How Redis TTL and Eviction Policies Prevent Memory Crashes in Production

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Redis manages memory through two core mechanisms: key expiration and eviction policies. Expiration allows keys to self-delete after a set time-to-live (TTL), ensuring cached data stays fresh without manual cleanup. Redis uses both lazy expiration—checking TTL on access—and periodic active expiration to remove stale keys. When Redis hits its configured memory ceiling (maxmemory), the eviction policy determines whether it discards least-used keys or rejects new writes entirely. Choosing the right policy, such as allkeys-lru for pure caches or noeviction for critical data stores, is essential to preventing out-of-memory failures in production.

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Python OOP Day 3: Inheritance, Polymorphism, and Duck Typing Explained

A tutorial series on Python object-oriented programming has reached its third installment, focusing on inheritance and polymorphism. The guide explains three types of inheritance — single, multilevel, and multiple — showing how child classes can reuse and extend parent class behavior. It also covers method overriding and the built-in super() function, which allows child classes to call parent methods without duplicating code. Polymorphism and duck typing are demonstrated through a practical payroll system where different employee types respond to the same method call in their own way. The article includes working code examples and diagrams to illustrate how these concepts apply in real-world Python projects.

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All 236 Tests Passed Locally, Yet the Release Was Broken — Here's Why

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ProgrammingDEV Community ·

Developer finds Claude Code usage-limit hook fires before transcript is fully written

A developer building a Telegram notification tool for Claude Code discovered a subtle timing bug that caused usage-limit alerts to silently fail. When Claude Code hits an account usage limit, it triggers a StopFailure hook, but the session transcript is written asynchronously, meaning the hook can fire before the rate-limit data is flushed to disk. In one logged incident, the developer's code read the transcript just 19.7 milliseconds before Claude Code finished writing it, causing the limit-detection logic to find nothing and fall back to a generic error ping. Because a fallback notification still arrived each time, the failure was invisible until the developer noticed the expected limit-specific message was absent. The finding highlights that the hook payload's transcript path only guarantees the file exists, not that the current turn's data has been fully written to it.

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ProgrammingDEV Community ·

How JavaScript Handles Async Tasks: The Event Loop and Concurrency Model Explained

JavaScript is a single-threaded language, meaning it can execute only one operation at a time, yet it manages asynchronous tasks like API calls, timers, and user interactions without freezing the browser. This is made possible by JavaScript's concurrency model, which delegates time-consuming operations to browser Web APIs or Node.js APIs while the main thread continues running. Once an asynchronous task completes, its callback is placed in the Callback Queue and later picked up by the Event Loop for execution. The Call Stack tracks active function calls using a Last In, First Out structure, and works alongside the Microtask Queue and Macrotask Queue to determine execution order. Understanding these components helps developers write more efficient, non-blocking JavaScript code for modern web applications.

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