Joblib

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- Fix a security issue where ``eval(pre_dispatch)`` could potentially run
arbitrary code. Now only basic numerics are supported.
https://github.com/joblib/joblib/pull/1327

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- Fix byte order inconsistency issue during deserialization using joblib.load
in cross-endian environment: the numpy arrays are now always loaded to
use the system byte order, independently of the byte order of the system
that serialized the pickle.
https://github.com/joblib/joblib/pull/1181

- Fix joblib.Memory bug with the ``ignore`` parameter when the cached function
is a decorated function.
https://github.com/joblib/joblib/pull/1165

- Fix `joblib.Memory` to properly handle caching for functions defined
interactively in a IPython session or in Jupyter notebook cell.
https://github.com/joblib/joblib/pull/1214

- Update vendored loky (from version 2.9 to 3.0) and cloudpickle (from
version 1.6 to 2.0)
https://github.com/joblib/joblib/pull/1218

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- Add check_call_in_cache method to check cache without calling function.
https://github.com/joblib/joblib/pull/820

- dask: avoid redundant scattering of large arguments to make a more
efficient use of the network resources and avoid crashing dask with
"OSError: [Errno 55] No buffer space available"
or "ConnectionResetError: [Errno 104] connection reset by peer".
https://github.com/joblib/joblib/pull/1133

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- Make `joblib.hash` and `joblib.Memory` caching system compatible with `numpy
>= 1.20.0`. Also make it explicit in the documentation that users should now
expect to have their `joblib.Memory` cache invalidated when either `joblib`
or a third party library involved in the cached values definition is
upgraded. In particular, users updating `joblib` to a release that includes
this fix will see their previous cache invalidated if they contained
reference to `numpy` objects.
https://github.com/joblib/joblib/pull/1136

- Remove deprecated `check_pickle` argument in `delayed`.
https://github.com/joblib/joblib/pull/903

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- Fix a spurious invalidation of `Memory.cache`'d functions called with
`Parallel` under Jupyter or IPython.
https://github.com/joblib/joblib/pull/1093

- Bump vendored loky to 2.9.0 and cloudpickle to 1.6.0. In particular
this fixes a problem to add compat for Python 3.9.

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- Fix a problem in the constructors of Parallel backends classes that
inherit from the `AutoBatchingMixin` that prevented the dask backend to
properly batch short tasks.
https://github.com/joblib/joblib/pull/1062

- Fix a problem in the way the joblib dask backend batches calls that would
badly interact with the dask callable pickling cache and lead to wrong
results or errors.
https://github.com/joblib/joblib/pull/1055

- Prevent a dask.distributed bug from surfacing in joblib's dask backend
during nested Parallel calls (due to joblib's auto-scattering feature)
https://github.com/joblib/joblib/pull/1061

- Workaround for a race condition after Parallel calls with the dask backend
that would cause low level warnings from asyncio coroutines:
https://github.com/joblib/joblib/pull/1078