Rats Processors
Project description
rats-processors
In you python project or Jupyter notebook, you can compose a pipeline as follows:
from typing import NamedTuple
import pandas as pd
from rats.apps import PipelineContainer
from rats.processors import CombinedPipeline, ExecutablePipeline, task, pipeline
class DataOut(NamedTuple):
data: pd.DataFrame
class MyContainer(PipelineContainer):
@task
def load_data(self) -> DataOut:
return DataOut(data=pd.read_csv("data.csv"))
@task
def train_model(self, data: pd.DataFrame):
return {"model": "trained"}
@pipeline
def my_pipeline(self) -> ExecutablePipeline:
load_data = self.load_data()
train_model = self.get(train_model)
return self.combine(
pipelines=[load_data, train_model],
dependencies=(train_model.inputs.data << load_data.outputs.data),
)
and run it like this:
container = MyContainer() # initialize your container
p = container.get("my_pipeline") # public method to get a service from a container
container.draw(p)
container.run(p)
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