fastcore v2

Fastcore v2 was released in July 2026, removing or relocating several APIs and requiring Python 3.11 or later. The update replaces Param with type annotations, moves async helpers to a new fastcore.aio module, and removes parallel_gen in favor of stdlib patterns. Users needing old APIs can pin fastcore<2.

Note In July 2026 we released fastcore v2, which removes or relocates a number of APIs that had accumulated better alternatives. If you use from fastcore.utils import or fastcore.all , most of these changes won’t affect you. The breaking changes: Param is gone from fastcore.script ; use plain type annotations with docments, or typing.Annotated type, "help" , optionally with a dict of argparse arguments for advanced features. L https://fastcore.fast.ai/foundation.html l ’s starmap , starfilter , and the other star / rstar methods are replaced by the and https://fastcore.fast.ai/foundation.html star star function adapters, which compose with every https://fastcore.fast.ai/foundation.html rstar rstar method e.g. https://fastcore.fast.ai/foundation.html l L t.map star f ; relatedly, spread is replaced by , and https://fastcore.fast.ai/foundation.html star star dspread is renamed to . Async helpers now live in the new https://fastcore.fast.ai/basics.html dstar dstar fastcore.aio module: , https://fastcore.fast.ai/aio.html run sync run sync , and https://fastcore.fast.ai/aio.html iter sync iter sync moved there from https://fastcore.fast.ai/aio.html ctx sync ctx sync net , and , https://fastcore.fast.ai/aio.html maybe await maybe await , https://fastcore.fast.ai/aio.html then then , https://fastcore.fast.ai/aio.html mapa mapa , https://fastcore.fast.ai/aio.html acache acache , https://fastcore.fast.ai/aio.html reawaitable reawaitable , and the other async utilities moved there from https://fastcore.fast.ai/aio.html is async callable is async callable xtras . and the config file functions moved from https://fastcore.fast.ai/xtras.html config Config foundation to xtras . fastcore.net lost its request builders urlrequest , urlsend , do request , urlcheck and clean type str is gone. parallel gen is removed; the stdlib ProcessPoolExecutor initializer pattern replaces it fastai’s parallel tokenize shows the recipe . Python 3.11 or later is now required. If you need the old APIs, pin fastcore<2 .Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. fastcore uses this flexibility to add to Python features inspired by other languages we’ve loved, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and clean up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s list type. To install fastcore run: conda install fastcore -c fastai if you use Anaconda, which we recommend or pip install fastcore . For an editable install https://stackoverflow.com/questions/35064426/when-would-the-e-editable-option-be-useful-with-pip-install , clone this repo and run: pip install -e ". dev " . fastcore is tested to work on Ubuntu, macOS and Windows versions tested are those shown with the -latest suffix here https://docs.github.com/en/actions/reference/specifications-for-github-hosted-runners supported-runners-and-hardware-resources . fastcore contains many features, including: fastcore.test : Simple testing functions fastcore.foundation : Mixins, delegation, composition, and more fastcore.xtras : Utility functions to help with functional-style programming, parallel processing, and more To get started, we recommend you read through the fastcore tour https://fastcore.fast.ai/tour.html . After you clone this repository, please run nbdev install hooks in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks e.g. which cells you ran which causes unnecessary merge conflicts. To run the tests in parallel, launch nbdev test . Before submitting a PR, check that the local library and notebooks match. - If you made a change to the notebooks in one of the exported cells, you can export it to the library with nbdev prepare . - If you made a change to the library, you can export it back to the notebooks with nbdev update .