devonwalshe/pd

Pipeline discovery data match application

Prototype application to facilitate data matching between pipeline inspections.

Project setup

Pre-requisites:

• postgres >= 9.5
• python >= 3.6

1. Clone the repository:

$ git clone [email protected]:devonwalshe/pd.git && cd pd

2. Install python dependencies:

$ pip install -r requirements.txt

3. Bootstrap seed data

$ createdb pd $ python bootstrap.py

4. Start flask api server:

$ python -m api.api

5. test API server response:

http://localhost:5000/pipelines

6. Start frontend

cd frontend && PORT=3002 npm run dev

6. Navigate to frontend

http://localhost:3002

Project Components

• API
  • Python ORM layer peewee to handle data interface
  • Python webserver flask-restful exposing a REST API
• Data
  • Inspection run test data
  • Matcher output test data
  • Database dumps
• Frontend
  • Frontend application facilitating the manual input for the data match (...)
• Matcher
  • Python application powering the automated data match
• Tests
  • application wide tests

Introspecting application models

The model definitions, including their attributes and relations are found in api/models/models.py

These don't necessarily make it clear which data is available on each item in the database, so following is instructions to get json like responses from each model:

1. Start an interactive python session from the project root: $ python (Alternatively you can use ipython which can be installed with pip install ipython)
2. Load in all the model definitions: from api.models.models import *
3. Get a single instance of any given model: item = PipeSection.get_by_id(1) (you can replace PipeSection with any model from the api/models/models.py file)
4. Introspect the model relations and associated data: model_to_dict(item) or model_to_dict(item, recurse=False) if you don't want to include the relations