Analytics helps businesses stay ahead of the competition.

In a rapidly evolving business landscape, the ability to harness the power of data is a key differentiator. With SG Analytics’ data engineering services, businesses can unlock new opportunities, optimize their operations, and achieve sustainable growth. Whether you’re a small startup or a large enterprise, SG Analytics has the expertise and experience to help you navigate the complexities of data engineering and achieve your business objectives.

[nyaza]

(this is a small story of how I came to write my own intrusion detection/prevention framework and why I'm really happy with that decision, don't mind me rambling)

Preface

About two weeks ago I was faced with a pretty annoying problem. Whilst I was going home by train I have noticed that my server at home had been running hot and slowed down a lot. This prompted me to check my nginx logs, the only service that is indirectly available to the public (more on that later), which made me realize that - due to poor access control - someone had been sending me hundreds of thousands of huge DNS requests to my server, most likely testing for vulnerabilities. I added an iptables rule to drop all traffic from the aforementioned source and redirected remaining traffic to a backup NextDNS instance that I set up previously with the same overrides and custom records that my DNS had to not get any downtime for the service but also allow my server to cool down. I stopped the DNS service on my server at home and then used the remaining train ride to think. How would I stop this from happening in the future? I pondered multiple possible solutions for this problem, whether to use fail2ban, whether to just add better access control, or to just stick with the NextDNS instance.

I ended up going with a completely different option: making a solution, that's perfectly fit for my server, myself.

My Server Structure

So, I should probably explain how I host and why only nginx is public despite me hosting a bunch of services under the hood.

I have a public facing VPS that only allows traffic to nginx. That traffic then gets forwarded through a VPN connection to my home server so that I don't have to have any public facing ports on said home server. The VPS only really acts like the public interface for the home server with access control and logging sprinkled in throughout my configs to get more layers of security. Some Services can only be interacted with through the VPN or a local connection, such that not everything is actually forwarded - only what I need/want to be.

I actually do have fail2ban installed on both my VPS and home server, so why make another piece of software?

Tabarnak - Succeeding at Banning

I had a few requirements for what I wanted to do:

Only allow HTTP(S) traffic through Cloudflare

Only allow DNS traffic from given sources; (location filtering, explicit white-/blacklisting);

Webhook support for logging

Should be interactive (e.g. POST /api/ban/{IP})

Detect automated vulnerability scanning

Integration with the AbuseIPDB (for checking and reporting)

As I started working on this, I realized that this would soon become more complex than I had thought at first.

Webhooks for logging This was probably the easiest requirement to check off my list, I just wrote my own log() function that would call a webhook. Sadly, the rest wouldn't be as easy.

Allowing only Cloudflare traffic This was still doable, I only needed to add a filter in my nginx config for my domain to only allow Cloudflare IP ranges and disallow the rest. I ended up doing something slightly different. I added a new default nginx config that would just return a 404 on every route and log access to a different file so that I could detect connection attempts that would be made without Cloudflare and handle them in Tabarnak myself.

Integration with AbuseIPDB Also not yet the hard part, just call AbuseIPDB with the parsed IP and if the abuse confidence score is within a configured threshold, flag the IP, when that happens I receive a notification that asks me whether to whitelist or to ban the IP - I can also do nothing and let everything proceed as it normally would. If the IP gets flagged a configured amount of times, ban the IP unless it has been whitelisted by then.

Location filtering + Whitelist + Blacklist This is where it starts to get interesting. I had to know where the request comes from due to similarities of location of all the real people that would actually connect to the DNS. I didn't want to outright ban everyone else, as there could be valid requests from other sources. So for every new IP that triggers a callback (this would only be triggered after a certain amount of either flags or requests), I now need to get the location. I do this by just calling the ipinfo api and checking the supplied location. To not send too many requests I cache results (even though ipinfo should never be called twice for the same IP - same) and save results to a database. I made my own class that bases from collections.UserDict which when accessed tries to find the entry in memory, if it can't it searches through the DB and returns results. This works for setting, deleting, adding and checking for records. Flags, AbuseIPDB results, whitelist entries and blacklist entries also get stored in the DB to achieve persistent state even when I restart.

Detection of automated vulnerability scanning For this, I went through my old nginx logs, looking to find the least amount of paths I need to block to catch the biggest amount of automated vulnerability scan requests. So I did some data science magic and wrote a route blacklist. It doesn't just end there. Since I know the routes of valid requests that I would be receiving (which are all mentioned in my nginx configs), I could just parse that and match the requested route against that. To achieve this I wrote some really simple regular expressions to extract all location blocks from an nginx config alongside whether that location is absolute (preceded by an =) or relative. After I get the locations I can test the requested route against the valid routes and get back whether the request was made to a valid URL (I can't just look for 404 return codes here, because there are some pages that actually do return a 404 and can return a 404 on purpose). I also parse the request method from the logs and match the received method against the HTTP standard request methods (which are all methods that services on my server use). That way I can easily catch requests like:

XX.YYY.ZZZ.AA - - [25/Sep/2023:14:52:43 +0200] "145.ll|'|'|SGFjS2VkX0Q0OTkwNjI3|'|'|WIN-JNAPIER0859|'|'|JNapier|'|'|19-02-01|'|'||'|'|Win 7 Professional SP1 x64|'|'|No|'|'|0.7d|'|'|..|'|'|AA==|'|'|112.inf|'|'|SGFjS2VkDQoxOTIuMTY4LjkyLjIyMjo1NTUyDQpEZXNrdG9wDQpjbGllbnRhLmV4ZQ0KRmFsc2UNCkZhbHNlDQpUcnVlDQpGYWxzZQ==12.act|'|'|AA==" 400 150 "-" "-"

I probably over complicated this - by a lot - but I can't go back in time to change what I did.

Interactivity As I showed and mentioned earlier, I can manually white-/blacklist an IP. This forced me to add threads to my previously single-threaded program. Since I was too stubborn to use websockets (I have a distaste for websockets), I opted for probably the worst option I could've taken. It works like this: I have a main thread, which does all the log parsing, processing and handling and a side thread which watches a FIFO-file that is created on startup. I can append commands to the FIFO-file which are mapped to the functions they are supposed to call. When the FIFO reader detects a new line, it looks through the map, gets the function and executes it on the supplied IP. Doing all of this manually would be way too tedious, so I made an API endpoint on my home server that would append the commands to the file on the VPS. That also means, that I had to secure that API endpoint so that I couldn't just be spammed with random requests. Now that I could interact with Tabarnak through an API, I needed to make this user friendly - even I don't like to curl and sign my requests manually. So I integrated logging to my self-hosted instance of https://ntfy.sh and added action buttons that would send the request for me. All of this just because I refused to use sockets.

First successes and why I'm happy about this After not too long, the bans were starting to happen. The traffic to my server decreased and I can finally breathe again. I may have over complicated this, but I don't mind. This was a really fun experience to write something new and learn more about log parsing and processing. Tabarnak probably won't last forever and I could replace it with solutions that are way easier to deploy and way more general. But what matters is, that I liked doing it. It was a really fun project - which is why I'm writing this - and I'm glad that I ended up doing this. Of course I could have just used fail2ban but I never would've been able to write all of the extras that I ended up making (I don't want to take the explanation ad absurdum so just imagine that I added cool stuff) and I never would've learned what I actually did.

So whenever you are faced with a dumb problem and could write something yourself, I think you should at least try. This was a really fun experience and it might be for you as well.

