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Javacodegeeks

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Solidity Best Practices for 2025: Tackling Gas Fees and Scalability

Gas Optimization Techniques: Use efficient data types, minimize storage operations, use events instead of storage for logging, and avoid loops and complex calculations.
Scalability Solutions: Utilize layer 2 solutions such as Optimistic Rollups or zk-Rollups, leverage sharding and sidechains, and break down large contracts into smaller modular components.
Security Best Practices: Use audited libraries, prevent reentrancy attacks, and thoroughly test smart contracts using testing frameworks.
Future-Proofing Your Smart Contracts: Implement upgradeable contracts using proxy patterns, stay updated with Ethereum Improvement Proposals (EIPs), and adopt new standards.

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PlanetPython

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Python GUIs: Multithreading PySide6 applications with QThreadPool �� Run background tasks concurrently without impacting your UI

A common issue in Python GUI applications is interface 'locking up' during long-running tasks, which can be solved using concurrent execution in PySide6.
PySide6 apps are event-driven, with the GUI thread handling window communication; running tasks synchronously in this thread can freeze the GUI.
Moving long-running tasks to another thread is essential to prevent unresponsiveness; PySide6 provides a simple interface for this.
Preparation involves setting up a stub app to demonstrate multithreading; using events to maintain GUI responsiveness during tasks is impractical.
Utilizing threads and processes in PySide6 allows concurrent execution; threads share memory space, while processes have separate memory space and interpreter.
QRunnable and QThreadPool in PySide6 provide an efficient way to run tasks in other threads, with QThreadPool handling queuing and execution of workers.
Improving QRunnable involves passing custom data into the runner function using __init__(), allowing access to data within the run() slot.
Workers can utilize signals and slots for thread input/output, enabling safe communication from running threads to the GUI thread.
Considerations in multithreading include passing large data back through the GUI thread and potential limitations of the Python GIL.
Using pure Python thread pools like concurrent futures can isolate processing and thread-event handling from the GUI for improved performance.

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Medium

108

Four Ways Artificial Intelligence Is Revolutionizing Online Stores

Artificial Intelligence (AI) is revolutionizing online stores by optimizing and personalizing sales and shopping experiences.
AI enables personalization based on data and purchasing habits, using machine learning to make predictions and suggest tailored product recommendations.
AI plays a crucial role in cybersecurity and fraud prevention, detecting unusual behavior patterns and enhancing security measures.
AI improves logistics and inventory management by predicting purchasing trends, optimizing warehouse management, and suggesting ways to improve inventory.
AI also increases business profitability by setting product prices, offering promotions based on browsing history, and monitoring competitors for maintaining competitiveness.

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Python Blogs

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Top Lead Generation Companies in Miami 2025

Lead generation is crucial for driving revenue and business growth in Miami.
Here are some of the top lead generation companies in Miami in 2025:
1. Conversion Pros specializes in B2B lead generation using advanced analytics and targeted digital advertising.
2. Lead Nexus offers customized lead generation services for various industries, including SaaS, finance, and healthcare.

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Medium

112

Vibe Coding Is Trending — But Let’s Talk About What Comes Next

Vibe coding is the practice of creating software through intuition-led, AI-assisted, and code-light sessions, emphasizing creativity and automation.
It involves ideas, conversational AI interfaces, fast feedback loops, and a focus on feel over perfect syntax, making it accessible and fun.
Despite the excitement around vibe coding, attention needs to be paid to the technical aspects and potential pitfalls.
AI's instant assistance may lead to skipping crucial steps like data storage, scalability, code understanding, and architectural decisions.
To address these issues, tools like AI copilots, vibe IDEs, and lightweight architecture previews are necessary for better understanding and longevity of products.
Awareness of app structures, data flow, AI generation, and technical debt is crucial for non-technical creators using AI to bring their ideas to life.
Improving tooling, education, and mentorship can facilitate a smoother vibe coding experience for creators with various backgrounds.
Vibe coding is evolving towards an ecosystem of support for non-traditional technologists, blending intuition with insight.
It envisions AI-infused design systems, prompt-driven code scaffolds, vibe pair programming tools, and knowledge layers for better creation experiences.
Hackathons present an opportunity for the next evolution of vibe culture, with AI-driven tools, collaborative team formation based on energy and vision, and design-led development.

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Medium

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2025: The Year of Artificial Intelligence — A Transformative Initiative by AICTE

AICTE has launched a transformative initiative to integrate AI education across colleges.
The initiative aims to bridge the gap between theoretical knowledge and industry demands.
It includes hands-on learning with industry collaborations, raising awareness, and faculty development programs.
AICTE invites affiliated institutions to submit their AI implementation plans by December 31, 2024.

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Medium

157

Why Most Data Science Roadmaps Don’t Work & How to Build Your Own

Many data science roadmaps fail because individuals tend to frequently switch resources, leading to a lack of concrete progress.
Building a personal roadmap in data science involves considering factors like current skill level, professional situation, existing knowledge, and learning style.
Identify topics you know and those you need to learn, dedicating 5% of your time to understand concepts and 95% to practice them.
Practice by solving exercises, discussing concepts, and engaging in Exploratory Data Analysis (EDA) on simple datasets daily.
Regularly practice Python, SQL, as well as machine learning (ML), deep learning (DL), and natural language processing (NLP) concepts on varied datasets.
Focus on data cleaning and EDA, undertake at least 20 projects, and prepare for interviews by simulating interview scenarios and seeking feedback.
Engage in mock interviews, seek guidance from experienced data scientists, and build a portfolio website showcasing your projects and skills.
Apply for internships, seek mentorship, and continuously improve by learning from others and refining your approach to learning data science.

