fastcore 2.1.11

Python supercharged for fastai development

Welcome to fastcore

[!NOTE]

fastcore v2

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’s starmap, starfilter, and the other star*/rstar* methods are replaced by the star and rstar function adapters, which compose with every L method (e.g. t.map(star(f))); relatedly, spread is replaced by star, and dspread is renamed to dstar. Async helpers now live in the new fastcore.aio module: run_sync, iter_sync, and ctx_sync moved there from net, and maybe_await, then, mapa, acache, reawaitable, is_async_callable, and the other async utilities moved there from xtras. Config and the config file functions moved from 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.

Getting started

To install fastcore run: conda install fastcore -c fastai (if you use Anaconda, which we recommend) or pip install fastcore. For an editable 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).

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.

Contributing

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.