MOCK GRAPH DATA GENERATOR

Applet using Streamlit to conveniently design and generate interwoven mock data. A running cloud instance of this can be found here

Install Poetry

This applet uses Poetry for dependency management.

Dependencies

This applet uses several packages that will auto-install if you use either the poetry or pipenv commands below. Notable is the use of 2 small packages:

1. graph-data-generator for generating the actual mock data from a .json configuration
2. neo4j-uploader for uploading generated .json output to a Neo4j graph database instance

Local Running

poetry update
poetry run streamlit run graph_data_generator_streamlit/app.py

Testing with local packages

poetry add --editable /path/to/package

Running in Google Cloud

• Set up a Google Cloud account
• Create a Google Cloud Project
• Enable billing for that project
• Temporarily move any .streamlit/secret.toml file to the root folder director (same level as Dockerfile)
• Install glcoud cli
• Run the following commands from the terminal of your local dev machine:

gcloud builds submit --tag gcr.io/<google_cloud_project_id>/mock-graph-generator
gcloud run deploy --image gcr.io/<google_cloud_project_id>/mock-graph-generator --platform managed --allow-unauthenticated

When completed, can move secrets.toml file back to .streamlit/ - that or maintain a separate external secrets.toml file just for Google Cloud