One powerful tool in Python3 for speeding up applications that involve significant amounts of I/O is the ThreadPoolExecutor from the concurrent.futures module. The concurrent.futures module can help ...

I wrote a function that was calling an LLM API. It waited for 2–3 seconds to respond and then processed it. It had to do this multiple times and I wanted to optimize it. Asked the LLM — it told me to ...

How much faster could your Python code run (if you used 100s of thread workers)? The ThreadPoolExecutor class provides modern thread pools for IO-bound tasks. This is not some random third-party ...

Spans created in tasks that run in a ThreadPoolExecutor should be included in the transactions sent to Sentry when AsyncioIntegration is enabled. Spans created in tasks that run in a ...