This project is a microservice that provides risk reports on companies through GraphQL. You can learn more about GraphQL by following the given link.
These instructions should get you started on this service.
Here are the requirements that you need to have before starting on this project.
First, we need to clone this project on your local machine. Below is a commandline to clone this project to your local machine.
git clone https://github.com/d-risk/mock-api-gateway.git
After cloning this project, it is time to create and populate a database for this service to use.
The database should be created and populated before continuing further.
In development mode, this service uses a file-based database Sqlite named db.sqlite3.
Below is the commandline to create and populate the database with randomly generated data.
python manage.py populatedb --companies 100 --singtel
The first argument --companies specifies how many companies to be generated.
The above example --companies 100 will create 100 companies.
The --singtel will add a risk report for the company Singapore Telecommunication Limited.
There are two ways to start this service: as a Docker container or using Python.
If you would like to run this service as a Docker container, there is a Dockerfile to create a Docker image.
Below is the commandline to build a Docker image.
docker build -t d-risk/mock-api-gateway .
Once the Docker image is built, it is time to run the image. Below is the commandline to run the image.
docker run --name mock-api-gateway -p 8000:8080 --rm -it d-risk/mock-api-gateway
When the Docker container is initialized, you can interact with this service using a browser through the given URL.
For example, using the above example, it would be localhost:8000.
The port is the port that is mapped to the Docker container.
The Python approach is meant for you to run this service on your local machine. It is recommended to create a virtual environment to install the required packages. Create a virtual environment as indicated below.
python -m venv .venv
This will create the .venv directory for the virtual environment.
To switch to the virtual environment, follow the commandline below.
On Windows:
.venv\Scripts\activate
On Unix or MacOS:
source .venv/bin/activate
Once in the virtual environment, install the dependencies as indicated below.
pip install -r requirements.freeze.txt
Once the dependencies are installed, you can start this service using the commandline given below.
python manage.py runserver
Once the service is started, use a browser and go to the given URL.
Usually, it is localhost:8000.
The Docker image is the recommended way to deploy this service. Once the Docker image is created, it can be uploaded to a repository of your choice and deployed on your preferred cloud platform.