README.md

Defi Data Ops Sample

This is a sample repository demonstrating a data ops pipeline loading DefiLlama data into BigQuery using Meltano and self-hosted Cube for data visualization, with configuration for deployment to Render

• Meltano Documentation

Dependencies

• Docker Engine
• Docker Compose
• Python 3
• Pipx

Getting Started

For help setting up VSCode with poetry and singer tap development, see this thread and this thread on configuring your python interpreter

For an introduction to Meltano, see this video

# For local python development
pipx install meltano
pipx install poetry

Developing

# Run containerized meltano instance
docker compose up

This will expose the Meltano ui on localhost:5001 and mount ./meltano as a shared volume so you can develop locally and run pipelines in a containerized environment.

Next, install meltano dependencies. The meltano.sh script is the same as running meltano, but it executes in the meltano docker container conext, targeting /project/amo by default.

You can then either use the UI, or ./meltano.sh to run additional commands, such as:

# Run a custom tap you're actively developing, printing output to stdout
./meltano.sh invoke tap-defillama
# Add a new loader
./meltano.sh add loader target-bigquery
# Run a pipeline
./meltano.sh elt tap-testapi target-jsonl

# ...etc