Tucson Data

Tucson data sources, code to fetch the data and to make it more usable.

This is a Dagster project scaffolded with dagster project scaffold.

Data sources

Bicycle Routes

Link: https://gisopendata.pima.gov/datasets/e590f125f2744ad0918c9025363004eb_2/explore

Bikeways

Link: https://maps.pagregion.com/PAGBikePed/BikewaysMap

This data has the same schema as the Bicycle Routes data from Pima County, but has fewer features. It doesn't appear to have mountain bike trails, and the BIKERTE_DS field seems a bit dirtier than the one in the Bicycle Routes data.

Jurisdiction Boundaries

Link: https://gisopendata.pima.gov/datasets/472d08edd7324a5bbda029a6d966095d_11

Libraries

Link: https://gisopendata.pima.gov/datasets/adab4088035540e6bf9babfccd0ee4e6_2/

Getting started

First, install your Dagster code location as a Python package. By using the --editable flag, pip will install your Python package in "editable mode" so that as you develop, local code changes will automatically apply.

pip install -e ".[dev]"

Then, start the Dagster UI web server:

dagster dev

Open http://localhost:3000 with your browser to see the project.

You can start writing assets in tucson_data/assets.py. The assets are automatically loaded into the Dagster code location as you define them.

Development

Adding new Python dependencies

You can specify new Python dependencies in setup.py.

Unit testing

Tests are in the tucson_data_tests directory and you can run tests using pytest:

pytest tucson_data_tests

Schedules and sensors

If you want to enable Dagster Schedules or Sensors for your jobs, the Dagster Daemon process must be running. This is done automatically when you run dagster dev.

Once your Dagster Daemon is running, you can start turning on schedules and sensors for your jobs.

Deploy on Dagster Cloud

The easiest way to deploy your Dagster project is to use Dagster Cloud.

Check out the Dagster Cloud Documentation to learn more.

ghing / tucson-data