Post Scriptum

First of all, apologies for the English - I'm not a native speaker so I'm sorry if some parts were incorrect or anything like that. Secondly, I'm sure that there are simpler ways to accomplish what I did here, however this was more about the experience of creating something myself rather than using some pre-made tool that does everything I want to (maybe even better?). Third, if you actually read until here, thanks for reading - hope it wasn't too boring - have a nice day :)

[mercyjuliet1512]

From Beginner to Pro: Dominate Automated Testing with Our Selenium Course

Welcome to our comprehensive Selenium course designed to help individuals from all backgrounds, whether novice or experienced, enhance their automated testing skills and become proficient in Selenium. In this article, we will delve into the world of Selenium, an open-source automated testing framework that has revolutionized software testing. With our course, we aim to empower aspiring professionals with the knowledge and techniques necessary to excel in the field of automated testing.

Why Choose Selenium?

Selenium offers a wide array of features and capabilities that make it the go-to choice for automated testing in the IT industry.

It allows testers to write test scripts in multiple programming languages, including Java, Python, C#, and more, ensuring flexibility and compatibility with various project requirements.

Selenium’s compatibility with different web browsers such as Chrome, Firefox, Safari, and Internet Explorer makes it a versatile choice for testing web applications.

The ability to leverage Selenium WebDriver, which provides a simple and powerful API, allows for seamless interaction with web elements, making automating tasks easier than ever before.

Selenium’s Key Components:

Selenium IDE:

Selenium Integrated Development Environment (IDE) is a Firefox plugin primarily used for recording and playing back test cases. It offers a user-friendly interface, allowing even non-programmers to create basic tests effortlessly.

Although Selenium IDE is a valuable tool for beginners, our course primarily focuses on Selenium WebDriver due to its advanced capabilities and wider scope.

Selenium WebDriver:

Selenium WebDriver is the most critical component of the Selenium framework. It provides a programming interface to interact with web elements and perform actions programmatically.

WebDriver’s functionality extends beyond just browser automation; it also enables testers to handle alerts, pop-ups, frames, and handle various other web application interactions.

Our Selenium course places significant emphasis on WebDriver, equipping learners with the skills to automate complex test scenarios efficiently.

Selenium Grid:

Selenium Grid empowers testers by allowing them to execute tests on multiple machines and browsers simultaneously, making it an essential component for testing scalability and cross-browser compatibility.

Through our Selenium course, you’ll gain a deep understanding of Selenium Grid and learn how to harness its capabilities effectively.

The Benefits of Our Selenium Course

Comprehensive Curriculum: Our course is designed to cover everything from the fundamentals of automated testing to advanced techniques in Selenium, ensuring learners receive a well-rounded education.

Hands-on Experience: Practical exercises and real-world examples are incorporated to provide learners with the opportunity to apply their knowledge in a realistic setting.

Expert Instruction: You’ll be guided by experienced instructors who have a profound understanding of Selenium and its application in the industry, ensuring you receive the best possible education.

Flexibility: Our course offers flexible learning options, allowing you to study at your own pace and convenience, ensuring a stress-free learning experience.

Industry Recognition: Completion of our Selenium course will provide you with a valuable certification recognized by employers worldwide, enhancing your career prospects within the IT industry.

Who Should Enroll?

Novice Testers: If you’re new to the world of automated testing and aspire to become proficient in Selenium, our course is designed specifically for you. We’ll lay a strong foundation and gradually guide you towards becoming a pro in Selenium automation.

Experienced Testers: Even if you already have experience in automated testing, our course will help you enhance your skills and keep up with the latest trends and best practices in Selenium.

IT Professionals: Individuals working in the IT industry, such as developers or quality assurance engineers, who want to broaden their skillset and optimize their testing processes, will greatly benefit from our Selenium course.

In conclusion, our Selenium course is a one-stop solution for individuals seeking to dominate automated testing and excel in their careers. With a comprehensive curriculum, hands-on experience, expert instruction, and industry recognition, you’ll be well-prepared to tackle any automated testing challenges that come your way. Make the smart choice and enroll in our Selenium course at ACTE Technologies today to unlock your full potential in the world of software testing.

[apptagsolution]

Exploring Essential Laravel Development Tools for Building Powerful Web Applications

Laravel has emerged as one of the most popular PHP frameworks, providing builders a sturdy and green platform for building net packages. Central to the fulfillment of Laravel tasks are the development tools that streamline the improvement process, decorate productiveness, and make certain code quality. In this article, we will delve into the best Laravel development tools that each developer should be acquainted with.

1  Composer: Composer is a dependency manager for PHP that allows you to declare the libraries your project relies upon on and manages them for you. Laravel itself relies closely on Composer for package deal management, making it an essential device for Laravel builders. With Composer, you may without problems upload, eliminate, or update applications, making sure that your Laravel project stays up-to-date with the present day dependencies.

2  Artisan: Artisan is the command-line interface blanketed with Laravel, presenting various helpful instructions for scaffolding, handling migrations, producing controllers, models, and plenty extra. Laravel builders leverage Artisan to automate repetitive tasks and streamline improvement workflows, thereby growing efficiency and productiveness.

3  Laravel Debugbar: Debugging is an crucial component of software program development, and Laravel Debugbar simplifies the debugging procedure by using supplying exact insights into the application's overall performance, queries, views, and greater. It's a accessible device for identifying and resolving problems all through improvement, making sure the clean functioning of your Laravel application.

4  Laravel Telescope: Similar to Laravel Debugbar, Laravel Telescope is a debugging assistant for Laravel programs, presenting actual-time insights into requests, exceptions, database queries, and greater. With its intuitive dashboard, developers can monitor the software's behavior, pick out performance bottlenecks, and optimize hence.

5  Laravel Mix: Laravel Mix offers a fluent API for outlining webpack build steps on your Laravel application. It simplifies asset compilation and preprocessing duties together with compiling SASS or LESS documents, concatenating and minifying JavaScript documents, and dealing with versioning. Laravel Mix significantly streamlines the frontend improvement procedure, permitting builders to attention on building notable consumer reviews.

6  Laravel Horizon: Laravel Horizon is a dashboard and configuration system for Laravel's Redis queue, imparting insights into process throughput, runtime metrics, and more. It enables builders to monitor and control queued jobs efficiently, ensuring most beneficial performance and scalability for Laravel programs that leverage history processing.

7  Laravel Envoyer: Laravel Envoyer is a deployment tool designed specifically for Laravel packages, facilitating seamless deployment workflows with 0 downtime. It automates the deployment process, from pushing code adjustments to more than one servers to executing deployment scripts, thereby minimizing the chance of errors and ensuring smooth deployments.

8  Laravel Dusk: Laravel Dusk is an cease-to-give up browser testing tool for Laravel applications, built on pinnacle of the ChromeDriver and WebDriverIO. It lets in builders to put in writing expressive and dependable browser assessments, making sure that critical user interactions and workflows function as expected across exceptional browsers and environments.

9  Laravel Valet: Laravel Valet gives a light-weight improvement surroundings for Laravel applications on macOS, offering seamless integration with equipment like MySQL, NGINX, and PHP. It simplifies the setup process, permitting developers to consciousness on writing code instead of configuring their development environment.

In end, mastering the vital Laravel development tools noted above is important for building robust, green, and scalable internet packages with Laravel. Whether it's handling dependencies, debugging troubles, optimizing overall performance, or streamlining deployment workflows, those equipment empower Laravel developers to supply outstanding answers that meet the demands of current internet development. Embracing these gear will certainly increase your Laravel improvement enjoy and accelerate your journey toward turning into a talented Laravel developer.

