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simplepipe is a simple composable, functional pipelining library for Python. It was built to facilitate the composition of small tasks, defined as pure functions, in order to perform a complex operation. It supports single and multi-output tasks (via generator functions). simplepipe also allows creation of hooks that can modify the behavior of the workflow after it has been created.
The following command will install the package in your python environment from PyPI.
pip install simplepipe
If you want install from the source code instead, run
python setup.py install
simplepipe allows you to define a list of tasks executed in a sequence that
uses data in a workspace and returns a new, updated workspace. Each task can be
python function, generator function or another Workflow object. The original workspace is unaffected. Method calls to add_task
, add_hook
, and add_hook_point
can be chained.
This is the default mode for tasks if no input or output spec is given. These functions must return a dict with result that will be used to update the workspace. Workflow objects can themselves be used as full-workspace tasks. These functions should return a dict that will be used with the 'update()' method on the workspace dict.
simplepipe makes sure that the input workspace dict is protected from mutations from these tasks and only updates the workspace with the returned value
import simplepipe
def do_stuff_with_workspace(workspace):
workspace['c'] = workspace['b']*2
return workspace
wf = simplepipe.Workflow()
data_in = {'a': 1, 'b': 2}
wf.add_task(do_stuff_with_workspace) # '*' is default mode
output = wf(data_in)
print(output) # Prints {'a': 1, 'b': 2, 'c': 4}
wf2 = simplepipe.Workflow()
wf2.add_task(wf) # Add another workflow as a task
wf2.add_task(fn= lambda c: 5*c, inputs='c', outputs='d')
output = wf(data_in)
print(output) # Prints {'a': 1, 'b': 2, 'c': 4, 'd': 20}
# Protection against mutator functions
def bad_mutator_fn(workspace):
workspace['a'] = 'just_messing_with_a'
return {'e': 'foobar'}
wf3 = simplepipe.Workflow()
wf3.add_task(fn=bad_mutator_fn)
output = wf(data_in)
print(output) # Prints {'a': 1, 'b': 2, 'e': 'foobar'}
import simplepipe
def sum(a, b):
return a+b
def twice(x):
return 2*x
wf = simplepipe.Workflow()
data_in = {'a': 1, 'b': 2}
wf.add_task(sum, inputs=['a', 'b'], outputs=['c']) \
.add_task(twice, inputs=['c'], outputs=['d'])
output = wf(data_in)
print(output) # Prints {'a': 1, 'b': 2, 'c': 3, 'd': 6}
Functions returning multiple values must use the yield
keyword to return them
separately, one at a time.
import simplepipe
def sum_and_product(a, b):
yield a+b
yield a*b
wf = simplepipe.Workflow()
data_in = {'a': 1, 'b': 2}
wf.add_task(sum_and_product, inputs=['a', 'b'], outputs=['c', 'd'])
output = wf(data_in)
print(output) # Prints {'a': 1, 'b': 2, 'c': 3, 'd': 2}
simplepipe also supports hooks that allow customization of the workflow after it has been created. Hook points are defined using the add_hook_point
method. Any number of hook functions can be bound to the hook points in the work flow. Multiple hooks added at the same hook point will be executed in the order that they were added.
Note: Hook functions are not pure functions and are supposed to mutate the output workspace. They do not return anything.
import simplepipe
def sum(a, b):
return a+b
def twice(x):
return 2*x
def do_after_sum(workspace):
workspace['c'] = workspace['c']*10
def do_after_twice(workspace):
workspace['e'] = 31337
wf = simplepipe.Workflow()
data_in = {'a': 1, 'b': 2}
wf.add_task(sum, inputs=['a', 'b'], outputs=['c'])
wf.add_hook_point('after_sum')
wf.add_task(twice, inputs=['c'], outputs=['d'])
wf.add_hook_point('after_twice')
# Hook functions can be inserted any time before the workflow is executed
wf.add_hook('after_sum', do_after_sum)
wf.add_hook('after_twice', do_after_twice)
output = wf(data_in)
print(output)
# {'a': 1, 'b': 2, 'c': 30, 'd': 60, 'e': 31337}
#About the Author Thomas Antony's LinkedIn Profile
FAQs
A simple functional pipelining library for Python.
We found that simplepipe demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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