Getting Started¶
pyungo is a lightweight library to link a set of dependent functions together, and execute them in an ordered manner.
pyungo is built around Graphs and Nodes used in a
DAG (Directed Acyclic Graph).
A Node
represent a function being run with a defined set of inputs
and returning one or several outputs. A Graph
is a collection of
Nodes where data can flow in an logical manner, the output of one node serving as
input of another.
Simple example¶
graph = Graph()
@graph.register()
def f_my_function_2(d, a):
e = d - a
return e
@graph.register(outputs=['d'])
def f_my_function_1(c):
return c / 10.
@graph.register()
def f_my_function_3(a, b):
c = a + b
return c
res = graph.calculate(data={'a': 2, 'b': 3})
print(res)
pyungo is registering the functions at import time. It then resolve the DAG and figure out the sequence at which the functions have to be run per their inputs / outputs. In this case, it will be function 3 then 1 and finally 2.
The ordered Graph
is run with calculate, with the given data. It returns
the output of the last function being run (e
), but all intermediate results are also
available in the graph instance.
The result will be (a + b) / 10 - a = -1.5
Note
In the above example, most of the inputs / outputs are not explicitely defined when
registering. pyungo inspects the function signature to get the names and extract the
returned variable names automatically. For f_my_function_1
, there is no returned
variable, so the output name needs to be explicitely provided.