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Project description
Baobao is a small library that attempts writing and maintaining data pipelines easier. It was written with Pandas in mind, but is not limited to it or even depends on it. It's AIP closely models Pandas pipe functionality.
Design principles are:
- Simple in the core
- Minimal dependencies
- Additional functionality is optional
Install with pip: pip install baobao
. Further documentation: https://hollstein.github.io/baobao/
Pipelines can be build like this:
import pandas as pd from baobao import Pipeline # To define pipelines from baobao import Step # Pipelines are build from Steps which may contain Pipelines # some functions that return pd.Dataframes to play with from baobao.utils.examples import load_1, load_2, load_3 Pipeline( root_node=load_1, # We have to start somewhere, could be any object or callable pipeline=( # Pipelines are build from Steps Step( # Each Step is build from a function that takes # the output of the previous Step as input in # the first argument func=pd.merge, # Any argoments to [func] can be given left_index=True, right_index=True, right=Pipeline(load_2), # including additional Pipelines ), Step(func=pd.merge, right=Pipeline(load_3), left_index=True, right_index=True), ) ).run() # Call the run method to actually run the pipeline, enjoy some logging out of the box
INFO:root:Pipeline(root_node=load_1(),memory=None)
INFO:root: Step(func=merge,args=(),left_index=True,right_index=True,right=Pipeline(root_node=l[...])
INFO:root:Pipeline(root_node=load_2(),memory=None)
Load 1
INFO:root:Complete pipeline after 3.02s
INFO:root: Step(func=merge,args=(),right=Pipeline(root_node=l[...],left_index=True,right_index=True)
INFO:root:Pipeline(root_node=load_3(),memory=None)
Load 2
INFO:root:Complete pipeline after 3.02s
INFO:root:Complete pipeline after 9.06s
Load 3
A neat way of speeding this up is caching results to disk:
# Baobao doesn't depend on any caching but respects Joblibs # API in case you want to chose some other caching strategy from joblib import Memory # Baobao options are separated into a dedicated object in # order to make it simple to push options down to Pipelines # included in Steps of the root Pipeline from baobao import PipelineOpts # Define the pipeline: pipeline = Pipeline( root_node=load_1, opts=PipelineOpts( memory=Memory("./cache", verbose=0), push_options=True # Pushing options down to included Pipelines ), pipeline=( Step(func=pd.merge, right=Pipeline(load_2), left_index=True, right_index=True), Step(func=pd.merge, right=Pipeline(load_3), left_index=True, right_index=True), ) ) # Run the pipeline: pipeline.run()
INFO:root:Pipeline(root_node=load_1(),memory=Memory(location=./cache/joblib))
INFO:root: Step(func=merge,args=(),right=Pipeline(root_node=l[...],left_index=True,right_index=True)
INFO:root: Pipeline(root_node=load_2(),memory=Memory(location=./cache/joblib))
INFO:root: Complete pipeline after 0.00s
INFO:root: Step(func=merge,args=(),right=Pipeline(root_node=l[...],left_index=True,right_index=True)
INFO:root: Pipeline(root_node=load_3(),memory=Memory(location=./cache/joblib))
INFO:root: Complete pipeline after 0.01s
INFO:root:Complete pipeline after 0.04s
Reasoning over pipelines might be simpler with this printing utility:
from baobao.utils import print_pipeline print_pipeline(pipeline)
pipeline << load_1
╠══ Step 0:merge
║ ╠══ right = DataFrame shape:(10, 1), columns:['c2']
║ ╠══ left_index = True
║ ╚══ right_index = True
╚══ Step 1:merge
╠══ right = DataFrame shape:(10, 1), columns:['c3']
╠══ left_index = True
╚══ right_index = True
Printing can be adjusted using the multiple dispatch pattern:
from baobao.pipeline import str_ @str_.register def _(inp: pd.DataFrame): return f"DataFrame(shape:{inp.shape})" @str_.register def _(inp: bool): return f"Bool:{inp}" print_pipeline(pipeline)
pipeline << load_1
╠══ Step 0:merge
║ ╠══ right = DataFrame(shape:(10, 1))
║ ╠══ left_index = Bool:True
║ ╚══ right_index = Bool:True
╚══ Step 1:merge
╠══ right = DataFrame(shape:(10, 1))
╠══ left_index = Bool:True
╚══ right_index = Bool:True
A little more depth added:
