If you're familiar with the concept of map-reduce or Apache spark, then you may also be familiar with the workings of this library.
This is a sparse and deadpan writeup of what you should expect from this library.
Functions included:
map(func)- standard map function. Applies function in the argument to all values in the stream.flatmap(func)- takes a stream of iterables and emits individual values in those streams.filter(func)- boolean filter. Takes a function as a parameter. This function will be called with each element of the stream. If this function returnsTruewhen evaluating an object in the stream, then that object is re-emited to the stream.take(num)- a rate limiter..take(5)will only emit the first 5 elements of the stream.tap(func)- a passive function. Takes a single function as a parameter and passes iteratively passes objects from the stream to it.
Consumers:
print_stream()- iterates through all values of the stream and prints them.
Listed below are some over complicated solutions to trivial problems.
Import:
from pstream.pstream import pStream as _
Add Two:
def add_two(x):
return x + 2
stream = _([1,2,3,4,5])
stream.map(add_two)
stream.print_stream()
[3, 4, 5, 6, 7]
Every other even number between 0 and 100
def is_odd(x):
return x%2 != 0
def times_two(x):
return 2*x
stream = _(range(100)) \
.filter(is_odd)\
.take(25)\
.map(times_two)
stream.print_stream()
[2, 6, 10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78, 82, 86, 90, 94, 98]