[nividawebsolutions]

20 Best Android Development Practices in 2023

Introduction: 

In today's competitive market, creating high-quality Android applications requires adherence to best development practices.  Android app development agencies in Vadodara (Gujarat, India) like Nivida Web Solutions Pvt. Ltd., play a crucial role in delivering exceptional applications.  This article presents the 20 best Android development practices to follow in 2023, ensuring the success of your app development projects.

1.     Define Clear Objectives:

Begin by defining clear objectives for your Android app development project.  Identify the target audience, the app's purpose, and the specific goals you aim to achieve.  This clarity will guide the development process and result in a more focused and effective application.

 2. Embrace the Material Design Guidelines:

Google's Material Design guidelines provide a comprehensive set of principles and guidelines for designing visually appealing and intuitive Android applications.  Adhering to these guidelines ensures consistency, enhances usability, and delivers an optimal user experience.

 3. Optimize App Performance:

Performance optimization is crucial for user satisfaction.  Focus on optimizing app loading times, minimizing network requests, and implementing efficient caching mechanisms.  Profiling tools like Android Profiler can help identify performance bottlenecks and improve overall app responsiveness.

 4. Follow a Modular Approach:

Adopting a modular approach allows for easier maintenance, scalability, and code reusability.  Breaking down your app into smaller, manageable modules promotes faster development, reduces dependencies, and enhances collaboration among developers.

 5. Implement Responsive UI Designs:

Designing a responsive user interface (UI) ensures that your app adapts seamlessly to various screen sizes and orientations.  Utilize Android’s resources, such as ConstraintLayout, to create dynamic and adaptive UIs that provide a consistent experience across different devices.

 6. Prioritize Security:

Android app security is of paramount importance.  Employ secure coding practices, authenticate user inputs, encrypt sensitive data, and regularly update libraries and dependencies to protect your app against vulnerabilities and potential attacks.

 7. Opt for Kotlin as the Preferred Language:

Kotlin has gained immense popularity among Android developers due to its conciseness, null safety, and enhanced interoperability with existing Java code.  Embrace Kotlin as the primary programming language for your Android app development projects to leverage its modern features and developer-friendly syntax.

 8. Conduct Thorough Testing:

Testing is crucial to ensure the reliability and stability of your Android applications.  Employ a combination of unit testing, integration testing, and automated UI testing using frameworks like Espresso to catch bugs early and deliver a robust app to your users.

 9. Optimize Battery Consumption:

Battery life is a significant concern for Android users.  Optimize your app's battery consumption by minimizing background processes, reducing network requests, and implementing efficient power management techniques.  Android's Battery Optimization APIs can help streamline power usage.

 10. Implement Continuous Integration and Delivery (CI/CD):

Adopting CI/CD practices facilitates frequent code integration, automated testing, and seamless deployment. Tools like Jenkins and Bitrise enable developers to automate build processes, run tests, and deploy app updates efficiently, resulting in faster time-to-market and improved quality.

 11. Leverage Cloud Technologies:

Integrating cloud technologies, such as cloud storage and backend services, can enhance your app's scalability, performance, and reliability.  Services like Firebase offer powerful tools for authentication, database management, push notifications, and analytics.

 12. Ensure Accessibility:

Make your Android app accessible to users with disabilities by adhering to accessibility guidelines.  Provide alternative text for images, support screen readers, and use colour contrast appropriately to ensure inclusivity and a positive user experience for all users.

 13. Optimize App Size:

Large app sizes can deter users from downloading and installing your application.  Optimize your app's size by eliminating unused resources, compressing images, and utilizing Android App Bundles to deliver optimized APKs based on device configurations.

 14. Implement Offline Support:

Provide offline capabilities in your app to ensure users can access essential features and content even when offline.  Implement local caching, synchronize data in the background, and notify users of limited or no connectivity to deliver a seamless user experience.

 15. Implement Analytics and Crash Reporting:

Integrate analytics and crash reporting tools, such as Google Analytics and Firebase Crashlytics, to gain insights into user behaviour, identify areas for improvement, and address crashes promptly. This data-driven approach helps in refining your app's performance and user engagement.

 16. Keep Up with Android OS Updates:

Stay up to date with the latest Android OS updates, new APIs, and platform features.  Regularly update your app to leverage new functionalities, enhance performance, and ensure compatibility with newer devices.

 17. Provide Localized Versions:

Cater to a global audience by providing localized versions of your app.  Translate your app's content, user interface, and notifications into different languages to expand your user base and increase user engagement.

 18. Ensure App Store Optimization (ASO):

Optimize your app's visibility and discoverability in the Google Play Store by utilizing appropriate keywords, engaging app descriptions, compelling screenshots, and positive user reviews.  ASO techniques can significantly impact your app's download and conversion rates.

 19. Follow Privacy Regulations and Guidelines:

Adhere to privacy regulations, such as GDPR and CCPA, and ensure transparent data handling practices within your app. Obtain user consent for data collection, storage, and usage, and provide clear privacy policies to establish trust with your users.

 20. Regularly Update and Maintain Your App:

Continuously monitor user feedback, track app performance metrics, and release regular updates to address bugs, introduce new features, and enhance user experience.  Regular maintenance ensures that your app remains relevant, competitive, and secure.

 Conclusion:

 Adopting these 20 best Android development practices in 2023 will help Android app development companies in India, create exceptional applications.  By focusing on objectives, embracing Material Design, optimizing performance, and following modern development approaches, your Android apps will stand out in the market, delight users, and achieve long-term success.  Also by partnering with an Android App Development Company in India (Gujarat, Vadodara) you can leverage their expertise.

[mindyourtopics44]

25 Python Projects to Supercharge Your Job Search in 2024

Introduction: In the competitive world of technology, a strong portfolio of practical projects can make all the difference in landing your dream job. As a Python enthusiast, building a diverse range of projects not only showcases your skills but also demonstrates your ability to tackle real-world challenges. In this blog post, we'll explore 25 Python projects that can help you stand out and secure that coveted position in 2024.

1. Personal Portfolio Website

Create a dynamic portfolio website that highlights your skills, projects, and resume. Showcase your creativity and design skills to make a lasting impression.

2. Blog with User Authentication

Build a fully functional blog with features like user authentication and comments. This project demonstrates your understanding of web development and security.

3. E-Commerce Site

Develop a simple online store with product listings, shopping cart functionality, and a secure checkout process. Showcase your skills in building robust web applications.

4. Predictive Modeling

Create a predictive model for a relevant field, such as stock prices, weather forecasts, or sales predictions. Showcase your data science and machine learning prowess.

5. Natural Language Processing (NLP)

Build a sentiment analysis tool or a text summarizer using NLP techniques. Highlight your skills in processing and understanding human language.

6. Image Recognition

Develop an image recognition system capable of classifying objects. Demonstrate your proficiency in computer vision and deep learning.

7. Automation Scripts

Write scripts to automate repetitive tasks, such as file organization, data cleaning, or downloading files from the internet. Showcase your ability to improve efficiency through automation.

8. Web Scraping

Create a web scraper to extract data from websites. This project highlights your skills in data extraction and manipulation.

9. Pygame-based Game

Develop a simple game using Pygame or any other Python game library. Showcase your creativity and game development skills.

10. Text-based Adventure Game

Build a text-based adventure game or a quiz application. This project demonstrates your ability to create engaging user experiences.

11. RESTful API

Create a RESTful API for a service or application using Flask or Django. Highlight your skills in API development and integration.

12. Integration with External APIs

Develop a project that interacts with external APIs, such as social media platforms or weather services. Showcase your ability to integrate diverse systems.

13. Home Automation System

Build a home automation system using IoT concepts. Demonstrate your understanding of connecting devices and creating smart environments.

