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PlanetPython

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Python Software Foundation: Powering Python together in 2025, thanks to our community!

The Python Software Foundation (PSF) expresses gratitude to donors and new members in their end-of-year fundraiser and membership drive.
The PSF raised $30,000 through the PyCharm promotion offered by JetBrains and around $99,000 overall to support Python and its community.
Key goals for 2025 include embracing opportunities and tackling challenges, fostering sustainable growth, and improving workflows through collaboration.
The PSF welcomes new members and encourages involvement from the Python community in shaping its future.

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Dev

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The Ever-Evolving Tale of Intelligence, from Symbolic Systems to Generative Ai

Artificial Intelligence refers to making machines perform tasks that typically require human intelligence.
Generative AI creates brand-new content from analyzed data, which takes the approach of symbolic reasoning, machine learning, deep learning to another level.
Programmers, journalists, social media managers, copywriters, and designers can use GenAI to supercharge their work, making them able to focus more on architecture and creative aspects.
Like blockchain technology, GenAI has gone through its Hype Cycle, where the current stage is at or near its peak of inflated expectations. Nevertheless, meaningful applications will continue to grow over time.
Large Language Models (LLMs) are another major ingredient that makes GenAI so powerful as they allow these systems to understand context and nuance in ways that we couldn't have imagined just a few years ago.
The next chapter in GenAI's ever-evolving story is to explore how these systems hum with their building blocks, training strategies, and optimization techniques, known as the GenAI pipeline.
GenAI is not a technology that threatens to take away jobs, but an ally that can change how we work.
GenAI is not just a technology; it's a new lens through which we can imagine and build our future.
Fonyuy Gita welcomes feedback, collaboration ideas, and other inquiries.
Fonyuy Gita may be contacted via email, Github, X (formerly Twitter), and LinkedIn.

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Dev

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Dynamically Render Components Based on Configuration

When building apps, you often encounter situations where you need to render different components or layouts based on data.
Instead of using a lot of if-else or switch statements, you can use a configuration-driven approach for cleaner and more scalable code.
This technique involves dynamically rendering components based on a configuration object.
Benefits include scalability, reusability, and improved readability.

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Nordicapis

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What Does Section 1033 Mean for Open Banking in the US?

Open banking is becoming a more prominent topic in the US, with many market commentators talking about Section 1033, a revised regulation from the Frank-Dodd Act, and how it might affect the state of the open banking ecosystem in the US.
According to Visa, open banking is already a big deal in the US financial services market. 87% of account-holding customers use open banking solutions to connect their accounts to third-party solutions.
The United States open banking market is not standardized enough, and participation varies based on bank size. The “Final Rule” of Section 1033 aims to provide standardized participation framework for the US market.
One of the most significant changes in Section 1033, finalized on October 22, 2024, is the move towards API standards, both functional and security-related, for the first time.
The certification of Data Providers for using a 'certified' standard to provide their APIs, and the fact that APIs must be provided at zero cost to the consumer, is crucial under Section 1033.
There are some aspects of the open banking market in the USA that require addressing, such as a directory of participants, recognized trust anchors, and certification of conformance to standards by Data Providers.
The implementation of Section 1033 might be impacted by legal challenges and changes in regulations from the incoming US administration.
Section 1033 is expected to bring about increased standardization in the US open banking market. Still, it remains to be seen whether this makes life easier for ecosystem participants.
The Nordic APIs blog will keep an eye on what happens next and update the article with any changes.

