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’s
starmap
, starfilter
, and the other star*
/rstar*
methods are replaced by the and
star
function adapters, which compose with every
rstar
`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
dstar
fastcore.aio
module: ,
run_sync
, and
iter_sync
moved there from
ctx_sync
net
, and ,
maybe_await
,
then
,
mapa
,
acache
,
reawaitable
, and the other async utilities moved there from
is_async_callable
xtras
. and the config file functions moved from
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, 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 functionsfastcore.foundation
: Mixins, delegation, composition, and morefastcore.xtras
: Utility functions to help with functional-style programming, parallel processing, and more
To get started, we recommend you read through the fastcore tour.
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
.