14. Weather Station

Create a weather station that collects and displays data from various sensors. Showcase your skills in data acquisition and analysis.

15. Distributed Chat Application

Build a distributed chat application using a messaging protocol like MQTT. Highlight your skills in distributed systems.

16. Blockchain or Cryptocurrency Tracker

Develop a simple blockchain or a cryptocurrency tracker. Showcase your understanding of blockchain technology.

17. Open Source Contributions

Contribute to open source projects on platforms like GitHub. Demonstrate your collaboration and teamwork skills.

18. Network or Vulnerability Scanner

Build a network or vulnerability scanner to showcase your skills in cybersecurity.

19. Decentralized Application (DApp)

Create a decentralized application using a blockchain platform like Ethereum. Showcase your skills in developing applications on decentralized networks.

20. Machine Learning Model Deployment

Deploy a machine learning model as a web service using frameworks like Flask or FastAPI. Demonstrate your skills in model deployment and integration.

21. Financial Calculator

Build a financial calculator that incorporates relevant mathematical and financial concepts. Showcase your ability to create practical tools.

22. Command-Line Tools

Develop command-line tools for tasks like file manipulation, data processing, or system monitoring. Highlight your skills in creating efficient and user-friendly command-line applications.

23. IoT-Based Health Monitoring System

Create an IoT-based health monitoring system that collects and analyzes health-related data. Showcase your ability to work on projects with social impact.

24. Facial Recognition System

Build a facial recognition system using Python and computer vision libraries. Showcase your skills in biometric technology.

25. Social Media Dashboard

Develop a social media dashboard that aggregates and displays data from various platforms. Highlight your skills in data visualization and integration.

Conclusion: As you embark on your job search in 2024, remember that a well-rounded portfolio is key to showcasing your skills and standing out from the crowd. These 25 Python projects cover a diverse range of domains, allowing you to tailor your portfolio to match your interests and the specific requirements of your dream job.

If you want to know more, Click here:https://analyticsjobs.in/question/what-are-the-best-python-projects-to-land-a-great-job-in-2024/

[js-developer]

Exploring the Powerhouse: 30 Must-Know JavaScript Libraries and Frameworks for Web Development

React.js: A declarative, efficient, and flexible JavaScript library for building user interfaces.

Angular.js (Angular): A web application framework maintained by Google, used for building dynamic, single-page web applications.

Vue.js: A progressive JavaScript framework for building user interfaces. It is incrementally adaptable and can be integrated into other projects.

Node.js: A JavaScript runtime built on Chrome's V8 JavaScript engine that enables server-side JavaScript development.

Express.js: A web application framework for Node.js that simplifies the process of building web applications.

jQuery: A fast, small, and feature-rich JavaScript library that simplifies HTML document traversal and manipulation, event handling, and animation.

D3.js: A powerful library for creating data visualizations using HTML, SVG, and CSS.

Three.js: A cross-browser JavaScript library and application programming interface (API) used to create and display animated 3D computer graphics in a web browser.

Redux: A predictable state container for JavaScript apps, often used with React for managing the state of the application.

Next.js: A React framework for building server-side rendered and statically generated web applications.

Svelte: A radical new approach to building user interfaces. It shifts the work from the browser to the build step, resulting in smaller, faster applications.

Electron: A framework for building cross-platform desktop applications using web technologies such as HTML, CSS, and JavaScript.

RxJS: A library for reactive programming using Observables, making it easier to compose asynchronous or callback-based code.

Webpack: A module bundler for JavaScript applications. It takes modules with dependencies and generates static assets representing those modules.

Babel: A JavaScript compiler that allows developers to use the latest ECMAScript features by transforming them into browser-compatible JavaScript.

Jest: A JavaScript testing framework designed to ensure the correctness of your code.

Mocha: A feature-rich JavaScript test framework running on Node.js and in the browser.

Chai: A BDD/TDD assertion library for Node.js and the browser that can be paired with any testing framework.

Lodash: A modern JavaScript utility library delivering modularity, performance, and extras.

Socket.io: A library that enables real-time, bidirectional, and event-based communication between web clients and servers.

GraphQL: A query language for APIs and a runtime for executing those queries with your existing data.

Axios: A promise-based HTTP client for the browser and Node.js, making it easy to send asynchronous HTTP requests.

Jasmine: A behavior-driven development framework for testing JavaScript code.

Meteor.js: A full-stack JavaScript platform for developing modern web and mobile applications.

Gatsby.js: A modern website framework that builds performance into every website by leveraging the latest web technologies.

Chart.js: A simple yet flexible JavaScript charting library for designers and developers.

Ember.js: A JavaScript framework for building web applications, with a focus on productivity and convention over configuration.

Nuxt.js: A framework for creating Vue.js applications with server-side rendering and routing.

Grunt: A JavaScript task runner that automates common tasks in the development process.

Sass (Syntactically Awesome Stylesheets): A CSS preprocessor that helps you write maintainable, scalable, and modular styles.

Remember to check each library or framework's documentation and community support for the latest information and updates.

[yethiconsulting]

Building Robust API Test Suites with the Best Automation Frameworks

Introduction

Introduce the role of robust API test suites in maintaining the functionality, reliability, and performance of modern applications. Emphasize the importance of selecting the right automation framework to build these test suites effectively.

Selecting the Right Framework

Discuss the criteria for choosing an API automation framework, such as ease of use, compatibility with protocols (REST, SOAP, GraphQL), and integration with CI/CD pipelines. Mention popular frameworks like Postman, RestAssured, and Karate.

Structuring Test Suites for Maintainability

Explain how a well-structured API test suite can reduce maintenance overhead. Discuss best practices for organizing tests, such as grouping tests by functionality, and using reusable components (like request templates and utility functions).

Coverage and Depth of Testing

Highlight the need for comprehensive coverage, including functional testing, error handling, and edge cases. Point out how API automation frameworks should allow testing of different request methods (GET, POST, PUT, DELETE) and support for data-driven testing.

Parallel Execution for Scalability

Explore the importance of frameworks that support parallel execution, enabling faster test runs across multiple environments and API endpoints, which is critical for large-scale systems.

Conclusion

Summarize the key steps to building robust API test suites and how using the best automation frameworks enhances the overall development process and quality assurance.

[shemsuji432]

Demystifying Python: Exploring 7 Exciting Capabilities of This Coding Marvel

Greetings aspiring coders! Are you ready to unravel the wonders of Python programming? If you're curious about the diverse possibilities that Python offers, you're in for a treat. Let's delve into seven captivating things you can achieve with Python, explained in simple terms from the best Python Training Institute.

1. Craft Dynamic Websites:

Python serves as the backbone for numerous websites you encounter daily. Utilizing robust frameworks such as Django and Flask, you can effortlessly fashion web applications and dynamic websites. Whether your ambition is to launch a personal blog or the next big social platform, Python is your reliable companion. If you want to learn more about Python from the Beginner to Advance level, I will highly recommend the best Python course in Bangalore

2. Automate Mundane Tasks:

Say goodbye to repetitive tasks! Python comes to the rescue with its automation prowess. From organizing files to sending emails and even extracting information from websites, Python's straightforward approach empowers your computer to handle these tasks autonomously.

3. Master Data Analysis:

For those who revel in manipulating numbers and data, Python is a game-changer. Libraries like NumPy, Pandas, and Matplotlib transform data analysis into an enjoyable and accessible endeavor. Visualize data, discern patterns, and unlock the full potential of your datasets.