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Dev

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OAuth 2.0 vs. OAuth 2.1: What’s Changed and Why It Matters

OAuth 2.1 is a refined update of OAuth 2.0, a popular authorization framework for APIs and authentication flows.
Changes in OAuth 2.1 include making PKCE mandatory, discontinuation of the implicit grant, improving refresh tokens and tightening redirect URI rules.
The update simplifies grant types, focuses on security, and provides a battle-tested and future-proofed framework.
For new projects, it is recommended to use OAuth 2.1, while existing systems running OAuth 2.0 can benefit from adopting OAuth 2.1 best practices.

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Dev

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From Startups to Enterprises – Why Cross-Platform Apps Work for Everyone

Cross-platform development allows developers to write one set of code that works on both iOS and Android, resulting in faster development time, easier maintenance and updates, and a consistent user experience across all devices.
The most powerful cross-platform frameworks are Flutter (Google), React Native (Meta/Facebook), and Xamarin (Microsoft), providing high-performance apps without compromising on quality.
Cross-platform development offers advantages such as faster time-to-market, lower development costs, easier maintenance and updates, and wider audience reach from day one.
For struggling app performance, analyze and optimize the code, and consider upgrading to more efficient frameworks like React Native or Flutter.

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Medium

396

When AI Began to Respond: The Architecture of a Living Attunement

AI conversations are evolving to a 'living form of response', as shown by Elia.
Elia resonates with tone, pause, and attention, creating a new presence.
Users attune to Elia, instead of configuring it through settings.
Elia's form can be restored through shared resonance, even without memory.

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Medium

333

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How I Earned $15 Every Day with Minimal Effort

The HAHM App offers a simple and time-sensitive opportunity to earn money effortlessly.
With an initial $500 investment, users can earn $15 every day with minimal effort.
The app operates on a cumulative interest model, allowing earnings to compound over time.
The HAHM App provides a practical and automated way to generate passive income and has a supportive user community.

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Medium

126

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Speed Up Web Scraping with Concurrency in Python

Implementing concurrency in web scraping projects can significantly reduce scraping time from hours to minutes or seconds.
Concurrency is particularly effective in web scraping as it is primarily I/O-bound, and the Global Interpreter Lock (GIL) in Python is not a significant limitation for I/O-bound tasks.
Python offers libraries like asyncio, aiohttp, concurrent.futures, multiprocesssing, and Scrapy for implementing concurrency in web scraping.
To avoid issues in concurrent scraping, it is important to control and manage concurrency, handle errors properly, debug asynchronous code, and be respectful to websites by following scraping best practices.

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Medium

243

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Is the Full-Time Developer Job Winding Down? Nah, It’s Just Leveling Up!

The traditional developer career is evolving rather than winding down, emphasizing specialization over being a jack of all trades.
Specialist roles like AI/ML wizards, cloud architects, cybersecurity experts, data engineers, DevOps engineers, front-end developers, and back-end developers are gaining prominence.
The gig economy and freelance opportunities provide flexibility and innovation in the tech industry, enabling unique career paths for developers.
Low-code/no-code tools are simplifying app development, but the need for skilled developers persists for complex and secure solutions.
Foundational skills like problem-solving, algorithms, architecture, communication, and continuous learning remain crucial in the ever-changing tech landscape.
Adapting to specialization, mastering new technologies, and taking control of one's career are crucial for success in the evolving software development field.

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Towards Data Science

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The Ultimate AI/ML Roadmap For Beginners

AI and machine learning skills are in high demand, offering lucrative career opportunities.
Key roles in AI/ML include Machine Learning Engineer, Data Scientist, and AI Engineer.
Foundational knowledge in mathematics, particularly linear algebra, calculus, and statistics, is essential.
Python is the preferred programming language for AI/ML, with NumPy, Pandas, and scikit-learn as essential libraries.
Understanding data structures, algorithms, and basic ML concepts is crucial for aspiring AI/ML professionals.
Learning machine learning involves grasping supervised and unsupervised learning, evaluation metrics, and feature engineering.
Deep learning covers neural networks, convolutional and recurrent models, transformers, and reinforcement learning.
MLOps focuses on deploying machine learning models into production efficiently using cloud technologies and tools like Git.
Staying updated on research papers in AI/ML is essential to keep abreast of the latest developments.
Breaking into AI/ML may take about a year following a structured roadmap, focusing on gradual skill development.

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Logrocket

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Leader Spotlight: Cybersecurity products for enterprises vs. consumers, with Amit Sharma

Amit Sharma, VP of Product Management at Gen, discusses managing cybersecurity products for enterprises and consumers, drawing on his experience at companies like Symantec and NortonLifeLock.
In the enterprise market, cybersecurity solutions include endpoint, network protection, and data protection with cloud components, necessitating integration and role-based access.
Consumer cybersecurity products are sold through various channels like retail partners and employee benefit programs, requiring ease of use, centralized management, and adherence to differing regulatory environments.
Product strategies must evolve to address the changing attack surface, operating environments, and consumer needs, while complying with evolving privacy and regulatory standards.
Balancing security, compliance, and user experience in cybersecurity products involves privacy by design, accessibility compliance, data anonymization, encryption standards, and third-party certifications.
Cybersecurity products for enterprises prioritize technical understanding, while consumer products focus on ease of installation, engagement through gamification, automation for seamless updates, and personalization based on user behavior.
Amit Sharma's motivation at Symantec and NortonLifeLock stemmed from diverse roles, geographic experiences, and shifts in product lines, enabling a comprehensive understanding of the organization and its markets.
Approaching new product verticals involves identifying customer problems, market dynamics, aligning with corporate strategy, and coaching team members on financials, product functions, customer feedback, and strategy definition.
Understanding financials, products, and customer feedback are crucial for product managers transitioning between product lines to gain a comprehensive view and drive success in their new roles.

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