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Medium

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We Trained an AI to Reveal the Ultimate Halloween Costume

The ultimate Halloween costume is about cultural relevance, reflecting what's trending in entertainment at the time.
To arrive at the ultimate Halloween costume, specific prompts can guide AI through the process to synthesize cultural data from the last decade and modern viral trends.
Despite media trends, traditional costumes like witches, vampires, and ghosts remain perennial favorites every year.
Both Barbie Witch and Spiderman costumes surged in popularity due to the success of the Barbie movie and Spiderman: Across the Spider-Verse.
ChatGPT was guided through a more comprehensive process that focused on larger cultural patterns through the implementation of Retrieval Augmented Generation (RAG) method.
AI-driven creativity can help us learn how to guide models to think contextually and provide insights that are timely, meaningful, and useful.
AI can blend synthesis, creativity, and historical trends to help us make smarter decisions within Halloween costumes and business applications.
Ghosts and witches, Halloween staples for decades, continue to be popular due to their adaptability and association with spooky, supernatural themes.
The Barbie Witch costume taps into multiple layers of pop culture with the appeal of Barbie's massive cultural roots and the timeless appeal of witches, becoming a creative and relevant combination.
The RAG model synthesized cultural data from the last decade and modern viral trends to produce more thoughtful and relevant responses for the ultimate Halloween costume.

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Medium

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A New Year of Possibilities for STON.fi

STON.fi achieved successful integration with a new partner, expanding opportunities for collaborations
Significant progress was made on their development roadmap, with key features nearing completion
They engaged with their community through social media and other channels, providing updates and support
STON.fi aims to expand their ecosystem through strategic partnerships, improve their platform's user experience, and grow their community

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Dev

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SPL: a database language featuring easy writing and fast running

SPL is a database language with easy writing and fast running. It contains two essential functions: calculation and transaction. SQL is the mainstream database language currently used, but SQL is considered incompetent in both aspects. SPL is designed to make calculation easier in writing and faster in running through the invention of new algebra. SPL is based on the discrete dataset, which extends many operations of the structured data and is rich in set data types. SPL has many advantages over the relational algebra, such as discrete records, the ordering characteristic, and more understanding of grouping and aggregation. Moreover, SPL has many engineering-level advantages, including easier to write parallel computing code, large memory pre-association, unique column storage mechanism, and more. SPL is capable of implementing various big data algorithms that deliver high performance with seemingly real-time or near-real-time results.

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Dev

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10 Software Engineering Books Developers Should Read in 2025

Continuous learning is essential for software engineers, and books are a great way to learn from other people’s experiences.
This article shares 10 essential books every software engineer should read in 2025, covering topics like general advice for programmers, coding, software architecture, design patterns, and data structures and algorithms.
Books featured include The Pragmatic Programmer by Andrew Hunt and David Thomas, Clean Code by Robert C. Martin, and Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.
The Pragmatic Programmer provides actionable advice for developers, Code Complete (2nd Edition) helps with software construction, Clean Code emphasizes the importance of readability and neatness, and Refactoring teaches how to improve existing codebases.
Designing Data-Intensive Applications explains modern software applications, while System Design Interview volumes 1 & 2 prepares readers for system design interviews.
Design Patterns by Gamma, Helm, Johnson, and Vlissides introduces 23 foundational software patterns, while Eric Evan’s Domain-Driven Design explores techniques to handle complex business domains in software development.
Lastly, Cracking the Coding Interview provides programming questions and solutions to technical interviews.
Reading these books can help one become a better software engineer and developer by expanding their knowledge base and providing insights and techniques to enhance their skills.
Readers can start with a book that addresses their specific area of improvement.
A bonus free book on Distributed System Design is also available through Microsoft.

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Dev

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End-to-End API Testing: How Mocking and Debugging Work Together

