pyqflow 1.1.2

API for creating async workflows.

Qflow is a Python library tailored for asynchronous orchestration of machine learning pipelines. It allows users to define their pipelines declaratively, with the flexibility for processing at each stage to run either remotely or locally. The library supports a wide range of operations, which can be customized with user-defined Python functions.

Instalation

Install

clone repo and install requirements.txt in a Python>=3.7.0 environment.

pip install -r requirements.txt

Example

Simple wordcount example with no remote stages. We can define a qflow pipeline as follows:

from qflow import (
    QWorkflow,
    QFileSource,
    QFlatMap,
    QNativeMap,
    QAggregate
)
from qflow.functools import fst, snd, head


class WordCount(QWorkflow):

    def forward(self, input_text):
        
        results = (
            QFileSource(input_text) 
            | QFlatMap(
                lambda line: line.split()
                ) 
            | QNativeMap(
                lambda word: (word, 1)
                ) 
            | QAggregate(
                key_factory = fst
                )
            | QNativeMap(
                lambda words: ( fst(head(words)), sum(map(snd, words)) )
                )
        )

        return results

To use this pipeline we can run it as follows:

# create the processing pipeline.
workflow = WordCount()

# run the pipeline with the file "input.txt" as input.
results = workflow("input.txt")

print(results)