DBND an open source framework for building and tracking data pipelines. DBND is used for processes ranging from data ingestion, preparation, machine learning model training and production.

DBND includes a Python library, set of APIs, and CLI that enables you to collect metadata from your workflows, create a system of record for runs, and easily orchestrate complex processes.

DBND simplifies the process of building and running data pipelines from dbnd import task

from dbnd import task

@task
def say_hello(name: str = "databand.ai") -> str:
    value = "Hello %s!" % name
    return value

And makes it easy to track your critical pipeline metadata

from dbnd import log_metric, log_dataframe

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

See our documentation with examples and quickstart guides to get up and running with DBND.

For using DBND, we recommend that you work with a virtual environment like Virtualenv or Conda. Update 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 [email protected]