Aromatic

ArangoDB Modelling Layer based on Pydantic and inspired by Odmantic

Reached version 0.0.2 - Baby Steps

It now supports all of the following types

• str
• int
• List
• Tuple
• Naive datetime
• Naive date

v0.0.3 - Objective - Jun 27

it now supports CRUD on the following types

• Work on the following types
  • Embedded Models (are simply Pydantic BaseModels, likely to change to accomodate invalid name error)
  • List
  • Dict
  • datetime
  • date
  • Any
  • con* types from pydantic

See main.py for usage.

Running Integration Tests (units coming soon)

Setting up ArangoDB for Integration Tests

1. By default, expecting ArangoDB to be running at http://localhost:8529/

HOSTS = "http://localhost:8529"
USERNAME = "root"
PASSWORD = "openSesame"
DATABASE = "romatic_test"

2. To start a docker container with default credentials

docker run --name arango -d -p 8529:8529 -e ARANGO_ROOT_PASSWORD=openSesame arangodb/arangodb:latest

3. Navigate to http://localhost:8529 on your browser, login with set credentials

4. Select DB _system, on the left hand pane, select Databases > Add Database and create a new DB (we expect it to be romatic_test but if you want to change, feel free to do so)

5. In case the credentials, host, port and database varies in your system, feel free to set that in test/conftest.py

Running the Tests

To run Integration tests, cd into the git directory

pytest -v

To check coverage report

coverage run -m pytest -v
coverage report

Name                    Stmts   Miss Branch BrPart  Cover
---------------------------------------------------------
aromatic/__init__.py        0      0      0      0   100%
aromatic/basemodel.py      20      0      8      0   100%
aromatic/engine.py        145     61     76      7    48%
aromatic/errors.py         19      9      6      0    40%
---------------------------------------------------------
TOTAL                     184     70     90      7    53%

It is strongly advised that you take appropriate precautions when going outside due to covid. And do not run on production if you're not willing to fix a lot of bugs.