Chainz
Chainz is a lightweight library to provide chaining, functional methods
to iterables.
To install: pip install chainz
Basic example:
.. code:: python
from chainz import Chain
Chain(xrange(10))\
.map(lambda x: x + 1)\
.filter(lambda x: x % 2 == 0)\
.omit(lambda x: x % 3 == 0)\
.reduce(lambda x, y: x + y)
# 30
Chain
The fundamental class in chainz is Chain, which accepts an
iterable as an argument to its constructor. It is itself an iterable,
just exposing the supplied iterable. It exposes functional methods like
map, filter, and flatten, which return the chain so as to be
chainable. These methods alter the chain; chain.map(f) is the same
as chain = chain.map(f).
Some methods, such as reduce and for_each, are "sinks", in that
they consume the iterable. These methods do not return the chain, to
make it clear that once they are called, the chain is done.
All non-sink methods are lazy, so they don't result in any evaluation.
Only by using a sink method, or consuming the iterable in another way
(such as list(chain) or [x for x in chain]), do you actually
evaluate the iterable.
You can think of Chain as a way to wrap itertools in a more
chainable fashion.
Errors
By default, a Chain will stop whenever there's an exception. Often
that is not what you want. When you are processing a long list of items
(something for which Chain was specifically created for), you just
want to note what went wrong, and move on to the next item. The method
on_error allows just that. It takes a function
f(exception, object) which itself takes two parameter. The first
parameter is the raised exception. The second parameter is the object
that caused the exception.
Example
.. code:: python
def handle_error(exception, obj):
print("%s caused exception: %s" % (obj, exception))
def double(x):
if x == 1:
raise Exception('Bad')
return x*2
chain = Chain(xrange(3)).on_error(handle_error).map(double)
list(chain)
# "1 caused exception: Exception('Bad')"
# [0, 2]
API
---
Please see the ``docs/`` directory for auto-generated (and thus
up-to-date) documentation. This is generated from the doc strings, so
introspection can also be helpful (eg, ``print Chain.reduce.__doc__``).