from itertools import count class indexediterator(object): # Helper class to be returned as the actual generator with # indexing; wraps the generator in an iterator that also # supports item retrieval by index. def __init__(self, gen): self.__gen = gen # the generator that created us self.__iter = gen._iterable() def __iter__(self): # Return the generator function; note that we return # the same one each time, which matches the semantics # of actual generators (i.e., once the generator function # is called, iter(gen) returns the same iterator and does # not reset the state) return self.__iter def next(self): # Return next item from generator term = next(self.__iter) if term == self.__gen.sentinel: raise StopIteration return term def __len__(self): # If the generator is exhausted, we know its length, so # we can use that information; if not, we raise TypeError, # just like any other object with no length result = self.__gen._itemcount() if result is None: raise TypeError, "object of type %s has no len()" % \ self.__class__.__name__ return result def __getitem__(self, index): # Return the item at index, advancing the generator if # necessary; if the generator is exhausted before index, # raise IndexError, just like any other sequence when an # index out of range is requested result = self.__gen._retrieve(index) if result is self.__gen.sentinel: raise IndexError, "sequence index out of range" return result class IndexedGenerator(object): """Make a generator indexable like a sequence. """ sentinel = object() def __init__(self, gen): # The underlying generator self.__gen = gen # Memoization fields self.__cache = [] self.__iter = None self.__empty = False def _retrieve(self, n): # Retrieve the nth item from the generator, advancing # it if necessary # Negative indexes are invalid unless the generator # is exhausted, so check that first if n < 0: end = self._itemcount() if (end is None) or (end == 0): # No length known yet, or no items at all return self.sentinel else: return self.__cache[end + n] # Now try to advance the generator (which may empty it, # or it may already be empty) while (not self.__empty) and (n >= len(self.__cache)): try: term = next(self.__iter) except StopIteration: self.__empty = True else: self.__cache.append(term) if n < len(self.__cache): return self.__cache[n] return self.sentinel def _iterable(self): # Yield terms from the generator for n in count(): term = self._retrieve(n) if term is self.sentinel: break yield term def _itemcount(self): # Once we are exhausted, the number of items in the # sequence is known, so we can provide it; otherwise # we return None if self.__empty: return len(self.__cache) return None def __call__(self, *args, **kwargs): """Make instances of this class callable. This method must be present, and must be a generator function, so that class instances work the same as their underlying generators. """ if not (self.__empty or self.__iter): self.__iter = self.__gen(*args, **kwargs) return indexediterator(self) # This creates a decorator that works if applied to a method # (the above will only work on an ordinary generator function) # -- requires the Delayed Decorator recipe at # http://code.activestate.com/recipes/577993-delayed-decorator/ indexable_generator = partial(DelayedDecorator, IndexedGenerator)