4. Embark on Game Development:

Surprising as it may be, Python allows you to dip your toes into the realm of game development. Thanks to libraries like Pygame, you can bring your gaming ideas to life. While you may not be creating the next AAA blockbuster, Python provides an excellent starting point for game development enthusiasts.

5. Explore Artificial Intelligence:

Python stands out as a juggernaut in the field of artificial intelligence. Leveraging libraries such as TensorFlow and PyTorch, you can construct machine learning models. Teach your computer to recognize images, comprehend natural language, and even engage in gaming – the possibilities are limitless.

6. Craft Mobile Applications:

Yes, you read that correctly. Python empowers you to develop mobile applications through frameworks like Kivy and BeeWare. Now, you can turn your app concepts into reality without the need to learn an entirely new language for each platform.

7. Mastery in Network Programming:

Python emerges as your ally in the realm of networking. Whether you aspire to create network tools, collaborate with APIs, or automate network configurations, Python simplifies the intricacies of networking.

In essence, Python can be likened to a versatile Swiss Army knife for programmers. It's approachable for beginners, flexible, and applicable across diverse domains. Whether you're drawn to web development, data science, or AI, Python stands as the ideal companion for your coding journey. So, grab your keyboard, start coding, and witness the magic of Python unfold!

[digvijay00]

Unveiling the Ultimate Handbook for Aspiring Full Stack Developers

In the ever-evolving realm of technology, the role of a full-stack developer has undeniably gained prominence. Full-stack developers epitomize versatility and are an indispensable asset to any enterprise or endeavor. They wield a comprehensive array of competencies that empower them to navigate the intricate landscape of both front-end and back-end web development. In this exhaustive compendium, we shall delve into the intricacies of transforming into a proficient full-stack developer, dissecting the requisite skills, indispensable tools, and strategies for excellence in this domain.

Deciphering the Full Stack Developer Persona

A full-stack developer stands as a connoisseur of both front-end and back-end web development. Their mastery extends across the entire spectrum of web development, rendering them highly coveted entities within the tech sector. The front end of a website is the facet accessible to users, while the back end operates stealthily behind the scenes, handling the intricacies of databases and server management. You can learn it from Uncodemy which is the Best Full stack Developer Institute in Delhi.

The Requisite Competencies

To embark on a successful journey as a full-stack developer, one must amass a diverse skill set. These proficiencies can be broadly categorized into front-end and back-end development, coupled with other quintessential talents:

Front-End Development

Markup Linguistics and Style Sheets: Cultivating an in-depth grasp of markup linguistics and style sheets like HTML and CSS is fundamental to crafting visually captivating and responsive user interfaces.

JavaScript Mastery: JavaScript constitutes the linchpin of front-end development. Proficiency in this language is the linchpin for crafting dynamic web applications.

Frameworks and Libraries: Familiarization with popular front-end frameworks and libraries such as React, Angular, and Vue.js is indispensable as they streamline the development process and elevate the user experience.

Back-End Development

Server-Side Linguistics: Proficiency in server-side languages like Node.js, Python, Ruby, or Java is imperative as these languages fuel the back-end functionalities of websites.

Database Dexterity: Acquiring proficiency in the manipulation of databases, including SQL and NoSQL variants like MySQL, PostgreSQL, and MongoDB, is paramount.

API Expertise: Comprehending the creation and consumption of APIs is essential, serving as the conduit for data interchange between the front-end and back-end facets.

Supplementary Competencies

Version Control Proficiency: Mastery in version control systems such as Git assumes monumental significance for collaborative code management.

Embracing DevOps: Familiarity with DevOps practices is instrumental in automating and streamlining the development and deployment processes.

Problem-Solving Prowess: Full-stack developers necessitate robust problem-solving acumen to diagnose issues and optimize code for enhanced efficiency.

The Instruments of the Craft

Full-stack developers wield an arsenal of tools and technologies to conceive, validate, and deploy web applications. The following are indispensable tools that merit assimilation:

Integrated Development Environments (IDEs)

Visual Studio Code: This open-source code editor, hailed for its customizability, enjoys widespread adoption within the development fraternity.

Sublime Text: A lightweight and efficient code editor replete with an extensive repository of extensions.

Version Control

Git: As the preeminent version control system, Git is indispensable for tracking code modifications and facilitating collaborative efforts.

GitHub: A web-based platform dedicated to hosting Git repositories and fostering collaboration among developers.

Front-End Frameworks

React A potent JavaScript library for crafting user interfaces with finesse.

Angular: A comprehensive front-end framework catering to the construction of dynamic web applications.

Back-End Technologies

Node.js: A favored server-side runtime that facilitates the development of scalable, high-performance applications.

Express.js: A web application framework tailor-made for Node.js, simplifying back-end development endeavors.

Databases

MongoDB: A NoSQL database perfectly suited for managing copious amounts of unstructured data.

PostgreSQL: A potent open-source relational database management system.

Elevating Your Proficiency as a Full-Stack Developer

True excellence as a full-stack developer transcends mere technical acumen. Here are some strategies to help you distinguish yourself in this competitive sphere:

Continual Learning: Given the rapid evolution of technology, it's imperative to remain abreast of the latest trends and tools.

Embark on Personal Projects: Forge your path by creating bespoke web applications to showcase your skills and amass a portfolio.

Collaboration and Networking: Participation in developer communities, attendance at conferences, and collaborative ventures with fellow professionals are key to growth.

A Problem-Solving Mindset: Cultivate a robust ability to navigate complex challenges and optimize code for enhanced efficiency.

Embracing Soft Skills: Effective communication, collaborative teamwork, and adaptability are indispensable in a professional milieu.

In Closing

Becoming a full-stack developer is a gratifying odyssey that demands unwavering dedication and a resolute commitment to perpetual learning. Armed with the right skill set, tools, and mindset, one can truly shine in this dynamic domain. Full-stack developers are in high demand, and as you embark on this voyage, you'll discover a plethora of opportunities beckoning you.

So, if you aspire to join the echelons of full-stack developers and etch your name in the annals of the tech world, commence your journey by honing your skills and laying a robust foundation in both front-end and back-end development. Your odyssey to becoming an adept full-stack developer commences now.

[jcmarchi]

Generative AI, innovation, creativity & what the future might hold - CyberTalk

New Post has been published on https://thedigitalinsider.com/generative-ai-innovation-creativity-what-the-future-might-hold-cybertalk/

Generative AI, innovation, creativity & what the future might hold - CyberTalk

Stephen M. Walker II is CEO and Co-founder of Klu, an LLM App Platform. Prior to founding Klu, Stephen held product leadership roles Productboard, Amazon, and Capital One.

Are you excited about empowering organizations to leverage AI for innovative endeavors? So is Stephen M. Walker II, CEO and Co-Founder of the company Klu, whose cutting-edge LLM platform empowers users to customize generative AI systems in accordance with unique organizational needs, resulting in transformative opportunities and potential.

In this interview, Stephen not only discusses his innovative vertical SaaS platform, but also addresses artificial intelligence, generative AI, innovation, creativity and culture more broadly. Want to see where generative AI is headed? Get perspectives that can inform your viewpoint, and help you pave the way for a successful 2024. Stay current. Keep reading.

Please share a bit about the Klu story:

We started Klu after seeing how capable the early versions of OpenAI’s GPT-3 were when it came to common busy-work tasks related to HR and project management. We began building a vertical SaaS product, but needed tools to launch new AI-powered features, experiment with them, track changes, and optimize the functionality as new models became available. Today, Klu is actually our internal tools turned into an app platform for anyone building their own generative features.

What kinds of challenges can Klu help solve for users?

