lined 0.0.6

Building simple pipelines, simply.

lined

Building simple pipelines, simply.

A really simple example:

>>> p = Pipeline(sum, str)
>>> p([2, 3])
'5'

A still quite simple example:

>>> def first(a, b=1):
...     return a * b
>>>
>>> def last(c) -> float:
...     return c + 10
>>>
>>> f = Pipeline(first, last)
>>>
>>> assert f(2) == 12
>>> assert f(2, 10) == 30

Let's check out the signature of f:

>>> from inspect import signature
>>>
>>> assert str(signature(f)) == '(a, b=1) -> float'
>>> assert signature(f).parameters == signature(first).parameters
>>> assert signature(f).return_annotation == signature(last).return_annotation == float

Border case: One function only

>>> same_as_first = Pipeline(first)
>>> assert same_as_first(42) == first(42)

More?

string and dot digraph representations

Pipeline's string representation (__repr__) and how it deals with callables that don't have a __name__ (hint: it makes one up):

from lined.base import Pipeline
from functools import partial

pipe = Pipeline(sum, np.log, str, print, partial(map, str), name='some_name')
pipe

Pipeline(sum, log, str, print, unnamed_func_001, name='some_name')

If you have graphviz installed, you can also do this:

pipe.dot_digraph()

And if you don't, but have some other dot language interpreter, you can just get the body (and fiddle with it):

print('\n'.join(pipe.dot_digraph_body()))

rankdir="LR"
sum [shape="box"]
log [shape="box"]
str [shape="box"]
print [shape="box"]
unnamed_func_001 [shape="box"]
sum -> log
log -> str
str -> print
print -> unnamed_func_001

Optionally, a pipeline can have an input_name and/or an output_name. These will be used in the string representation and the dot digraph.

pipe = Pipeline(sum, np.log, str, print, partial(map, str), input_name='x', output_name='y')
str(pipe)

"Pipeline(sum, log, str, print, unnamed_func_001, name='some_name')"

pipe.dot_digraph()