Packages the distutils stdlib module as a standalone package,
```
377K distutils.data
221K distutils.data.br
19K distutils.js
```
to reduce the minimal pyodide size.

Part of #1542 

This also,
 - adds documentation on what's supported or not in the stdlib
 - makes a few changes to `pyodide_build/buildall.py` to be able to add such stdlib packages as a dependency in other packages (which didn't work before). For instance, until there is a release with https://github.com/pypa/packaging/pull/396 micropip has a dependency on distutils.
Unvendor distutils. Packages the distutils stdlib module as a standalone package,
```
377K distutils.data
221K distutils.data.br
19K distutils.js
```
to reduce the minimal pyodide size.

Part of #1542 

This also,
 - adds documentation on what's supported or not in the stdlib
 - makes a few changes to `pyodide_build/buildall.py` to be able to add such stdlib packages as a dependency in other packages (which didn't work before). For instance, until there is a release with https://github.com/pypa/packaging/pull/396 micropip has a dependency on distutils.
# http://stackoverflow.com/questions/4651683/numpy-grouping-using-itertools-groupby-performance
# setup: import numpy as np ; N = 350000 ; values = np.array(np.random.randint(0,3298,size=N),dtype='u4') ; values.sort()  # noqa
# run: grouping(values)

# pythran export grouping(uint32 [])


def grouping(values):
    import numpy as np

    diff = np.concatenate(([1], np.diff(values)))
    idx = np.concatenate((np.where(diff)[0], [len(values)]))
    return values[idx[:-1]], np.diff(idx)

# http://stackoverflow.com/questions/4651683/numpy-grouping-using-itertools-groupby-performance
# setup: import numpy as np ; N = 350000 ; values = np.array(np.random.randint(0,3298,size=N),dtype='u4') ; values.sort()  # noqa
# run: grouping(values)

# pythran export grouping(uint32 [])


def grouping(values):
    import numpy as np

    diff = np.concatenate(([1], np.diff(values)))
    idx = np.concatenate((np.where(diff)[0], [len(values)]))
    return values[idx[:-1]], np.diff(idx)
