🧘‍♂️️Lightweight fault tolerance primitives for your resilient and modern Python microservices

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Hyx (/ˈhʌɪx/) is a set of well-known stability patterns that are commonly needed when you build microservice-based applications. Hyx is meant to be Hystrix (Java), resilience4j (Java) or Polly (C#) but for the Python world.

Key Features

• Implements five commonly used resiliency patterns with various configurations based on advice and experience of industry leaders (e.g. AWS, Google, Netflix)
• Idiomatic Pythonic implementation based on decorators and context managers
• AsyncIO Native Implementation
• Built-in telemetry support for OpenTelemetry, Prometheus, and StatsD
• Lightweight. Readable Codebase. High Test Coverage

Requirements

• Python 3.9+
• AsyncIO-powered applications (no sync support?)

Installation

Hyx can be installed from PyPi:

pip install hyx
or via uv
uv add hyx

Optional Dependencies

For telemetry support, install with the appropriate extras:

pip install hyx[otel]        # OpenTelemetry
pip install hyx[prometheus]  # Prometheus
pip install hyx[statsd]      # StatsD

Component Map

| Component | Problem | Solution | Implemented? | |-------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------| | 🔁 Retry | Failures happen sometimes, but they self-recover after a short time | Automatically retry operations on temporary failures | ✅ | | 💾 Cache | | | | | ⚡️ Circuit Breaker | When downstream microservices become overloaded, sending even more load only makes things worse | Temporarily stop sending requests to failing microservices when error thresholds are exceeded. Then check if the pause helped them recover | ✅ | | ⏱ Timeout | Sometimes operations take too long. We can't wait forever, and after a certain point success becomes unlikely | Bound waiting to a reasonable amount of time | ✅ | | 🚰 Bulkhead | Without limits, some code can consume too many resources, bringing down the whole application (and upstream services) or slowing down other parts | Limit the number of concurrent calls, queue excess calls, and fail calls that exceed capacity | ✅ | | 🏃‍♂️ Rate Limiter | A microservice can be called at any rate, including one that could bring it down if triggered accidentally | Limit the rate at which your system can be accessed | ✅ | | 🤝 Fallback | Nothing guarantees that your dependencies will work. What do you do when they fail? | Degrade gracefully by providing default values or placeholders when dependencies are down | ✅ |

Inspired by Polly's Resiliency Policies

Acknowledgements

• resilience4j/resilience4j
• Netflix/Hystrix
• slok/goresilience
• App-vNext/Polly
• Diplomatiq/resily