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do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

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dbt-fal: do more with dbt

dbt-fal is the easiest way to run Python with your dbt project.

fal Cloud   Total downloads   fal on PyPI   Slack channel   Discord conversation

Introduction - ๐Ÿ“– README

The dbt-fal ecosystem has two main components: The command line and the adapter.

CLI

With the CLI, you can:

Python Adapter

With the Python adapter, you can:

  • Enable a developer-friendly Python environment for most databases, including ones without dbt Python support such as Redshift, Postgres.
  • Use Python libraries such as sklearn or prophet to build more complex dbt models including ML models.
  • Easily manage your Python environments with isolate.
  • Iterate on your Python models locally and then scale them out in the cloud.

Why are we building this?

We think dbt is great because it empowers data people to get more done with the tools that they are already familiar with.

This library will form the basis of our attempt to more comprehensively enable data science workloads downstream of dbt. And because having reliable data pipelines is the most important ingredient in building predictive analytics, we are building a library that integrates well with dbt.

Have feedback or need help?