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Javacodegeeks

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Getting Started with ActiveJ

ActiveJ is a lightweight, high-performance Java framework known for its speed, minimalism, and modular architecture.
It offers advantages like high performance, asynchronous & non-blocking processing, minimalistic design, modularity, and built-in dependency injection.
A simple ActiveJ HTTP server can be created easily using HttpServerLauncher for handling requests efficiently.
ActiveJ Serializer provides efficient object serialization and deserialization capabilities for optimal performance.
Working with Dependency Injection in ActiveJ using ActiveJ Inject allows for organized dependency management and clean code structure.
ActiveJ's asynchronous I/O capabilities, Eventloop, and Promises enable efficient handling of high-throughput data processing tasks.
Eventloop in ActiveJ processes code asynchronously, scheduling tasks and enabling non-blocking operations for high performance.
Promises in ActiveJ represent the outcome of ongoing operations, facilitating asynchronous task management and concurrency.
The article provides practical examples, including building a HTTP server, using ActiveJ Serializer for object serialization, and demonstrating Dependency Injection.
ActiveJ simplifies handling concurrency, I/O operations, and data serialization, making it a valuable choice for responsive and scalable applications.

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Andrew Chen

216

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DoorDash's v1 was 8 PDF menus on a static HTML website

The early days of DoorDash, version 1.0, consisted of a static HTML page with 8 restaurant menus in PDF format and a Google Voice number.
The initial version was created in just 45 minutes, showcasing how simplicity can evolve into a widely-used product over time.
Lessons from implementing Minimum Viable Products (MVPs) over the past decade reveal common challenges like inconclusive testing and false negatives.
Product development struggles with competing in existing markets, inadequate user insights, and local optimization, among other issues.
Testing MVPs often leads to ambiguous results and can sometimes cause false restarts, requiring constant reevaluation and refinement of the product.
Creating follow-up tests is crucial but challenging due to the influence of previous tests on user perceptions and expectations.
Learning from existing successes and failures in a market can provide valuable insights for startups entering established sectors rather than pioneering new categories.
While MVPs have their place, some product categories and stages may not align well with the concept, especially in cases requiring significant upfront investment.
Overreliance on data over genuine customer insights poses a risk in product development, highlighting the importance of strategic judgment and qualitative understanding.
The startup journey involves shipping multiple MVPs, learning from failures, and iterating persistently to navigate the challenges of building a successful product over time.

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Medium

289

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Building a HyperStartup Alone: Tackling Hard Problems in 2025

Most startups focus on speed, funding, and rapid iteration, while avoiding hard problems that require specialized knowledge and take too long.
HyperStartups are deep, solo-driven, open startups focused on solving hard problems like AI, abductive reasoning, language models, etc.
The primary focus is NeuralLang, a new DSL designed to make neural networks as expressive and modular as programming languages.
The creator of HyperStartups wants to document every step, involve others in the progress, and create a culture of deep problem-solving.

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Medium

The Path to Excellence: Why I Chose Not to Stand in Line

Many people chase after quick success in trendy fields, but the author chose a different path.
The author is studying Telecommunications Engineering and sees it as a gateway to global opportunities.
They believe that excellence is a journey, not a moment, and taking the harder path leads to true success.
The author wants to create their own path and encourages others to not be afraid to walk alone.

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Medium

326

What is Data Sharing?

Data sharing involves the disclosure and transfer of various types of data, including personal identifiers, financial information, behavioral data, location data, biometric and health data, social media and communications, and employment and education data.
Data can be used in a devious way to target individuals, including microtargeting and manipulation, digital stalking and surveillance, price discrimination, denial of opportunities based on shared data, covert harassment and digital policing, reputation attacks, and the creation of data brokers and shadow profiles.
Unethical use of data can involve creating psychological profiles to manipulate beliefs or behavior, real-time tracking of movements and habits, showing different pricing based on personal data, denying coverage or services based on health or behavioral data, digitally targeting and discrediting individuals, undermining reputations through data leaks or smearing, and the buying and selling of data for profiling and manipulation.

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Medium

144

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Powerful Love Spells That Work: Discover the Secrets with Dr. Isingoma +256774791278

Dr. Isingoma's love spells are powerful and effective, tailored to each client's specific needs.
His approach combines ancient wisdom, personalized consultations, and ethical practices.
Clients report positive changes within days, thanks to his speed and effectiveness.
Dr. Isingoma offers a variety of love spells, including attraction, reconciliation, commitment, confidence boosting, and protection.

