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Machine Learning Orchestration

Project description

pipeline status coverage report

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DBND is an agile pipeline framework that helps date engineering teams track and orchestrate their data processes. Used for processes ranging from data prep, machine learning model training, experimentation, testing, and production, DBND is easy to use and natively provides teams visibility, reproducibility, and dynamic orchestration for your projects.

DBND simplifies the process of building, running, and tracking data pipelines

from dbnd import task

def say_hello(name: str = "") -> str:
    value = "Hello %s!" % name
    return value

And provides way for tracking your critical pipeline metadata

    from dbnd import log_metric, log_dataframe

    log_dataframe("my_dataset", my_dataset) 
    log_metric("r2", r2)

Getting Started

See our Quickstart guide to get up and running with DBND. Our documentation is available for more examples and guides

The Latest and Greatest

We recommend that you work with a virtual environment like Virtualenv or Conda. Updating to the latest and greatest:

pip install dbnd

If you would like access to our latest features, or have any questions, feedback, or contributions we would love to here from you! Get in touch through

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