This pipeline idea has actually been implemented further, see <http://
blog.onideas.ws/stream.py>.
from stream import map, filter, cut
range(10) >> map(lambda x: [x**2, x**3]) >> filter(lambda t: t[0]!
=25 and t[1]!=64) >> cut[1] >> list
[0, 1, 8, 27, 216, 343, 512, 729]
Wow, cool!
Just to show that you can easily add the iterator.map(f).blabla-syntax
to Python:
from __future__ import print_function
class rubified(list):
map = lambda self, f: rubified(map(f, self))
filter = lambda self, f: rubified(filter(f, self))
reject = lambda self, f: rubified(filter(lambda x: not f(x),
self))
# each = lambda self, f: rubified(reduce(lambda x, y:
print(y), self, None))
def each(self, f):
for x in self: f(x)
def __new__(cls, value):
return list.__new__(cls, value)
def print_numbers():
rubified([1, 2, 3, 4, 5, 6]).map(lambda n:
[n * n, n * n * n]).reject(lambda (square, cube):
square == 25 or cube == 64).map(lambda (square, cube):
cube).each(lambda n:
print(n))
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