FastAPI + Redis: Basic Application of Caching and State Management
Web development often faces challenges of handling rapid request responses and sharing temporary state across multiple requests. The combination of FastAPI (a high-performance asynchronous framework) and Redis (an in-memory database) effectively addresses these issues. FastAPI supports high concurrency, while Redis, with its fast read/write speed and expiration time features, can cache frequently accessed, low-updating data (such as Fibonacci calculation results) to reduce redundant computations and store temporary states (such as user access counters) for cross-request sharing. This article introduces environment setup (installing FastAPI, Redis client, and starting Redis), basic connections (using utility functions to manage Redis clients with `decode_responses=True` to ensure string results), and demonstrates applications through two examples: caching (Fibonacci calculation results) and state management (user access counts). It also mentions dependency injection for code optimization and notes on Redis persistence, connection pooling, and key naming conventions in production environments.
Read MoreFastAPI State Management: Simple Implementation of Global Variables and Caching
In FastAPI, two common approaches for state management are global variables and caching. Global variables are the simplest way to share state, usable directly in single-process environments but requiring asyncio.Lock to prevent race conditions in multi-request scenarios. Their limitations include process isolation issues, memory dependency, and data loss risks. Caching is more efficient and categorized into three types: in-memory caching (using dictionaries or the cachetools library, supporting LRU/TTL strategies), and distributed caching (e.g., Redis, suitable for cross-service sharing and persistence). Comparison: Global variables suit single-process, simple scenarios, while caching is ideal for high-frequency access, distributed systems, or data requiring persistence. Practical recommendations: Use global variables or cachetools in development, and distributed caches like Redis in production to avoid cross-process issues with global variables.
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