lazysequence

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A lazy sequence makes an iterator look like an immutable sequence:

.. code:: python

from lazysequence import lazysequence

def load_records(): return range(10) # let's pretend this is expensive

records = lazysequence(load_records()) if not records: raise SystemExit("no records found")

first, second = records[:2]

print("The first record is", first) print("The second record is", second)

for record in records.release(): # do not cache all records in memory print("record", record)

Why?

Sometimes you need to peek ahead at items returned by an iterator. But what if later code needs to see all the items from the iterator? Then you have some options:

Pass any consumed items separately. This can get messy, though.
Copy the iterator into a sequence beforehand, if that does not take a lot of space or time.
Duplicate the iterator using itertools.tee, or write your own custom itertool that buffers consumed items internally. There are some good examples of this approach on SO, by Alex Martelli, Raymond Hettinger, and Ned Batchelder.

.. _itertools.tee: https://docs.python.org/3/library/itertools.html#itertools.tee .. _Alex Martelli: https://stackoverflow.com/a/1518097/1355754 .. _Raymond Hettinger: https://stackoverflow.com/a/15726344/1355754 .. _Ned Batchelder: https://stackoverflow.com/a/1517965/1355754

A lazy sequence combines advantages from option 2 and option 3. It is an immutable sequence that wraps the iterable and caches consumed items in an internal buffer. By implementing collections.abc.Sequence_, lazy sequences provide the full set of sequence operations on the iterable. Unlike a copy (option 2), but like a duplicate (option 3), items are only consumed and stored in memory as far as required for any given operation.

.. _collections.abc.Sequence: https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence

There are some caveats:

The lazy sequence will eventually store all items in memory. If this is a problem, use s.release() to obtain an iterator over the sequence items without further caching. After calling this function, the sequence should no longer be used.
Explicit is better than implicit. Clients may be better off being passed an iterator and dealing with its limitations. For example, clients may not expect len(s) to incur the cost of consuming the iterator to its end.