Dashboard Prototype

Prototype data dashboard using the Cuthill Gold Standard Dataset, which was processed from Cuthill, et. al. (original dataset available at doi:10.5061/dryad.2hp1978). Test datasets (the processed version of Cuthill's data with and without filepath URLs) are available in test_data.

This dashboard focuses on images labeled at the species and subspecies level as described in a CSV.

How it works

For full dashboard functionality, upload a CSV or XLS file with the following columns: - Species: Species of each sample. - Subspecies: Subspecies of each sample. - View: View of the sample (eg., 'ventral' or 'dorsal' for butterflies). - Sex: Sex of each sample. - hybrid_stat: Hybrid status of each sample (eg., 'validsubspecies', 'subspeciessynonym', or 'unknown'). - lat: Latitude at which image was taken or specimen was collected: number in [-90,90]. - lon: Longitude at which image was taken or specimen was collected: number in [-180,180]. long will also be accepted. - file_url: URL to access file. *Note:** Images should be in PNG or JPEG format, TIFF may fail to render in the sample image display.

**Note:* - Column names are not case-sensitive. - lat and lon columns are not required to utilize the dashboard, but there will be no map view if they are not included. Blank (or null) entries are recorded as unknown, and thus excluded from map view. - file_url is not required, but there will be no sample images option if it is not included. - locality may be provided, otherwise it will take on the value lat|lon or unknown if these are not provided.

Running Dashboard

Create and activate a new (python) virtual environment. Then install the required packages (if using conda, first run conda install pip):

pip install -r requirements.txt

and run

python dashboard.py

Then navigate to http://127.0.0.1:8050/ in your browser to see the graphs.

Running with Docker

To run the dashboard in a more scalable manner a Dockerfile is provided. This container uses gunicorn to support more users at the same time. Building and running the container requires that docker is installed.

Building the container

docker build -t dashboard .

Running the container

To deploy the dashboard with 6 workers run the following command: docker run --env BACKEND_WORKERS=6 -p 5000:5000 -it dashboard Then open the following URL http://0.0.0.0:5000/.

Preview

Histogram View

Map View

Testing

Test Requirements

The testing suite requires Dash Testing and pytest-mock, which can be installed in your python environment by running: pip install dash\[testing] pytest-mock

Running Tests

Within your python environment run the following command to run all tests: pytest