Fastcore

New Features

- add `L.setattrs`, inspired by Saul Pwanson ([117](https://github.com/fastai/fastcore/issues/117))
- move `Config` from `nbdev` ([116](https://github.com/fastai/fastcore/issues/116))
- add `nested_attr` and use it in `L.attrgot` ([115](https://github.com/fastai/fastcore/issues/115))

Deprecations (will be removed in future release)

- `patch_property`: use `patch(as_prop=True)` instead

New Features

- New param `cast` for `store_attr` and new decorator `with_cast` ([114](https://github.com/fastai/fastcore/issues/114))
- add `L.insert` and `exec_local` ([113](https://github.com/fastai/fastcore/issues/113))
- Patch decorator with optional argument ([110](https://github.com/fastai/fastcore/pull/110)), thanks to [Salehbigdeli](https://github.com/Salehbigdeli)
- Make typedispatch decorator more general ([106](https://github.com/fastai/fastcore/pull/106)), thanks to [Salehbigdeli](https://github.com/Salehbigdeli)

Bugs Squashed

- Fix default in oper ([112](https://github.com/fastai/fastcore/pull/112)), thanks to [Salehbigdeli](https://github.com/Salehbigdeli)
- Inconsistency with `cmp_instance` and `typedispatch` because of binary sort algorithm ([100](https://github.com/fastai/fastcore/issues/100))

New Features

- add `ignore_ex=False` and `as_bytes=False` params to `run` ([108](https://github.com/fastai/fastcore/issues/108))
- `AttrDict`: a `dict` subclass that also provides access to keys as attrs; and change `dict2obj` to create `AttrDict`s instead of `SimpleNamespace`s ([107](https://github.com/fastai/fastcore/issues/107))

New Features

- `run`: flexibly run an external process and raise exception if it fails ([105](https://github.com/fastai/fastcore/issues/105))

New Features

- add `threadpool=False` param to `parallel` to use threads instead of processes ([102](https://github.com/fastai/fastcore/issues/102))

New Features

- add `L.map_filter` and `L.map_first` ([97](https://github.com/fastai/fastcore/issues/97))
- These support some nice refactorings, like changing from this:
python
d = []
for c in cs:
m = f(c)
if not m:
continue
d.append(m.group(1))

to this:
python
d = cs.map_filter(f).map(Self.group(1))