3 posts tagged with "runtime-checks"

⚡ How Fast is Typeguard? Performance Benchmarks and Analysis​

Understanding the speed of Typeguard is essential when integrating it into performance-critical Python applications. Since Typeguard performs runtime reflection and checking, it inevitably adds overhead. However, the time added is typically measured in microseconds (µs), making it extremely fast for single invocations.

The key factors determining the speed are the complexity of the type signature and the size of the data structure being checked.

When Typeguard is used in scenarios where functions are invoked thousands of times per request (e.g., in tight loops or high-frequency processing), understanding the cumulative performance impact is essential. This article delves into how invocation frequency and type signature complexity influence Typeguard's overhead and offers strategies to mitigate performance hits while maintaining type safety.

When implementing runtime checks like Typeguard, the primary concern is the performance overhead it adds to production code, especially in high-throughput applications that rely on fast I/O operations (like database queries).

The short answer is: Typeguard adds a measurable execution overhead, but it is often negligible compared to the time spent on I/O (Database operations).

Here is a breakdown of the performance implications and when you should be concerned.