When is not a good time to use python generators?

Use a list instead of a generator when:

1) You need to access the data multiple times (i.e. cache the results instead of recomputing them):

for i in outer:           # used once, okay to be a generator or return a list    for j in inner:       # used multiple times, reusing a list is better         ...

2) You need random access (or any access other than forward sequential order):

for i in reversed(data): ...     # generators aren't reversibles[i], s[j] = s[j], s[i]          # generators aren't indexable

3) You need to join strings (which requires two passes over the data):

s = ''.join(data)                # lists are faster than generators in this use case

4) You are using PyPy which sometimes can't optimize generator code as much as it can with normal function calls and list manipulations.

In general, don't use a generator when you need list operations, like len(), reversed(), and so on.

There may also be times when you don't want lazy evaluation (e.g. to do all the calculation up front so you can release a resource). In that case, a list expression might be better.

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Profiling your code is the only way to know if what you're doing has any effect at all.

Most usages of xrange, generators, etc are over static size, small datasets. It's only when you get to large datasets that it really makes a difference. range() vs. xrange() is mostly just a matter of making the code look a tiny little bit more ugly, and not losing anything, and maybe gaining something.

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