A recipe storage solution built primarily via a graph database (dgraph). Current API POC in Python, MVP will migrated to Golang. Angular front-end.
A recipe should track the following metadata:
* title
* picture
* prep and cook time
* ingredients
* steps
* rating (track ratings from individual users separately)
* tags (such as culinary region, type of meal, or whatever else you want to tag a recipe with)
* notes, tagged by the user who added them
* list of dates of when the recipe was made
Core API functionality:
* authentication
* facebook SSO?
* two roles:
* full control of everything
* can only rate + add notes
* basic CRUD on recipes
* search recipes by any and all metadata
* master store of ingredients, typical CRUD ops
* recommendation engine using graph data
* dashboard with random stupid stats
API: ec2-34-238-150-16.compute-1.amazonaws.com:4000
Ratel: ec2-34-238-150-16.compute-1.amazonaws.com:8000
The API can be started via a simple python3 recipy.py. Long running commands, such as running the API, should be done via screen. Current screens can be found via -ls:
ubuntu@ip-172-31-12-209:~/chefconnect$ screen -ls
There are screens on:
10780.run (04/17/20 21:29:35) (Detached)
2163.ratel (04/17/20 13:31:29) (Detached)
1958.alpha (04/17/20 13:17:45) (Detached)
1774.zero (04/17/20 13:16:34) (Detached)
4 Sockets in /run/screen/S-ubuntu.
Attach to a specific screen via -d -R, e.g.: screen -d -R run. Detach with ctrl-a, ctrl-d. The alpha, zero, and ratel screens are for dgraph. THe run screen is for the API. Commands for restarting each, replacing the IP address as necessary:
docker run -it -p 5080:5080 --network dgraph_default -p 6080:6080 -v ~/zero:/dgraph dgraph/dgraph:latest dgraph zero --my=172.31.12.209:5080
docker run -it -p 7080:7080 --network dgraph_default -p 8080:8080 -p 9080:9080 -v ~/recipy_data:/dgraph dgraph/dgraph:latest dgraph alpha --lru_mb=1024 --zero=172.31.12.209:5080 --my=172.31.12.209:7080
docker run -it -p 8000:8000 --network dgraph_default dgraph/dgraph:latest dgraph-ratel
Currently a single-host deployment. Full production env will migrate to HA. Data can be populated via python3 manage.py. Will create the schema and insert two small sample recipes.