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Should the Backend Be “Beautiful”?

Beauty in backend development refers to clarity, structure, and maintainability.
A beautiful backend has clear architecture, is easy to read and navigate, and handles errors gracefully.
The backend's beauty matters for scalability, collaboration, debugging, onboarding, and pride in work.
Backend beauty comes from using async/await properly, keeping methods lean, writing tests, and avoiding 'magic' code.

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PlanetPython

406

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Django Weblog: Django security releases issued: 5.1.8 and 5.0.14

Django security releases issued: 5.1.8 and 5.0.14
The Django team has issued security releases for Django 5.1.8 and 5.0.14
The releases address a potential denial-of-service vulnerability in LoginView, LogoutView, and set_language() on Windows
Users of Django are encouraged to upgrade to the latest releases

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Dev

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How to Parse Environment Variables into DTO in .NET: AWS S3 Bucket Example

Treating configuration settings as a DTO class will make your code more readable.
To parse configuration into a DTO class, you can create a separate class to hold the configuration properties.
In .NET, you can configure the dependency injection container to store your configuration using IOptions and Configure().
If you prefer using records instead of classes, you can use the Get extension method to map configuration to a strongly typed object.

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Medium

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Into the world of HFTs and Market-Statistical arbitrage Introduction

High-Frequency Trading (HFT) leverages advanced computing to execute trades in milliseconds using mathematical models and automation.
Key components include co-location services, ultra-fast networks, and AI for analyzing market trends.
HFT strategies include latency arbitrage, market making, statistical arbitrage, and momentum trading.
Technological advancements like quantum computing, blockchain, and AI enhance HFT efficiency.
Market arbitrage exploits price differences across markets, contributing to market efficiency.
Factors influencing market arbitrage include exchange latency, liquidity variations, and regulatory differences.
Statistical arbitrage uses historical data and quantitative models to profit from price relationships.
Machine learning has transformed statistical arbitrage by analyzing vast amounts of financial data.
While HFT benefits market efficiency and liquidity, concerns about unfair advantages and market instability exist.
Regulators globally are refining policies to balance HFT innovation with market fairness.

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Medium

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How Machine Learning Works: A Simple Explanation for Beginners

Machine learning is about teaching computers to recognize patterns in data without explicitly programming them for every possible scenario.
The process starts with a dataset, which can be of different types and quality.
To teach the computer to recognize patterns, a machine learning algorithm is used. These algorithms fall into three main categories: supervised, unsupervised, and reinforcement learning.
Supervised learning involves training a model using labeled data with a known answer.

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Medium

251

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Augmentcode ai review — large code base? This is your answer

Augmentcode ai review - large code base?
Switch off Copilot to access the full article for free.
Index your codebase to use Copilot.
Review of Augmentcode AI, which provides correct recommendations and relevant questions.

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Self-Learning-Java

247

How to Interact with Ollama Language Models via APIs Using Python?

Ollama Language Models (LLMs) are powerful tools for generating human-like text, and interacting with them via APIs opens up endless possibilities.
APIs provide a seamless way to communicate with LLMs for tasks like text generation, summarization, and more.
The post provides a step-by-step guide to interacting with Ollama LLMs via APIs in Python.
By following the guide, users can easily integrate Ollama LLMs into applications for dynamic, human-like text generation.

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Self-Learning-Java

128

How to Use the /api/chat Endpoint for Conversations?

The /api/chat endpoint is crucial for maintaining conversations with an AI assistant, catering to chatbots, virtual assistants, etc.
Passing conversation history with each request enables natural responses and context maintenance.
Roles like system, user, and assistant differentiate conversation parts in the /api/chat endpoint.
Initiate a conversation with a single user message in the messages array.
Continuing a conversation involves including the entire history in subsequent requests.
Utilize the system role to guide the assistant's behavior effectively.
Usage of the stream parameter affects response delivery in one payload or real-time chunks.
By following role conventions and structuring messages, clarity and efficiency are ensured.
Including chat history and utilizing the system role enhances engagement and contextual awareness.
The /api/chat endpoint offers a versatile approach for conversational AI systems, fostering engaging experiences.

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Medium

410

Beginners-How to Set Up PHP for Development (Windows, Mac, Linux) 2025

To run PHP, you need a local server.
For Windows, download XAMPP from Apache Friends, then run the installer and start Apache and MySQL.
Enable PHP Extensions by editing the php.ini file and removing the semicolon before 'extension=zip'. Restart Apache.
Install Composer to manage PHP libraries, and choose a code editor such as VS Code or PHPStorm.

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Dev

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Mastering Next.js API Caching: Improve Performance with Middleware and Headers

Effective API caching is crucial for Next.js applications to reduce latency, server load, and operational costs.
Implementing caching strategies improves app performance, optimizes external API usage, and enhances user experience.
Cache-Control headers and Next.js Middleware play key roles in managing API caching efficiently.
Setting Cache-Control headers helps in reducing response times, handling concurrent requests, and controlling CDN caching.
Using Middleware for global API caching rules centralizes caching policies and ensures scalability.
Understanding and utilizing Cache-Control directives like public, private, s-maxage, and stale-while-revalidate is essential.
Layering API caching with ISR and SSG strategies in Next.js results in optimal performance and resource management.
Common pitfalls around cache invalidation include serving stale data, misconfigured caches, and accidentally caching sensitive information.
Best practices to avoid cache invalidation issues include monitoring, versioning API routes, and controlling caching separately for CDN and browsers.
By combining API caching with ISR and SSG, developers can achieve double performance gains, reduced infrastructure costs, and improved SEO benefits.