from baobao.utils.examples import * # Import more load_X functions def mk_pipeline(): # get fresh pipeline each time we call this function return Pipeline( root_node=load_1, opts=PipelineOpts( memory=None,#Memory("./cache", verbose=0), push_options=True ), pipeline=( Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline(load_2)), Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline( root_node=load_3, pipeline=( Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline(load_4)), Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline( root_node=load_2, pipeline=( Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline(load_5)), Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline(load_6)), ) )), )) ), Step(func=pd.merge, left_index=True, right_index=True, right=Pipeline(load_5)), ) )
Lets print this one again:
print_pipeline(mk_pipeline())
pipeline << load_1
╠══ Step 0:merge
║ ╠══ left_index = Bool:True
║ ╠══ right_index = Bool:True
║ ╚══ right
║ ╚══ pipeline << load_2
╠══ Step 1:merge
║ ╠══ left_index = Bool:True
║ ╠══ right_index = Bool:True
║ ╚══ right
║ ╚══ pipeline << load_3
║ ╠══ Step 0:merge
║ ║ ╠══ left_index = Bool:True
║ ║ ╠══ right_index = Bool:True
║ ║ ╚══ right
║ ║ ╚══ pipeline << load_4
║ ╚══ Step 1:merge
║ ╠══ left_index = Bool:True
║ ╠══ right_index = Bool:True
║ ╚══ right
║ ╚══ pipeline << load_2
║ ╠══ Step 0:merge
║ ║ ╠══ left_index = Bool:True
║ ║ ╠══ right_index = Bool:True
║ ║ ╚══ right
║ ║ ╚══ pipeline << load_5
║ ╚══ Step 1:merge
║ ╠══ left_index = Bool:True
║ ╠══ right_index = Bool:True
║ ╚══ right
║ ╚══ pipeline << load_6
╚══ Step 2:merge
╠══ left_index = Bool:True
╠══ right_index = Bool:True
╚══ right
╚══ pipeline << load_5
and run it in a sequential manner:
mk_pipeline().run()
INFO:root:Pipeline(root_node=load_1(),memory=None)
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_2(),memory=None)
Load 1
INFO:root: Complete pipeline after 3.01s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_3(),memory=None)
Load 2
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_4(),memory=None)
Load 3
INFO:root: Complete pipeline after 3.02s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_2(),memory=None)
Load 4
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_5(),memory=None)
Load 2
INFO:root: Complete pipeline after 3.01s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_6(),memory=None)
Load 5
INFO:root: Complete pipeline after 3.01s
INFO:root: Complete pipeline after 9.05s
INFO:root: Complete pipeline after 15.10s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_5(),memory=None)
Load 6
INFO:root: Complete pipeline after 3.01s
INFO:root:Complete pipeline after 24.15s
Load 5
We can speed things up by submitting those pipelines that do not contain further pipelines to a multiprocess Pool and enjoy some nice speedups:
from baobao.utils import run_parallel run_parallel(mk_pipeline(), n_jobs=4)
INFO:root:Submit: Pipeline(root_node=load_2(),memory=None) to: <multiprocessing.pool.Pool state=RUN pool_size=4>
INFO:root:Submit: Pipeline(root_node=load_4(),memory=None) to: <multiprocessing.pool.Pool state=RUN pool_size=4>
INFO:root:Submit: Pipeline(root_node=load_5(),memory=None) to: <multiprocessing.pool.Pool state=RUN pool_size=4>
INFO:root:Pipeline(root_node=load_2(),memory=None)
INFO:root:Submit: Pipeline(root_node=load_6(),memory=None) to: <multiprocessing.pool.Pool state=RUN pool_size=4>
INFO:root:Pipeline(root_node=load_4(),memory=None)
INFO:root:Submit: Pipeline(root_node=load_5(),memory=None) to: <multiprocessing.pool.Pool state=RUN pool_size=4>
INFO:root:Pipeline(root_node=load_1(),memory=None)
INFO:root:Pipeline(root_node=load_5(),memory=None)
INFO:root:Pipeline(root_node=load_6(),memory=None)
Load 4
Load 2
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=<multiprocessing.poo[...])
Load 6
INFO:root:Complete pipeline after 3.04s
Load 5
INFO:root:Pipeline(root_node=load_5(),memory=None)
INFO:root:Complete pipeline after 3.04s
INFO:root:Complete pipeline after 3.06s
INFO:root:Complete pipeline after 3.06s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_3(),memory=None)
Load 1
Load 5
INFO:root:Complete pipeline after 3.02s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=<multiprocessing.poo[...])
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=Pipeline(root_node=l[...])
INFO:root: Pipeline(root_node=load_2(),memory=None)
Load 3
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=<multiprocessing.poo[...])
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=<multiprocessing.poo[...])
INFO:root: Complete pipeline after 3.02s
INFO:root: Complete pipeline after 6.04s
INFO:root: Step(func=merge,args=(),left_index=Bool:True,right_index=Bool:True,right=<multiprocessing.poo[...])
INFO:root:Complete pipeline after 9.15s
Load 2
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