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mlr-validator's Introduction

MLR-Validator

Validates inserts and updates to the MLR system

Build Status Coverage Status

This project has been built and tested with python 3.6.x. To build the project locally you will need python 3 and virtualenv installed.

% virtualenv --python=python3 env
% env/bin/pip install -r requirements.txt

To run the tests:

env/bin/python -m unittest

To run the application locally execute the following:

% env/bin/python app.py

The swagger documentation can then be accessed at http://127.0.0.1:5000/api

Default configuration variables can be overridden be creating a .env file. For instance to turn debug on, you will want to create an .env with the following:

DEBUG = True

The two docker files provided pull the artifact from cida.usgs.gov/artifactory. The build type and version should be specfied as build-arg's when building the image. The argument build_type should be 'snapshots' or 'releases'. The artfact_version should be the version of the usgs-wma-mlr-validator that you want to be used in the docker container. The optional build argument, 'listening_port' can be specified and defaults to 7010. This port will be exposed by the container. To build within the DOI network, use Dockerfile-DOI and place the DOI cert in '/rootcrt'. Below is an example of how to build and run.

% docker build --build-arg artifact_version=0.1.0.dev0 --build-arg build_type=snapshots -t validator -f Dockerfile-DOI .
% docker run --publish 5000:7010 validator

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