Developer Shares Simple Python Number-Guessing Game on DEV Community

·4 views

A developer has published a beginner-friendly Python project called Guess Master on the DEV Community platform. The game has the computer randomly select a number between 1 and 100, challenging the player to identify it through repeated guesses. After each attempt, the program responds with 'Too High' or 'Too Low' as directional hints. The game tracks the total number of attempts and allows the player to quit at any time by typing a command. The source code, shared publicly, uses Python's built-in random module and a simple input loop to drive the gameplay.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Developer Builds Full-Featured Laravel Blog with Analytics, SEO, and Admin Panel

A developer has open-sourced a full-featured personal blogging platform built with Laravel 13.17 and PHP 8.3, going well beyond a basic CRUD application. The project includes a public-facing blog with categories, tags, search, comments, and an RSS feed, alongside a custom admin panel for content and user management. Visitor analytics are handled through custom middleware that filters out bots, AJAX calls, and duplicate visits using cookies and IP tracking. The platform also incorporates comprehensive SEO tools, including Open Graph tags, JSON-LD, sitemaps, and a robots.txt file, all configurable from the admin dashboard. The complete source code has been made publicly available on GitHub for developers looking to study real-world Laravel application architecture.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Self-Taught Developer from Bangladesh Launches Dev.to Journal to Document His Coding Journey

Afee Muhammod Wafy, a science student and self-taught web developer from Rangpur, Bangladesh, has introduced himself on the DEV Community platform. He describes his interest in programming as driven by curiosity rather than academic obligation, tracing his analytical mindset to his background in science education. Wafy plans to use his dev.to journal to document his growth in full-stack development, modern APIs, and AI technologies. He intends to share honest reflections on self-directed learning, debugging experiences, and observations on open-source culture. His portfolio and social profiles are publicly available as he seeks to connect with fellow developers and learners worldwide.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Why Fixed-Window Rate Limiters Have a Security Flaw and How to Fix It

Fixed-window rate limiters, commonly used in Express APIs to guard against DDoS and brute-force attacks, contain a critical boundary vulnerability that attackers can exploit. By firing the maximum allowed requests just before and just after a window resets, an attacker can double the permitted traffic within seconds without technically breaking any rules. A sliding window algorithm addresses this by continuously tracking request history rather than resetting on a rigid clock cycle. An optimized version uses just two integer counters per IP address — current and previous window counts — to estimate traffic with O(1) time and space complexity. This approach is especially important for sensitive systems like FinTech payment gateways and authentication endpoints where burst traffic can enable credential-stuffing attacks.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Engineer Achieves 28 TPS on Free Kaggle GPUs Using Tensor Parallelism and CUDA Graphs

A developer built ShardFlow v2.1, a distributed inference system that runs a Qwen2.5-7B language model split across two free Kaggle T4 GPU notebooks located in different US cloud regions. Because a single T4's 16GB VRAM barely fits the model with no room for a KV cache, tensor parallelism was used to divide layers between two nodes communicating via a low-cost AWS EC2 relay. Speculative decoding, where a smaller 0.5B draft model proposes batches of tokens for the larger model to verify, lifted throughput from roughly 5 TPS to 14 TPS by reducing costly WAN round trips. The biggest gain came from applying CUDA Graphs to the draft model's forward pass, collapsing thousands of individual Python-issued kernel launches into a single driver call and cutting draft generation time from 112ms to 25ms. The combined optimizations pushed peak throughput to 28.10 tokens per second across two cloud regions over public internet with near-zero infrastructure cost.

0 comments Read more at DEV Community