Building an AI-powered feature that connects to an API is pretty easy, but maintaining that over time and understanding what’s working for your users takes months of extra functionality to build out. We make it possible for our users to build their own version of ChatGPT, built on their internal documents or data, in minutes.

What is your vision for the company?

The founding insight that we have is that there’s a lot of busy work that happens in companies and software today. I believe that over the next few years, you will see each company form AI teams, responsible for the internal and external features that automate this busy work away.

I’ll give you a good example for managers: Today, if you’re a senior manager or director, you likely have two layers of employees. During performance management cycles, you have to read feedback for each employee and piece together their strengths and areas for improvement. What if, instead, you received a briefing for each employee with these already synthesized and direct quotes from their peers? Now think about all of the other tasks in business that take several hours and that most people dread. We are building the tools for every company to easily solve this and bring AI into their organization.

Please share a bit about the technology behind the product:

In many ways, Klu is not that different from most other modern digital products. We’re built on cloud providers, use open source frameworks like Nextjs for our app, and have a mix of Typescript and Python services. But with AI, what’s unique is the need to lower latency, manage vector data, and connect to different AI models for different tasks. We built on Supabase using Pgvector to build our own vector storage solution. We support all major LLM providers, but we partnered with Microsoft Azure to build a global network of embedding models (Ada) and generative models (GPT-4), and use Cloudflare edge workers to deliver the fastest experience.

What innovative features or approaches have you introduced to improve user experiences/address industry challenges?

One of the biggest challenges in building AI apps is managing changes to your LLM prompts over time. The smallest changes might break for some users or introduce new and problematic edge cases. We’ve created a system similar to Git in order to track version changes, and we use proprietary AI models to review the changes and alert our customers if they’re making breaking changes. This concept isn’t novel for traditional developers, but I believe we’re the first to bring these concepts to AI engineers.

How does Klu strive to keep LLMs secure?

Cyber security is paramount at Klu. From day one, we created our policies and system monitoring for SOC2 auditors. It’s crucial for us to be a trusted partner for our customers, but it’s also top of mind for many enterprise customers. We also have a data privacy agreement with Azure, which allows us to offer GDPR-compliant versions of the OpenAI models to our customers. And finally, we offer customers the ability to redact PII from prompts so that this data is never sent to third-party models.

Internally we have pentest hackathons to understand where things break and to proactively understand potential threats. We use classic tools like Metasploit and Nmap, but the most interesting results have been finding ways to mitigate unintentional denial of service attacks. We proactively test what happens when we hit endpoints with hundreds of parallel requests per second.

What are your perspectives on the future of LLMs (predictions for 2024)?

This (2024) will be the year for multi-modal frontier models. A frontier model is just a foundational model that is leading the state of the art for what is possible. OpenAI will roll out GPT-4 Vision API access later this year and we anticipate this exploding in usage next year, along with competitive offerings from other leading AI labs. If you want to preview what will be possible, ChatGPT Pro and Enterprise customers have access to this feature in the app today.

Early this year, I heard leaders worried about hallucinations, privacy, and cost. At Klu and across the LLM industry, we found solutions for this and we continue to see a trend of LLMs becoming cheaper and more capable each year. I always talk to our customers about not letting these stop your innovation today. Start small, and find the value you can bring to your customers. Find out if you have hallucination issues, and if you do, work on prompt engineering, retrieval, and fine-tuning with your data to reduce this. You can test these new innovations with engaged customers that are ok with beta features, but will greatly benefit from what you are offering them. Once you have found market fit, you have many options for improving privacy and reducing costs at scale – but I would not worry about that in the beginning, it’s premature optimization.

LLMs introduce a new capability into the product portfolio, but it’s also an additional system to manage, monitor, and secure. Unlike other software in your portfolio, LLMs are not deterministic, and this is a mindset shift for everyone. The most important thing for CSOs is to have a strategy for enabling their organization’s innovation. Just like any other software system, we are starting to see the equivalent of buffer exploits, and expect that these systems will need to be monitored and secured if connected to data that is more important than help documentation.

Your thoughts on LLMs, AI and creativity?

Personally, I’ve had so much fun with GenAI, including image, video, and audio models. I think the best way to think about this is that the models are better than the average person. For me, I’m below average at drawing or creating animations, but I’m above average when it comes to writing. This means I can have creative ideas for an image, the model will bring these to life in seconds, and I am very impressed. But for writing, I’m often frustrated with the boring ideas, although it helps me find blind spots in my overall narrative. The reason for this is that LLMs are just bundles of math finding the most probable answer to the prompt. Human creativity —from the arts, to business, to science— typically comes from the novel combinations of ideas, something that is very difficult for LLMs to do today. I believe the best way to think about this is that the employees who adopt AI will be more productive and creative— the LLM removes their potential weaknesses, and works like a sparring partner when brainstorming.

You and Sam Altman agree on the idea of rethinking the global economy. Say more?

Generative AI greatly changes worker productivity, including the full automation of many tasks that you would typically hire more people to handle as a business scales. The easiest way to think about this is to look at what tasks or jobs a company currently outsources to agencies or vendors, especially ones in developing nations where skill requirements and costs are lower. Over this coming decade you will see work that used to be outsourced to global labor markets move to AI and move under the supervision of employees at an organization’s HQ.

As the models improve, workers will become more productive, meaning that businesses will need fewer employees performing the same tasks. Solo entrepreneurs and small businesses have the most to gain from these technologies, as they will enable them to stay smaller and leaner for longer, while still growing revenue. For large, white-collar organizations, the idea of measuring management impact by the number of employees under a manager’s span of control will quickly become outdated.

While I remain optimistic about these changes and the new opportunities that generative AI will unlock, it does represent a large change to the global economy. Klu met with UK officials last week to discuss AI Safety and I believe the countries investing in education, immigration, and infrastructure policy today will be best suited to contend with these coming changes. This won’t happen overnight, but if we face these changes head on, we can help transition the economy smoothly.

Is there anything else that you would like to share with the CyberTalk.org audience?

Expect to see more security news regarding LLMs. These systems are like any other software and I anticipate both poorly built software and bad actors who want to exploit these systems. The two exploits that I track closely are very similar to buffer overflows. One enables an attacker to potentially bypass and hijack that prompt sent to an LLM, the other bypasses the model’s alignment tuning, which prevents it from answering questions like, “how can I build a bomb?” We’ve also seen projects like GPT4All leak API keys to give people free access to paid LLM APIs. These leaks typically come from the keys being stored in the front-end or local cache, which is a security risk completely unrelated to AI or LLMs.

[gradsireninc]

How To Get An Online Internship In the IT Sector (Skills And Tips)

Internships provide invaluable opportunities to gain practical skills, build professional networks, and get your foot in the door with top tech companies.

With remote tech internships exploding in IT, online internships are now more accessible than ever. Whether a college student or career changer seeking hands-on IT experience, virtual internships allow you to work from anywhere.

However, competition can be fierce, and simply applying is often insufficient. Follow this comprehensive guide to develop the right technical abilities.

After reading this, you can effectively showcase your potential, and maximize your chances of securing a remote tech internship.

