A service keeps an in-memory cache shared by its request handlers. Traditional multiprocess deployment duplicates that state and adds coordination whenever workers need to agree. Free-threaded Python…

An inventory endpoint receives JSON containing a SKU and quantity. The useful path is short: turn bytes into a typed object, reject invalid data clearly, and call the handler. Represent the payload…

A webhook receives an order, calls a synchronous payment SDK, writes through a blocking database client, and returns JSON. Converting every call site to async would add ceremony while both…

Typed request bodies should not require a tower of validation layers. pip install dexpot ​ class Order(msgspec.Struct): sku: str quantity: int ​ dexpot decodes and validates the body in one fused…

Your API is fine at normal traffic. Then its queue grows and tail latency explodes. dexpot attacks saturation directly with a bounded pool on GIL builds and explicit 503 shedding when full. ​ pip…

You have a sync SDK, a blocking database client, and a plain Python handler. Async integration often adds thread-pool boundaries or rewrites. ​ pip install "dexpot[cli]" dexpot serve main:app ​…

dexpot dresses for the Python runtime it has. Free-threaded build? Threads across cores. Classic GIL? Bounded pool with overload shedding. Same synchronous API, fewer costume changes for you.