Python Mongodb ML Model Managing

Traditional way of saving machine learning models in file system having some challenges, especially moving to different environment. Machine learning binary models saving in git also not advisable. It's not a best practice either.

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pip install mongodb-ml-models

[mongodb.model]
host=0.0.0.0  # Replace with the host IP if the mongo server was on different machine
port=6273
model_type=type # A collection name for your model

[class_name] # Replace with your class name, this name is used for accessing the models in the code
db_name=model_db # Replace with the db name you want
version=V1 # Version number here, update with every new model else replace the existing model in the db

from handle_mongodb_models import ManageModel

Then you can upload your binary model by

ManageModel.upload_model(binary_model, model_class)

binary_model = ManageModel.get_model(model_class)

This will load the model if it was not available in the local machine