Understand In-Demand IT Skills

The first step is gaining a solid grasp of the most in-demand technical and soft skills. While specific requirements vary by company and role, these competencies form a strong foundation:

Technical Skills:

Proficiency in programming languages like Python, JavaScript, Java, and C++

Experience with front-end frameworks like React, Angular, and Vue.js

Back-end development skills - APIs, microservices, SQL databases Cloud platforms such as AWS, Azure, Google Cloud

IT infrastructure skills - servers, networks, security

Data science abilities like SQL, R, Python

Web development and design

Mobile app development - Android, iOS, hybrid

Soft Skills:

Communication and collaboration

Analytical thinking and problem-solving

Leadership and teamwork

Creativity and innovation

Fast learning ability

Detail and deadline-oriented

Flexibility and adaptability

Obtain Relevant Credentials

While hands-on skills hold more weight, relevant academic credentials and professional IT certifications can strengthen your profile. Consider pursuing:

Bachelor’s degree in Computer Science, IT, or related engineering fields

Internship-specific courses teaching technical and soft skills

Certificates like CompTIA, AWS, Cisco, Microsoft, Google, etc.

Accredited boot camp programs focusing on applied skills

MOOCs to build expertise in trending technologies like AI/ML, cybersecurity

Open source contributions on GitHub to demonstrate coding skills

The right credentials display a work ethic and supplement practical abilities gained through projects.

Build An Impressive Project Portfolio

Nothing showcases skills better than real-world examples of your work. Develop a portfolio of strong coding, design, and analytical projects related to your target internship field.

Mobile apps - publish on app stores or use GitHub project pages

Websites - deploy online via hosting services

Data science - showcase Jupyter notebooks, visualizations

Open source code - contribute to public projects on GitHub

Technical writing - blog posts explaining key concepts

Automation and scripts - record demo videos

Choose projects demonstrating both breadth and depth. Align them to skills required for your desired internship roles.

Master Technical Interview Skills

IT internship interviews often include challenging technical questions and assessments. Be prepared to:

Explain your code and projects clearly. Review them beforehand.

Discuss concepts related to key technologies on your resume. Ramp up on fundamentals.

Solve coding challenges focused on algorithms, data structures, etc. Practice online judges like LeetCode.

Address system design and analytical problems. Read case interview guides.

Show communication and collaboration skills through pair programming tests.

Ask smart, well-researched questions about the company’s tech stack, projects, etc.

Schedule dedicated time for technical interview practice daily. Learn to think aloud while coding and get feedback from peers.

Show Passion and Curiosity

Beyond raw skills, demonstrating genuine passion and curiosity for technology goes a long way.

Take online courses and certifications beyond the college curriculum

Build side projects and engage in hackathons for self-learning

Stay updated on industry news, trends, and innovations

Be active on forums like StackOverflow to exchange knowledge

Attend tech events and conferences

Participate in groups like coding clubs and prior internship programs

Follow tech leaders on social mediaListen to tech podcasts while commuting

Show interest in the company’s mission, products, and culture

This passion shines through in interviews and applications, distinguishing you from other candidates.

Promote Your Personal Brand

In the digital age, your online presence and personal brand are make-or-break. Craft a strong brand image across:

LinkedIn profile - showcase achievements, skills, recommendations

GitHub - displays coding activity and quality through clean repositories

Portfolio website - highlight projects and share valuable content

Social media - post career updates and useful insights, but avoid oversharing

Blogs/videos - demonstrate communication abilities and thought leadership

Online communities - actively engage and build relationships

Ensure your profiles are professional and consistent. Let your technical abilities and potential speak for themselves.

Optimize Your Internship Applications

Applying isn’t enough. You must optimize your internship applications to get a reply:

Ensure you apply to openings that strongly match your profile Customize your resume and cover letters using keywords in the job description

Speak to skills gained from coursework, online learning, and personal projects

Quantify achievements rather than just listing responsibilities

Emphasize passion for technology and fast learning abilities

Ask insightful questions that show business understanding

Follow up respectfully if you don’t hear back in 1-2 weeks

Show interest in full-time conversion early and often

Apply early since competitive openings close quickly

Leverage referrals from your network if possible

This is how you do apply meaningfully. If you want a good internship, focus on the quality of applications. The hard work will pay off.

Succeed in Your Remote Internship

The hard work pays off when you secure that long-awaited internship! Continue standing out through the actual internship by:

Over Communicating in remote settings - proactively collaborate

Asking smart questions and owning your learning

Finding mentors and building connections remotely

Absorbing constructive criticism with maturity

Shipping quality work on or before deadlines

Clarifying expectations frequently

Going above and beyond prescribed responsibilities sometimes

Getting regular feedback and asking for more work

Leaving with letters of recommendation and job referrals

When you follow these tips, you are sure to succeed in your remote internship. Remember, soft skills can get you long ahead in the company, sometimes core skills can’t.

Conclusion

With careful preparation, tenacity, and a passion for technology, you will be able to get internships jobs in USA that suit your needs in the thriving IT sector.

Use this guide to build the right skills, create an impressive personal brand, ace the applications, and excel in your internship.

Additionally, you can browse some good job portals. For instance, GrandSiren can help you get remote tech internships. The portal has the best internship jobs in India and USA you’ll find. The investment will pay dividends throughout your career in this digital age. Wishing you the best of luck! Let me know in the comments about your internship hunt journey.

[gradsiren]

How To Get An Online Internship In the IT Sector (Skills And Tips)

Internships provide invaluable opportunities to gain practical skills, build professional networks, and get your foot in the door with top tech companies.

With remote tech internships exploding in IT, online internships are now more accessible than ever. Whether a college student or career changer seeking hands-on IT experience, virtual internships allow you to work from anywhere.

However, competition can be fierce, and simply applying is often insufficient. Follow this comprehensive guide to develop the right technical abilities.

After reading this, you can effectively showcase your potential, and maximize your chances of securing a remote tech internship.

Understand In-Demand IT Skills

The first step is gaining a solid grasp of the most in-demand technical and soft skills. While specific requirements vary by company and role, these competencies form a strong foundation:

Technical Skills:

>> Proficiency in programming languages like Python, JavaScript, Java, and C++ >> Experience with front-end frameworks like React, Angular, and Vue.js >> Back-end development skills - APIs, microservices, SQL databases >> Cloud platforms such as AWS, Azure, Google Cloud >> IT infrastructure skills - servers, networks, security >> Data science abilities like SQL, R, Python >> Web development and design >> Mobile app development - Android, iOS, hybrid

Soft Skills:

>> Communication and collaboration >> Analytical thinking and problem-solving >> Leadership and teamwork >> Creativity and innovation >> Fast learning ability >> Detail and deadline-oriented >> Flexibility and adaptability

Obtain Relevant Credentials

While hands-on skills hold more weight, relevant academic credentials and professional IT certifications can strengthen your profile. Consider pursuing:

>> Bachelor’s degree in Computer Science, IT, or related engineering fields. >> Internship-specific courses teaching technical and soft skills. >> Certificates like CompTIA, AWS, Cisco, Microsoft, Google, etc. >> Accredited boot camp programs focusing on applied skills. >> MOOCs to build expertise in trending technologies like AI/ML, cybersecurity. >> Open source contributions on GitHub to demonstrate coding skills.

The right credentials display a work ethic and supplement practical abilities gained through projects.

Build An Impressive Project Portfolio

Nothing showcases skills better than real-world examples of your work. Develop a portfolio of strong coding, design, and analytical projects related to your target internship field.

>> Mobile apps - publish on app stores or use GitHub project pages >> Websites - deploy online via hosting services >> Data science - showcase Jupyter notebooks, visualizations >> Open source code - contribute to public projects on GitHub >> Technical writing - blog posts explaining key concepts >> Automation and scripts - record demo videos

Choose projects demonstrating both breadth and depth. Align them to skills required for your desired internship roles.

