.github/workflows | ||
docs | ||
src/retailtwin | ||
.gitignore | ||
.pre-commit-config.yaml | ||
Caddyfile | ||
mkdocs.yml | ||
pyproject.toml | ||
README.md |
retailtwin
Implementation of a digital twin of a retail corporation that operates a chain of grocery stores will be described. The implementation is of course limited but comprehensive enough to get some key insights about why corporate IT looks the way it looks. If anyone intends to create antifragile data systems it's important to study how fragile systems come to be on the first place.
Bootstrap the database
First create a postgresql database.
createdb -h localhost -U postgresuser retail
In this case we decided to call the database retail
and we created it in the same computer we will be running the digital twin. Then sync the data models in the freshly created database with:
retailtwin init postgresql://postgresuser:password@localhost/retail
Then we can populate the database with dummy data with the bootstrap
subcommand:
retailtwin bootstrap postgresql://postgresuser:password@localhost/retail
Finally we can create all the necessary functions, procedures, and triggers with
retailtwin sync postgresql://postgresuser:password@localhost/retail
Terminals
There are currently three available terminals to operate with the digital twin:
Stocking terminal
stock [DB_URI] [Store location]
stock postgresql://postgresuser:password@localhost/retail 1