How to Build a Mock TFX Pipeline in Python

# Mock TFX pipeline to illustrate component orchestration

def CsvExampleGen(data_path):
    """Mock component: Simulates reading CSV data."""
    print(f"ExampleGen: Reading from {data_path}")
    return {"records": 100, "name": "examples"}

def StatisticsGen(example_artifact):
    """Mock component: Simulates generating statistics."""
    print(f"StatisticsGen: Processing {example_artifact['records']} records")
    return {"mean": 5.2, "std": 1.8}

def SchemaGen(statistics_artifact):
    """Mock component: Simulates schema inference."""
    print(f"SchemaGen: Inferring schema from mean={statistics_artifact['mean']}")
    return {"columns": ["feature_a", "feature_b", "label"]}

def Transform(schema_artifact, examples_artifact):
    """Mock component: Simulates feature transformation."""
    print(f"Transform: Applying schema {schema_artifact['columns']}")
    return {"transformed_examples": 100}

def Trainer(transform_artifact):
    """Mock component: Simulates model training."""
    print(f"Trainer: Training on {transform_artifact['transformed_examples']} examples")
    return {"model_path": "model.pkl", "accuracy": 0.92}

def main():
    data_path = "data/train.csv"
    examples = CsvExampleGen(data_path)
    stats = StatisticsGen(examples)
    schema = SchemaGen(stats)
    transformed = Transform(schema, examples)
    model = Trainer(transformed)
    print(f"Pipeline complete: {model['model_path']}, accuracy={model['accuracy']}")

if __name__ == "__main__":
    main()