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Insider

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Cheating on tech interviews is soaring. Managers don't know what to do.

Many job applicants are resorting to cheating on technical coding interviews by using generative AI tools like ChatGPT, prompting concerns among hiring managers about the effectiveness of traditional coding tests.
AI has made cheating on technical screening tests more seamless, with tools like Interview Coder enabling candidates to cheat on coding tests and even sell the cheating tool for a monthly fee.
Companies like Amazon and Google are implementing measures to detect and disqualify candidates using generative AI during interviews, raising ethical questions about the boundaries of cheating.
The reliance on AI in engineering tasks is blurring the lines between fair testing practices and leveraging technology effectively on the job, leading to a reevaluation of traditional coding interview processes.
Recruiters and hiring managers are adapting to combat cheating, with AI tools being used to identify suspicious behavior in coding tests and interviews.
As AI becomes more prevalent in the job market, questions about defining cheating and the impact of AI on the hiring process emerge, highlighting the need for evolving interview practices.
There is a growing concern that young engineers reliant on AI tools may find it challenging to transition their skills effectively into workplace scenarios that require critical thinking and understanding beyond AI assistance.
Employers and job candidates are navigating a new frontier in technical interviews, with a push towards changing coding test norms and enhancing fairness in the evaluation process.
The breakdown in trust between employers and workers, exacerbated by cheating allegations and concerns, indicates a need for reimagining coding tests to restore integrity and improve the hiring process.
Tech industry correspondent Amanda Hoover suggests focusing on training interviewers to ask incisive questions rather than solely relying on detecting cheating, fostering a more effective and fair interview experience.
The evolving landscape of coding interviews underscores the necessity for innovative approaches that align with the growing role of AI in engineering tasks and the changing dynamics of the job market.

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Dev

185

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How to Build a Internal Data App with Google Sheets Backend Using Streamlit

This article discusses how to build an internal data app using Streamlit with Google Sheets as the backend.
The article provides a step-by-step guide for configuring Google Sheets API and setting up Streamlit for the app.
Key steps include enabling the Google Sheets API, creating a service account, granting access to the spreadsheet, and installing Streamlit.
The article showcases code snippets for authentication, retrieving data from Google Sheets, and displaying it in a Streamlit app.
Various methods for adding authentication for internal use in Streamlit apps are also discussed in the article.
Options include adding authentication individually, using Snowflake in Streamlit, or leveraging Morph platform for centralized app management.
Streamlit is highlighted as a useful tool for building data applications powered by machine learning or AI, especially for internal tools like workflow automation, demand forecasting, and internal chatbots.
The possibilities of applying Streamlit are vast, making it a valuable tool for data scientists and analysts.
Streamlit is recommended for those comfortable with Python and interested in developing data applications efficiently.
Overall, the article emphasizes the versatility and potential of Streamlit for a wide range of internal data app development scenarios.
To explore the full potential of Streamlit, the article encourages readers to give it a try and experiment with different use cases.

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11 Likes

Medium

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5 Packages Every Python Developer Should Have in Their Toolbox

Python has a variety of useful packages that make coding easier and more efficient.
Typer is a package that simplifies the creation of command-line applications, making them clean and understandable.
Rich is a package that enhances the appearance of the console screen, making the output more visually appealing.
Pandas is a versatile package for data analysis and manipulation, making it a must-have for Python developers.

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Medium

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Repositories in Game Development

A code repository is where your project’s files live and are tracked over time.
Repositories allow developers to easily rewind to older versions or create multiple branches for testing new features.
There are different tools available for version control, such as Git and SVN.
It is important to commit regularly and use clear commit messages in the repository.

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Dev

167

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How to Write Test Scenarios That Ensure App Success

Test scenarios provide a structured way to verify system functionality and are essential for ensuring app success.
They focus on what needs to be tested rather than the specific steps to be followed during testing.
Test scenarios make it easier to discuss testing scope with stakeholders and adapt to changing requirements.
Steps to write compelling test scenarios include analyzing requirements, listing user workflows, and prioritizing critical scenarios.
Dependencies and pre-conditions should be identified in test scenarios to avoid unexpected blockers during execution.
Test scenarios should be clear, concise, and reviewed with stakeholders for alignment with business objectives.
Test scenarios and test cases serve different purposes, with test cases providing step-by-step instructions for test execution.
Test scenarios should align with real-world user behavior, cover edge cases, and remain reusable across various test phases.
When writing test scenarios, it is important to avoid excessive details and regularly refresh them to reflect application changes.
Test scenarios are crucial for efficient software testing, offering flexibility and adaptability in complex and dynamic environments.

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