itertools.flatten()? and copying generators/iterators.

[Alex Martelli]

Peter Otten wrote:
   ...
> def flatten_dict(s, isScalar):
>     try:
>         scalar = isScalar[s.__class__]
>     except KeyError:
>         t = s.__class__
>         try:
>             s = iter(s)
>         except TypeError:
>             scalar = isScalar[t] = True
>         else:
>             scalar = isScalar[t] = False
> 
>     if scalar:
>         yield s
>     else:
>         for elem in s:
>             for subelem in flatten_dict(elem, isScalar):
>                 yield subelem

Neat: "caching" (aka memoizing) IS a good general technique
for optimization, and this is a cool and un-obvious application.


Alex