GitLocker: The Coding Marketplace

Description:

prodius 0.0.3

prodius
Calculating cartesian product is not easy if not using itertools.product().
Prodius library allows to perform the same but also allowing iterables to
be callables that return iterable. Provided callables will be called when
iterable is needed to calculate cartesian product.
itertools.product() ofsen raise MemoryError when one of iterables is too
large. No matter matter the size of iterable, prodius will never write
whole iterator into memory.
Issues

Iterables cannot be more than 11.
Maybe be slower than itertools.product().

Installing
Prodius can be installed with pip in your command-line.
pip install prodius

Usage
Prodius is just easy just like builtin itertools.product().
Realise that this wont offer any benefit as iterator are passed direcly.
import prodius

iterables = [range(10), range(10)]
for item in prodius.product(*iterables, repeat=2):
print(item)

Prodius also allows iterables to contain callable that returns iterable.
The difference is that functions were used as iterables which provide
iterables on demand.
import prodius

iterables = [lambda: range(10), lambda: range(10)]
for item in prodius.product(*iterables, repeat=2):
print(item)

This compares itertools.product() with prodius.product().
import prodius

# prodius.product() is used to calculate cartesian product.
# No exception or MemoryError expected even if iterables are large.
iterables = [lambda: range(10000000000), lambda: range(10000000000)]
product = prodius.product(*iterables) # works as espected

import itertools

# itertools.product() is used to calculate cartesian product.
# MemoryError expected as iterables are too large.
iterables = [range(10000000000), range(10000000000)]
product = itertools.product(*iterables) # MemoryError

Prodius also gives control of over items of iterable to be used in cartesian
product. That could be accomplised using itertools.cycle() by returning
different iterable each time function is called.
import prodius
import itertools

foods_numbers_list = [[1,2], ["apple", "orange"]]
foods_numbers_cycle = itertools.cycle(foods_numbers_list)

def numbers_foods():
return next(foods_numbers_cycle)

for item in prodius.product([100, 200], numbers_foods):
print(item)
# (100, 1)
# (100, 2)
# (200, 'apple')
# (200, 'orange')

Notice that 100 was matched with numbers (1, 2) while 200 matched with
('apple', 'orange').
Thats a fantastic trick with prodius even if it does not have realworld
application but who knows.
License
MIT license