End-to-end API testing is essential for verifying that all the components of an application work together as expected and that the application behaves correctly in real-world scenarios.
Mocking in API testing involves creating simulated versions of external services, allowing you to test your API in a controlled and predictable environment.
Debugging plays a crucial role in identifying and fixing issues that arise during testing and ensures that your API functions correctly under different conditions.
Mocking simplifies API testing by giving you complete control over the testing environment, reducing dependencies on external services, and making your tests more reliable and faster.
Debugging helps trace the flow of data, identify bottlenecks, and pinpoint the root cause of failures when testing APIs, and effective tools like Blackbird offer deep insights into API behavior for this purpose.
Combining mocking and debugging creates a comprehensive testing strategy that simplifies the identification and resolution of issues and ensures that APIs function as expected in real-world scenarios.
Best practices include using realistic scenarios, automating tests, collaborating with your team, monitoring performance, and continuously improving the testing process.
End-to-end API testing is essential for ensuring that your APIs work seamlessly in real-world scenarios. By integrating API mocking and debugging into your testing process, you can simulate complex environments, catch issues early, and ensure that your APIs handle all situations smoothly.
Mocking allows you to test without depending on external services, while debugging provides the insights needed to fix issues quickly and efficiently. Together, they create a powerful combination that enhances the reliability of your APIs.
Tools like Blackbird offer a comprehensive platform for creating mock services, running and debugging API code, and collaborating with your team, ensuring that your APIs are robust and reliable.

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Dev

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The Ultimate VPS Showdown: Hetzner, Ionos, and LuxVPS — Who’s Your Budget Buddy? 🎉

Hetzner offers reliable and robust VPS options for high-performance apps or production environments.
Ionos is a budget-friendly VPS provider suitable for small websites or projects on a shoestring budget.
LuxVPS provides unbeatable pricing and great deals for budget-conscious users, making it ideal for small to mid-sized projects.
Choosing the right VPS depends on factors such as project size, future growth, and budget considerations.

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Dev

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Building Machine Learning Models in Java

Java offers powerful capabilities and extensive libraries for machine learning (ML), making it a strong contender to Python.
Java is known for its performance, scalability, integration capabilities, and library support for ML.
To build ML models in Java, you need to set up the environment with JDK, IDE, and ML libraries like Weka.
You can build a simple classification model using Weka and perform tasks like data loading, model building, and evaluation.
For advanced ML tasks, Deeplearning4j is recommended, which is a powerful library for deep learning in Java.

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Medium

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Learning to Code: My Story

Learning to code can be both rewarding and challenging.
While there are days when everything makes sense and coding feels enjoyable, there are also days when one can struggle for hours to solve a problem.
Choosing computer science for its promising job opportunities is common, but people often overlook the difficulty of the learning process.
Despite the challenges, the satisfaction derived from writing successful code and witnessing it perform as intended can be fulfilling.

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Javacodegeeks

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Java Chatbots: Comparing Apache OpenNLP and Stanford NLP for NLP

Apache OpenNLP and Stanford NLP are two popular NLP libraries for Java developers.
Apache OpenNLP provides pre-trained models and utilities for common NLP tasks. It is lightweight and suitable for small to medium-scale applications.
Stanford NLP offers advanced algorithms and extensive functionality. It is ideal for research and enterprise-level chatbots.
Choose Apache OpenNLP for lightweight applications and Stanford NLP for complex tasks and multi-language support.

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Medium

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The top 5 future tech trends that will revolutionize our lives

Brain-Computer Interfaces (BCIs) will allow people with neurological disorders to control technology with their neural signals.
Quantum Computing will solve complex problems at an extraordinary speed, leading to medical breakthroughs, advances in finance, and climate modeling.
Synthetic Reality, with augmented, XR, and mixed reality, will redefine immersion in entertainment, education, and communication.
Synthetic Biology will enable engineers to create new biological systems and drive innovation in biofuels, agriculture, and disease treatments.
Space Technology advancements will unlock valuable resources, pave the way for interplanetary travel, and colonization of new habitats.

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Medium

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CMake Error: Cannot Link nanobind to Library

CMake is a tool used for managing the compilation process, linking libraries, and generating build files for various platforms.
To link Nanobind to a library using CMake, you need to properly configure the CMakeLists.txt file and specify the necessary dependencies.
Nanobind is a header-only library that simplifies the creation of Python bindings for C++ code, making the build process easier and more streamlined.
Challenges in integrating Nanobind with CMake may arise due to linker errors, version mismatches, or incorrect library paths. Following best practices and consulting documentation can help overcome these challenges.

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