Computer Science and Programming
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
Ko'proq ko'rsatish📈 Telegram kanali Computer Science and Programming analitikasi
Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 140 580 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 804-o'rinni va Italiya mintaqasida 88-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 140 580 obunachiga ega bo‘ldi.
28 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -743 ga, so‘nggi 24 soatda esa -38 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 7.56% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.72% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 10 623 marta ko‘riladi; birinchi sutkada odatda 2 417 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 14 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent sellerflash, github, developer, pricing, waybienad kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“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...”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 29 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
Kepler.gl is a WebGL-powered geospatial data visualization tool designed for analyzing and visualizing large-scale datasets in web browsers. Built with high-performance rendering capabilities, it enables interactive exploration of geographic data. Foursquare Studio extends kepler.gl's framework as a free analytics platform with regular feature updates.
WordPress and Django CMS serve different audiences and use cases. WordPress excels in ease of use, making it ideal for bloggers, small businesses, and non-developers who want quick setup with extensive themes and plugins. Django CMS offers superior performance and security out-of-the-box but requires coding expertise and higher development costs. WordPress wins for content management, customization without coding, community support, and affordability. Django CMS is better for complex enterprise applications requiring custom development and high scalability. Most users should choose WordPress for its user-friendly approach, while Django CMS suits developers building sophisticated web applications.
Construct 3 is a browser-based game development platform that allows users to create games without coding knowledge or with JavaScript support. The tool emphasizes ease of use and accessibility for game creation directly in web browsers.
SuperFile is a modern terminal file manager written in Go that offers a colorful, icon-rich interface as an alternative to traditional tools like Midnight Commander. It features multiple panels, keyboard-driven navigation, vim-compatible keybindings, and integrates with external editors while maintaining simplicity and usability for command-line file operations.
Inertia.js serves as a bridge between Laravel backends and JavaScript frontends (React/Vue), enabling single-page applications without complex API management. It allows teams to split work effectively - backend developers focus on Laravel logic while frontend developers handle client-side code. Key features include deferred props for performance optimization and history encryption for security. The framework maintains separation between backend and frontend concerns while providing seamless communication, making it ideal for developers who want Laravel's power with modern JavaScript frameworks.
Building confidence as a software engineer requires a structured approach focusing on six key areas: mastering one programming language deeply, writing unit tests with continuous integration, making refactoring a regular habit, pairing with other developers, reading technical books thoughtfully, and teaching others what you learn. The author emphasizes that understanding fundamentals in one language transfers to others, unit tests provide safety nets for bold changes, clean code through refactoring improves maintainability, pairing accelerates learning through different perspectives, quality books teach thinking patterns beyond tutorials, and teaching solidifies understanding while helping others.
Google has launched Mangle, a new programming language built on Datalog specifically designed for deductive database programming. Mangle offers powerful features including aggregation support, function calls within queries, optional type checking, recursive rules, and the ability to work across multiple databases. Unlike SQL or Python, Mangle is declarative and allows complex data reasoning without extensive code. It's particularly useful for data integration, graph analysis, ontology reasoning, and complex data analysis across industries like finance and AI. The language is available as an open-source project on GitHub with documentation and examples for developers to get started.
Spin 3.4 introduces HTTP/2 support for outgoing requests, enabling seamless integration with gRPC-based backends and improving performance through multiplexed connections. The release adds PostgreSQL connection pooling for better database performance and expands supported data types including UUID, JSONB, and array types. Additionally, Spin templates now include schema directives in spin.toml files for automatic validation and code completion in editors.
A critique of the 996 work culture (9am-9pm, 6 days a week) promoted by some tech companies and founders. The author argues that while intensity and dedication matter, sustainable productivity comes from output rather than hours worked. Excessive work schedules lead to burnout and are particularly problematic when founders impose them on employees who lack the same risks and leverage. True success requires balancing professional commitment with personal life and well-being.
Explores the 9 layers of modern software architecture from presentation to infrastructure, explains the key differences between concurrency and parallelism in computing, compares JWT and PASETO authentication tokens, provides a Linux Cron scheduling cheatsheet, and introduces AI agents versus Model Context Protocol (MCP) for AI system integration.
A practical guide to replacing pip with uv in Dockerized Python applications, showing how to achieve 10x faster package installation speeds. Covers migrating from requirements.txt to pyproject.toml, configuring Docker environment variables, and using uv commands for dependency management. Includes specific examples for Flask and Django projects with detailed Dockerfile modifications and shell scripts for managing dependencies.
Context engineering is emerging as a critical skill for AI engineers, focusing on building dynamic systems that provide LLMs with the right information, tools, and formatting to accomplish tasks reliably. Unlike traditional prompt engineering, context engineering emphasizes providing complete, structured context rather than clever wording. The approach addresses the primary cause of agent failures: inadequate context rather than model limitations. Key components include dynamic information retrieval, appropriate tool selection, proper formatting, and comprehensive system design. LangGraph and LangSmith are positioned as enabling technologies for implementing effective context engineering practices.
Go 1.25 introduces json/v2 package with significant changes from v1. Key improvements include new MarshalWrite/UnmarshalRead functions for direct I/O operations, streaming encode/decode via jsontext package, configurable options for formatting and behavior, enhanced field tags (inline, format, unknown), flexible custom marshalers with MarshalFunc/UnmarshalFunc, and changed default behaviors (nil slices/maps marshal to []/{}). Performance shows similar marshaling speed but 2.7x-10.2x faster unmarshaling. The package remains experimental requiring GOEXPERIMENT=jsonv2 flag.
A Canonical hiring lead shares insider guidance on successfully applying for jobs at the company. Key advice includes applying for the right roles rather than spraying multiple applications, demonstrating specific achievements instead of generic claims, preparing thoroughly for interviews, and avoiding AI-generated content. The company receives around one million applications annually for 300-400 positions, emphasizing the importance of standing out through concrete examples of excellence, initiative, and technical contributions. Canonical uses human reviewers rather than AI screening and values academic achievement as an indicator of personal qualities alongside professional experience.
A comprehensive performance analysis of 11 different methods to detect vowels in strings using Python. The study reveals that regex methods significantly outperform traditional loops due to CPython's interpreter overhead and optimized C implementations. Through bytecode analysis and CPython source code examination, the author demonstrates how regex engines use bitmap lookups for character matching, making them surprisingly faster than simple Python loops, especially for longer strings.
