imo-vmdb 1.5.1

Imports VMDB CSV files from IMO into a SQL database.

imo-vmdb

imo-vmdb imports data from the Visual Meteor Database (VMDB) of the International Meteor Organization (IMO) into a relational SQL database.

The data is enriched with computed properties (radiant positions, sun/moon position and illumination) and validated for plausibility. No analysis is performed by the tool itself — the database is the output.

For full documentation see https://imo-vmdb.readthedocs.io/en/latest/.

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Quick Start (Docker)

No Python required. Pull and run the web UI:

docker run --rm \
    -p 8000:8000 \
    -v ./data:/data \
    -e IMO_VMDB_DATABASE_DATABASE=/data/vmdb.db \
    ghcr.io/jankorichter/imo-vmdb

Open http://localhost:8000.

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Developer Setup

Prerequisites: Python 3.10+, Poetry

git clone https://github.com/jankorichter/imo-vmdb.git
cd imo-vmdb
poetry install
poetry run python -m imo_vmdb

With documentation extras (required to build Sphinx docs):

poetry install --extras docs

Run the web UI locally:

poetry run python -m imo_vmdb web_server -c config.ini

Run the test suite:

poetry run pytest

No server needs to be started beforehand. The tests use Flask's built-in test client, which calls the application directly in-process — no network, no port. A temporary SQLite database is created automatically for each test run.

Build Docker image locally:

docker compose up --build