Skip to main content

A dbt server and suite of optional developer tools to make developing with dbt delightful.

Project description

dbt-osmosis

PyPI Downloads License: Apache 2.0 black Streamlit App

Scc Count Badge Scc Count Badge

New to dbt-osmosis?

We now have a spiffy dbt-osmosis documentation site! 🎉

Please check it out for a more in-depth introduction to dbt-osmosis. 👇

dbt-osmosis

What is dbt-osmosis?

Hello and welcome to the project! dbt-osmosis 🌊 serves to enhance the developer experience significantly. We do this through providing 4 core features:

  1. Automated schema YAML management.

    1a. dbt-osmosis yaml refactor --project-dir ... --profiles-dir ...

    Automatically generate documentation based on upstream documented columns, organize yaml files based on configurable rules defined in dbt_project.yml, scaffold new yaml files based on the same rules, inject columns from data warehouse schema if missing in yaml and remove columns no longer present in data warehouse (organize -> document)

    1b. dbt-osmosis yaml organize --project-dir ... --profiles-dir ...

    Organize yaml files based on configurable rules defined in dbt_project.yml, scaffold new yaml files based on the same rules

    1c. dbt-osmosis yaml document --project-dir ... --profiles-dir ...

    Automatically generate documentation based on upstream documented columns

  2. A highly performant dbt server which integrates with tools such as dbt-power-user for VS Code to enable interactive querying + realtime compilation from your IDE

    2a. dbt-osmosis server serve --project-dir ... --profiles-dir ...

    Spins up a WSGI server. Can be passed --register-project to automatically register your local project

  3. Workbench for dbt Jinja SQL. This workbench is powered by streamlit and the badge at the top of the readme will take you to a demo on streamlit cloud with jaffle_shop loaded (requires extra pip install "dbt-osmosis[workbench]").

    3a. dbt-osmosis workbench --project-dir ... --profiles-dir ...

    Spins up a streamlit app. This workbench offers similar functionality to the osmosis server + power-user combo without a reliance on VS code. Realtime compilation, query execution, pandas profiling all via copying and pasting whatever you are working on into the workbenchat your leisure. Spin it up and down as needed.

  4. Diffs for data model outputs to model outputs across git revisions (🚧 this is in development)

    4a. dbt-osmosis diff -m some_model --project-dir ... --profiles-dir ...

    Run diffs on models dynamically. This pulls the state of the model before changes from your git history, injects it as a node to the dbt manifest, compiles the old and modified nodes, and diffs their query results optionally writing nodes to temp tables before running the diff query for warehouses with performance or query complexity limits (👀 bigquery)


Pre-commit

You can use dbt-osmosis as a pre-commit hook. This will run the dbt-osmosis yaml refactor command on your models directory before each commit. This is one way to ensure that your schema.yml files are always up to date. I would recommend reading the docs for more information on what this command does.

repos:
  - repo: https://github.com/z3z1ma/dbt-osmosis
    rev: v0.11.11 # verify the latest version
    hooks:
      - id: dbt-osmosis
        files: ^models/
        # you'd normally run this against your prod target, you can use any target though
        args: [--target=prod]
        additional_dependencies: [dbt-<adapter>]

Workbench

The workbench is a streamlit app that allows you to work on dbt models in a side-by-side editor and query tester. I've kept this portion of the README since users can jump into the streamlit hosted workbench to play around with it via the badge below. Expect the living documentation moving forward to exist at the dbt-osmosis documentation site.

I also expect there is some untapped value in the workbench that is only pending some time from myself. I've seen a path to a truly novel development experience and look forward to exploring it.

Demo the workbench 👇

Streamlit App

# NOTE this requires the workbench extra as you can see
pip install "dbt-osmosis[workbench]"

# Command to start server
dbt-osmosis workbench

Press "r" to reload the workbench at any time.

✔️ dbt Editor with instant dbt compilation side-by-side or pivoted

✔️ Full control over model and workbench theme, light and dark mode

✔️ Query Tester, test the model you are working on for instant feedback

✔️ Data Profiler (leverages pandas-profiling)

Editor

The editor is able to compile models with control+enter or dynamically as you type. Its speedy! You can choose any target defined in your profiles yml for compilation and execution.

editor

You can pivot the editor for a fuller view while workbenching some dbt SQL.

pivot

Test Query

Test dbt models as you work against whatever profile you have selected and inspect the results. This allows very fast iterative feedback loops not possible with VS Code alone.

test-model

Profile Model Results

Profile your datasets on the fly while you develop without switching context. Allows for more refined interactive data modelling when dataset fits in memory.

profile-data

Useful Links and RSS Feed

Some useful links and RSS feeds at the bottom. 🤓

profile-data


graph

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dbt_osmosis-0.13.2.tar.gz (110.7 kB view details)

Uploaded Source

Built Distribution

dbt_osmosis-0.13.2-py3-none-any.whl (117.3 kB view details)

Uploaded Python 3

File details

Details for the file dbt_osmosis-0.13.2.tar.gz.

File metadata

  • Download URL: dbt_osmosis-0.13.2.tar.gz
  • Upload date:
  • Size: 110.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.9

File hashes

Hashes for dbt_osmosis-0.13.2.tar.gz
Algorithm Hash digest
SHA256 86a6c7a3fc119e747da76b9bcf9db9562d84498939c0e6522e5766ef02a28eb6
MD5 0308e3193c54460f41a88d55ebd4ab5f
BLAKE2b-256 e596e88a35e91dd120d0f2afc5e2d610529f9c4592f7f24bed5dfa8d34df99a1

See more details on using hashes here.

File details

Details for the file dbt_osmosis-0.13.2-py3-none-any.whl.

File metadata

  • Download URL: dbt_osmosis-0.13.2-py3-none-any.whl
  • Upload date:
  • Size: 117.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.9

File hashes

Hashes for dbt_osmosis-0.13.2-py3-none-any.whl
Algorithm Hash digest
SHA256 a8f506951de88d2b142f5763edda9d986f0419fb505f0a137fad80a0c961f20e
MD5 cb831e692b40af533c437a69c2de8852
BLAKE2b-256 42ed3be95c33334b19311b8af8d0dfa872b2e84c8e134cec10411980e7fe3c79

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page