Master Technical Interview Skills

IT internship interviews often include challenging technical questions and assessments. Be prepared to:

>> Explain your code and projects clearly. Review them beforehand. >> Discuss concepts related to key technologies on your resume. Ramp up on fundamentals. >> Solve coding challenges focused on algorithms, data structures, etc. Practice online judges like LeetCode. >> Address system design and analytical problems. Read case interview guides. >> Show communication and collaboration skills through pair programming tests. >> Ask smart, well-researched questions about the company’s tech stack, projects, etc.

Schedule dedicated time for technical interview practice daily. Learn to think aloud while coding and get feedback from peers.

Show Passion and Curiosity

Beyond raw skills, demonstrating genuine passion and curiosity for technology goes a long way.

>> Take online courses and certifications beyond the college curriculum >> Build side projects and engage in hackathons for self-learning >> Stay updated on industry news, trends, and innovations >> Be active on forums like StackOverflow to exchange knowledge >> Attend tech events and conferences >> Participate in groups like coding clubs and prior internship programs >> Follow tech leaders on social media >> Listen to tech podcasts while commuting >> Show interest in the company’s mission, products, and culture

This passion shines through in interviews and applications, distinguishing you from other candidates.

Promote Your Personal Brand

In the digital age, your online presence and personal brand are make-or-break. Craft a strong brand image across:

>> LinkedIn profile - showcase achievements, skills, recommendations >> GitHub - displays coding activity and quality through clean repositories >> Portfolio website - highlight projects and share valuable content >> Social media - post career updates and useful insights, but avoid oversharing >> Blogs/videos - demonstrate communication abilities and thought leadership >> Online communities - actively engage and build relationships

Ensure your profiles are professional and consistent. Let your technical abilities and potential speak for themselves.

Optimize Your Internship Applications

Applying isn’t enough. You must optimize your internship applications to get a reply:

>> Ensure you apply to openings that strongly match your profile >> Customize your resume and cover letters using keywords in the job description >> Speak to skills gained from coursework, online learning, and personal projects >> Quantify achievements rather than just listing responsibilities >> Emphasize passion for technology and fast learning abilities >> Ask insightful questions that show business understanding >> Follow up respectfully if you don’t hear back in 1-2 weeks >> Show interest in full-time conversion early and often >> Apply early since competitive openings close quickly >> Leverage referrals from your network if possible

This is how you do apply meaningfully. If you want a good internship, focus on the quality of applications. The hard work will pay off.

Succeed in Your Remote Internship

The hard work pays off when you secure that long-awaited internship! Continue standing out through the actual internship by:

>> Over Communicating in remote settings - proactively collaborate >> Asking smart questions and owning your learning >> Finding mentors and building connections remotely >> Absorbing constructive criticism with maturity >> Shipping quality work on or before deadlines >> Clarifying expectations frequently >> Going above and beyond prescribed responsibilities sometimes >> Getting regular feedback and asking for more work >> Leaving with letters of recommendation and job referrals

When you follow these tips, you are sure to succeed in your remote internship. Remember, soft skills can get you long ahead in the company, sometimes core skills can’t.

Conclusion

With careful preparation, tenacity, and a passion for technology, you will be able to get internships jobs in USA that suit your needs in the thriving IT sector.

Use this guide to build the right skills, create an impressive personal brand, ace the applications, and excel in your internship.

Additionally, you can browse some good job portals. For instance, GrandSiren can help you get remote tech internships. The portal has the best internship jobs in India and USA you’ll find.

The investment will pay dividends throughout your career in this digital age. Wishing you the best of luck! Let me know in the comments about your internship hunt journey.

[mercyjuliet1512]

Deciding Between Selenium with Python and Selenium with Java: An In-Depth Comparison

In the domain of automated testing, Selenium emerges as a pivotal tool for ensuring the reliability and quality of web applications. When it comes to selecting the programming language to harness Selenium's capabilities, two prominent contenders often come into play: Python and Java. Both languages offer distinct advantages and considerations, making the decision between them crucial for any automation project.

In this blog post, we'll conduct a thorough comparison of Selenium with Python and Selenium with Java, exploring their unique strengths, use cases, and factors to consider. By the end, readers will have a clearer understanding of which option aligns best with their project requirements, team proficiencies, and organizational objectives.

Python with Selenium:

Python, celebrated for its simplicity and readability, has garnered significant traction within the automation testing community. Let's delve into some key benefits of leveraging Python with Selenium:

Simplicity and Readability: Python's hallmark characteristics include simplicity and readability. Its concise syntax enables developers to express ideas in fewer lines of code, resulting in scripts that are easier to comprehend and maintain. For testers, this translates to expedited development cycles and reduced overhead in managing test suites.

Extensive Ecosystem: Python boasts a vast ecosystem of libraries and frameworks that complement Selenium, augmenting its capabilities for test automation. Whether handling data manipulation, conducting API testing, or generating test reports, Python's rich library support caters to diverse automation needs. Furthermore, the active Python community ensures an abundance of resources, tutorials, and documentation to aid testers throughout the automation journey.

Rapid Prototyping: Python's dynamic nature lends itself well to rapid prototyping and iterative development. Testers can swiftly experiment with different approaches, adapt scripts on-the-go, and respond promptly to evolving requirements. This flexibility seamlessly aligns with agile development methodologies, empowering teams to deliver high-quality software with agility.

Integration Compatibility: Python's interoperability with other tools and technologies makes it an appealing choice for Selenium automation. Whether integrating with continuous integration (CI) pipelines, test reporting frameworks, or version control systems, Python's versatility ensures smooth interoperability, streamlining the testing workflow and bolstering overall efficiency.

Java with Selenium:

Java, renowned for its robustness and performance, has long been a cornerstone in enterprise software development. Here are some compelling reasons to consider Java for Selenium automation:

Robustness and Performance: Java's static typing and strong object-oriented principles contribute to the robustness and performance of Selenium test suites. Its compile-time error checking aids in identifying potential issues early in the development phase, resulting in more stable and reliable automation scripts. For large-scale enterprise projects with stringent quality requirements, Java's reliability is a significant asset.

Widespread Adoption: Java enjoys widespread adoption within the enterprise landscape, making it a natural choice for organizations with existing Java codebases or a Java-centric development environment. The abundance of Java expertise in the workforce, coupled with extensive community support and industry recognition, solidifies its status as a preferred language for Selenium automation in many corporate settings.

Mature Tooling: Java's mature ecosystem of testing tools and frameworks, including JUnit and TestNG, seamlessly integrate with Selenium to offer comprehensive test automation solutions. These frameworks furnish advanced features such as parameterized testing, parallel execution, and built-in reporting capabilities, empowering testers to design and execute sophisticated test suites effortlessly.

Enterprise Support: Java's popularity in enterprise environments translates to robust support from vendors, extensive documentation, and a plethora of third-party integrations. For organizations seeking enterprise-grade features, reliability, and scalability in their Selenium automation endeavors, Java's ecosystem and support infrastructure present a compelling value proposition.

Conclusion:

In summary, both Selenium with Python and Selenium with Java present compelling options for test automation, each with its unique strengths and considerations. Python excels in simplicity, rapid development, and a vast ecosystem, making it an ideal choice for agile teams and projects with evolving requirements. Conversely, Java offers robustness, performance, and widespread enterprise support, rendering it well-suited for large-scale enterprise applications with stringent quality standards.

Ultimately, the decision between Python and Java for Selenium automation hinges on various factors such as project prerequisites, team proficiencies, and organizational preferences. By meticulously evaluating these factors and weighing the pros and cons of each option, stakeholders can make informed decisions that align with their specific needs and aspirations. Whether opting for the simplicity of Python or the robustness of Java, Selenium remains an indispensable tool for driving quality and efficiency in web application testing.