A small pipeline framework built on top of functions
An article describing development and use of picopipe: Towards Data Science: The Worlds Smallest Data Pipeline Framework
pip install picopipe
def add1(value):
return value + 1
def add2(value):
return value + 2
def add3(value):
return value + 3
from picopipe import pipeline
p = pipeline(add1, add2, add3)
p([10, 20, 30])
See tests for more examples.
with open("pipeline.mmd", "w") as fp:
fp.write(to_mermaid(p))
Mermaid file (renders in github):
flowchart
subgraph pipeline_98e33e0628b546268abb2af5f74e50f1 ["pipeline"]
end
subgraph pipeline_205813c806fd4b37b40309497768f7c1 ["pipeline"]
node0["identity"]
node1["is_not_none"]
node2["identity"]
end
node0 --> node1
node1 --> node2
click node0 console.log "def identity(value):<br/>    return value<br/>"
click node1 console.log "@pfilter<br/>def is_not_none(v):<br/>    return v is not None<br/>"
click node2 console.log "def identity(value):<br/>    return value<br/>"
subgraph pipeline_d2f205ef957a428abbaa208241125819 ["pipeline"]
node3["add1"]
node4["[lambda]"]
end
node3 --> node4
click node3 console.log "def add1(value):<br/>    return value + 1<br/>"
click node4 console.log "lambda ...: ..."
pipeline_98e33e0628b546268abb2af5f74e50f1 --> pipeline_205813c806fd4b37b40309497768f7c1
pipeline_205813c806fd4b37b40309497768f7c1 --> pipeline_d2f205ef957a428abbaa208241125819