Viewing profile — jammycrisp

Yep! Both msgspec ( https://jcristharif.com/msgspec/supported-types.html#datacla... ) and orjson support encoding dataclasses to JSON natively.

> we measure the number of instructions and memory/cache accesses through CPU instrumentation performed with Valgrind. This approach gives repeatable and consistent results that co…

starlite was the original name, it was recently renamed to litestar due to comments about how easily confused "starlette" and "starlite" are.

+1 for litestar[1]. The higher bus-factor is nice, and I like that they're working to embrace a wider set of technologies than just pydantic. The framework currently lets you model…

If you like cattrs, you _might_ be interested in trying out my msgspec library [1]. It works out-of-the-box with attrs objects (as well as its own faster `Struct` types), while bei…

> Maybe it was very slow before That is at least partly the case. I maintain msgspec[1], another Python JSON validation library. Pydantic V1 was ~100x slower at encoding/decoding/v…

While it's definitely much faster than pydantic V1 (which is a huge accomplishment!), it's still not exactly what I'd call "fast". I maintain msgspec ( https://github.com/jcrist/ms…

Thanks, glad you like it!

While I agree that there are ways to write a faster validation library in python, there are also benefits to moving the logic to native code. msgspec[1] is another parsing/validati…

It looks like pydantic-core is distributing musllinux wheels, which should work fine on alpine. Fwiw tooling like cibuildwheel makes building and publishing wheels for all the comm…

Are there any necessary features that you've found missing in msgspec? One of the design goals for msgspec (besides much higher performance) was simpler usage. Fewer concepts to wr…

If you're primarily targeting Python as an application layer, you may also want to check out my msgspec library[1]. All the perf benefits of e.g. yyjson, but with schema validation…

Pytest has an equally deprecating option for a different "use case": disable_test_id_escaping_and_forfeit_all_rights_to_community_support = True https://docs.pytest.org/en/6.2.x/pa…

Integrating `dataclass` more into the language builtins might be nice, if only that it may allow/encourage a more native and performant implementation. Using a dataclass right now …

You might be interested in checking out Ibis ( https://ibis-project.org/ ). It provides a dataframe-like API, abstracting over many common execution engines (duckdb, postgres, bigq…

For creating images without docker from conda/mamba environments, there's also the existing `conda-docker` tool https://github.com/conda-incubator/conda-docker .

There's also https://github.com/llllllllll/phorth , an implementation of forth that compiles to cpython bytecode

For my own "fast" projects[1] I've taken to providing benchmarks, but adding a big 'ol caveat at the top describing ways in which the benchmark may not reflect reality. Some people…

GitHub issue: https://github.com/psf/requests/issues/6140

> I should mention that spyql leverages orjson, which has a considerable impact on performance Even with orjson, you're still paying the cost of creating a new PyObject for every n…