This project provides a Streamlit application that provides record-level verification of individual student reports for training and validation purposes as well publishing the records for inclusion in Global Biodiversity Information Facility.
We recommend using a Python virtual environment to install SPOC's package dependencies. SPOC is currently developed with Python 3.9 and above.
- Create a new virtual environment
python3 -m venv spoc-env - Activate (on POSIX systems)
source spoc-env/bin/activate - Clone the current SPOC Git repository
git clone https://github.com/sul-dlss-labs/spoc.git - Enter directory and install dependencies,
cd spoc && pip install -r requirements.txt
The SPOC project uses Jupyter Book and notebooks for documenting the workflows, project, data, models, and technology. The book is available through Github pages at https://sul-dlss-labs.github.io/spoc/.
To build the latest documentation for this project:
jupyter-book build doc/
Publish the documentation to Github pages
ghp-import -n -p -f doc/_build/html
On the AWS EC2 instance, follow the instructions for installing and configuring certbot.
For step 7, just get the certificate only using sudo certbot --standalone -d taxa.stanford.edu certonly
To renew the cert, stop the SPOC containers and run sudo certbot renew --dry-run, and again without the --dry-run flag to actually renew.
Make sure the key files are copied into the config folder before starting the containers:
sudo cp /etc/letsencrypt/live/taxa.stanford.edu/fullchain.pem ./config/
sudo cp /etc/letsencrypt/live/taxa.stanford.edu/privkey.pem ./config/
The SPOC project uses Python types with mypy, linting with Flake8, and Black
for Python code formatting. Unit tests use the pytest and can be run
with pytest test/ from the root directory.
Cypress is used for end-to-end integration testing.
The publicly available Streamlit application is hosted on AWS.