✨ Automate Your ML Pipelines with MLFCrafter (Open Source)
Hey Devs! 👋
I recently built a small open-source Python package called MLFCrafter that helps you build and run ML pipelines faster — no more repetitive boilerplate!
Instead of writing tons of lines to load, clean, scale, train, and evaluate a model, you just chain crafters together.
🛠 What is MLFCrafter?
MLFCrafter is a modular machine learning pipeline framework.
Each step in the pipeline is called a crafter, and you can compose them like building blocks.
Here’s how it looks in action:
from mlfcrafter import MLFChain, DataIngestCrafter, CleanerCrafter, ScalerCrafter, ModelCrafter, ScorerCrafter, DeployCrafter
chain = MLFChain(
DataIngestCrafter(data_path="data/iris.csv"),
CleanerCrafter(strategy="auto"),
ScalerCrafter(scaler_type="standard"),
ModelCrafter(model_name="random_forest"),
ScorerCrafter(),
DeployCrafter()
)
results = chain.run(target_column="species")
print(f"Test Score: {results['test_score']:.4f}")
That’s it — your full ML pipeline is up and running.
⚙️ Features
-
📁 Load your own dataset easily
-
🧼 Clean and scale with customizable settings
-
🤖 Train a model (logistic regression, random forest, etc.)
-
📊 Get evaluation metrics
-
🚀 Deploy your pipeline
-
🧪 Automate versioning + publishing with GitHub Workflows
-
🛠 Easy to extend with your own custom crafters
📦 Installation
pip install mlfcrafter
🔗 Links
GitHub: https://github.com/brkcvlk/MLFCrafter
PyPI: https://pypi.org/project/mlfcrafter
🙏 Let’s Connect
This is still early stage and I’d love feedback, ideas, or contributions.
If you try it out and hit any issues — I’m here to help!
Thanks for reading! 🚀
Feel free to drop a comment if you find this useful ❤️
