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Computer Science and Programming

Computer Science and Programming

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Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science

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📈 Análisis del canal de Telegram Computer Science and Programming

El canal Computer Science and Programming (@computer_science_and_programming) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 140 493 suscriptores, ocupando la posición 802 en la categoría Tecnologías y Aplicaciones y el puesto 88 en la región Italia.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 140 493 suscriptores.

Según los últimos datos del 30 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -752, y en las últimas 24 horas de -56, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.74%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.89% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 10 875 visualizaciones. En el primer día suele acumular 2 656 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 14.
  • Intereses temáticos: El contenido se centra en temas clave como sellerflash, github, developer, pricing, waybienad.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_sc...

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 31 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

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140 493
Suscriptores
-5624 horas
-2987 días
-75230 días
Archivo de publicaciones
Avoid SELECT *, even on a single-column tables TLDR Avoid using SELECT * in SQL queries, even for single-column tables, as it
Avoid SELECT *, even on a single-column tables
TLDR Avoid using SELECT * in SQL queries, even for single-column tables, as it can lead to inefficient database operations and performance issues. Explicitly selecting only necessary columns allows for better optimization, reducing overhead related to deserialization, network costs, and query unpredictability. Specific column selection also facilitates easier code maintenance and database schema updates.
🔗 https://medium.com/@hnasr/avoid-select-even-on-a-single-column-tables-d6deed7b4aee

How Senior Software Engineers Document Their Project Software engineers often dislike documenting projects, but it distinguis
How Senior Software Engineers Document Their Project
Software engineers often dislike documenting projects, but it distinguishes good engineers from bad. The Architectural Decision Record (ADR) is highlighted as an effective way to document architectural changes, providing benefits like aiding memory, improving team learning, and assisting future developers. The post outlines the importance of ADRs and provides a template and examples for implementation.
🔗 https://dev.to/koladev/how-senior-software-engineers-document-their-project-1nf4

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Repost from World’s History
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Repost from World’s History
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From Junior to Senior Developer with ChatGPT ChatGPT and similar AI tools can significantly aid developers by analyzing code,
From Junior to Senior Developer with ChatGPT
ChatGPT and similar AI tools can significantly aid developers by analyzing code, suggesting improvements, writing tests, and more. Their effectiveness depends on clear, specific prompts. While they are not designed to solve new or niche problems independently, they excel in tasks like code contextualization, reviews, and documentation. Tools like GitHub Copilot leverage additional context to provide more relevant suggestions, bridging the gap between junior and senior developer roles.
🔗 https://www.codemotion.com/magazine/ai-ml/from-junior-to-senior-developer-with-chatgpt

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Toasts are Bad UX TLDR Toasts often appear far from the user's focus, leading to jarring interactions. For example, YouTube's
Toasts are Bad UX
TLDR Toasts often appear far from the user's focus, leading to jarring interactions. For example, YouTube's toast notifications conflict with other on-screen actions. A redesign suggests directly integrating feedback into user actions, such as placing indicators near interacted elements. Examples from Gmail and clipboard actions further illustrate unnecessary toast usage. Ultimately, no feedback is worse, but there are better methods than relying on toasts.
🔗 https://maxschmitt.me/posts/toasts-bad-ux

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11 open source AI projects that developers will love TLDR Explore 11 open source AI projects aimed at easing software develop
11 open source AI projects that developers will love
TLDR Explore 11 open source AI projects aimed at easing software development. Projects like Upscayl enhance image resolution, Nyro automates mundane tasks, and Wren AI translates natural language into SQL. Tools like Geppetto and E2B sandboxes integrate AI with productivity tools, while DSPy and Guardrails optimize AI model training and accuracy. These projects demonstrate the potential of AI in transforming everyday tasks and development workflows.
🔗https://www.infoworld.com/article/3566915/11-open-source-ai-projects-that-developers-will-love.html

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Developers be like
Developers be like

10 Best Resources to Learn Software Architecture in 2025 TLDR Mastering software architecture is crucial for handling complex
10 Best Resources to Learn Software Architecture in 2025
TLDR Mastering software architecture is crucial for handling complex systems and transitioning from a developer role to an architect role. Essential resources include books like 'Designing Data-Intensive Applications' and courses such as 'The Complete Microservices and Event-Driven Architecture' on Udemy. Additionally, whitepapers and engineering blogs provide valuable insights. These resources cover various architectural styles, principles, and real-world challenges, helping you design scalable, maintainable, and high-performing systems.
🔗 https://medium.com/javarevisited/10-best-resources-to-learn-software-architecture-in-2025-2524ac91dc76

Using GPT-4o for web scraping TLDR A developer experimented with using GPT-4o's structured outputs for web scraping, creating
Using GPT-4o for web scraping
TLDR A developer experimented with using GPT-4o's structured outputs for web scraping, creating an AI-assisted web scraper. While the model performed well with simple and complex tables, it struggled with combined rows and generating XPaths. Cost is a concern due to the model's character volume requirements. Future improvements could include better UX through capturing browser events and further refining HTML data cleanup.
🔗 https://blancas.io/blog/ai-web-scraper

What is a Load Balancer? TLDR A load balancer distributes network or application traffic across multiple servers to ensure av
What is a Load Balancer?
TLDR A load balancer distributes network or application traffic across multiple servers to ensure availability, reliability, and performance. There are different types of load balancers, including hardware, software, cloud-based, Layer 4, Layer 7, and Global Server Load Balancing. Load balancers improve scalability and help manage large-scale applications efficiently. The post also touches on various design patterns for Kubernetes and highlights a sponsored service by QA Wolf for improved QA cycles.
🔗 https://blog.bytebytego.com/p/ep123-what-is-a-load-balancer

How does Garbage Collection work? TLDR Garbage collection is a crucial automatic memory management feature used in many progr
How does Garbage Collection work?
TLDR Garbage collection is a crucial automatic memory management feature used in many programming languages. Java offers multiple garbage collectors tailored to different scenarios, Python employs reference counting alongside a cyclic collector to handle circular references, and GoLang utilizes a concurrent mark-and-sweep garbage collector to minimize application pauses. Additional topics include tools for designing fault-tolerant systems and key system design trade-offs.
🔗 https://blog.bytebytego.com/p/ep125-how-does-garbage-collection

Open source tools to boost your productivity TLDR Open source technology offers alternatives to many proprietary software too
Open source tools to boost your productivity
TLDR Open source technology offers alternatives to many proprietary software tools, providing benefits like added transparency, customizability, and security. Highlighted tools include Penpot for design, Cal.com for scheduling, Screenity for screen recording, Jitsi for video conferencing, Nextcloud for cloud storage, Ghost for publishing, and more. Each offers features to help individuals and businesses move away from Big Tech incumbents without compromising productivity.
🔗 https://techcrunch.com/2024/08/11/a-not-quite-definitive-guide-to-open-source-alternative-software/