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Medium

Artificial and Natural Intelligence

A tsunami is a large wave in an ocean, which can be natural or artificial.
Intelligence is different from tsunamis, as it cannot be fake. If an agent behaves intelligently, it is considered intelligent.
Artificial intelligence, if achieved, will be real intelligence created artificially.
The Turing test, proposed by Turing in 1950, is a test for intelligence based on external behavior.

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RealPython

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Python Code Quality: Best Practices and Tools

High-quality Python code involves using tools and best practices to ensure functionality, readability, maintainability, efficiency, and security.
Best practices for quality Python code include descriptive naming, consistent style, modular design, and robust error handling.
Tools such as linters, formatters, and profilers can aid in achieving high-quality Python code.
Checking code quality with tools like linters helps maintain coding standards and detect errors.
Following practices like clear naming and comprehensive testing is key to writing quality Python code.
Quality Python code aligns with standards like PEP 8, emphasizing readability, maintainability, and efficiency.
Using formatters helps maintain consistent styling and readability in Python code.
Readability is enhanced by using descriptive names for variables, functions, classes, modules, and packages.
Low-quality code meets minimal functional requirements but lacks elegance, maintainability, and efficiency.
High-quality code is functional, readable, documented, compliant, reusable, maintainable, robust, testable, efficient, scalable, and secure.

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Dev

163

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How to configure CI/CD for your Node.js application

To configure CI/CD for your Node.js application, you need to follow these steps:
Step one: Create the repository on GitHub, configure the Docker Hub credentials, and push your source code.
Step two: Set up the GitHub Actions workflow for building, testing, and pushing the image to Docker Hub.
Step three: Run the workflow and check the repositories on Docker Hub for the newly pushed image.

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Medium

185

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Convert Non-Decimal String Values with Laravel’s Enhanced toInteger() Method

Laravel introduces an enhanced toInteger() method for converting non-decimal string values.
The toInteger() method allows for easier conversion of numbers in different bases within string operations.
This enhancement is useful for processing non-decimal numbers like color codes, binary data, or configuration values.
The method supports base values from 2 to 36, providing flexibility for a wide range of conversion needs.

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11 Likes

Medium

135

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Building Node.js and Golang Backend Communication with Kafka

Apache Kafka is a distributed platform used for building real-time data pipelines and streaming applications
Kafka is a set of machines working together to handle and process real-time infinite data
Kafka uses the concept of topics for sending and receiving messages
The article provides instructions for setting up Kafka with Node.js and Golang backends using Docker

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Dev

330

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Day-04: Java Work Flow

Java is a compiled programming language.
The workflow of Java involves transforming source code into byte code and then into binary code.
Java Development Kit (JDK) includes the compiler and Java Runtime Environment (JRE).
Java offers features such as platform independence, memory management, class libraries, security, and multithreading.

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Dev

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Getting started with Angular

Angular is a framework by Google for building single-page applications (SPAs) using HTML, CSS, and TypeScript.
To get started with Angular, you need to install Node.js and npm, then install Angular CLI.
After setting up the environment, you can create your first Angular project using Angular CLI.
Once the project is created, you can explore the key components within the src/app/ directory and run your Angular app using ng serve.

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Dev

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The Million-Dollar Problem of Slow Microservices Testing

Shifting integration tests from the slow outer loop to the rapid inner loop can transform development processes in organizations.
A VP of platform engineering highlighted losing about half a million dollars monthly due to their broken testing process.
Their integration testing was disconnected from the PR review process, leading to significant productivity losses.
The traditional solution of spinning up more environments was deemed costly and ineffective in solving the fundamental problem.
Microservice architectures create a dilemma for engineering teams, balancing scalability with diminishing developer productivity.
The outer loop of integrating changes, running full system tests, and deploying becomes a major productivity killer.
Challenges in the outer loop include an integration bottleneck, context switch penalties, and waiting times due to access controls.
Traditional approaches like creating more environments are not scalable and lead to bottlenecks and productivity drains.
A modern approach using tenancy-based environments with service mesh technology can dramatically improve testing efficiency.
By providing isolated testing environments for every pull request, organizations can enhance developer productivity and software quality.
Handling data isolation challenges is crucial, with shared databases and ephemeral database instances being viable solutions.

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Medium

289

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AWS Cloud Automation with Python & Boto3

Python with boto3 is a powerful AWS automation tool for infrastructure provisioning, cost analysis, and more.
Installing boto3 and configuring AWS credentials is the first step towards AWS automation.
The article provides practical examples and steps for automating tasks like EC2 instance provisioning and AWS billing reporting with Python and boto3.
Automation with Python and boto3 simplifies AWS management, enhances efficiency, and reduces manual effort.

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