Inventory Management System API

This is a Python microservice created using FastAPI that provides a REST API for the Inventory Management System.

How to Run

This microservice requires a MongoDB instance to run against.

Prerequisites

• Docker and Docker Compose installed (if you want to run the microservice inside Docker)
• Python 3.12 and MongoDB 7.0 installed on your machine (if you are not using Docker)
• Public key (must be OpenSSH encoded) to decode JWT access tokens (if JWT authentication/authorization is enabled)
• MongoDB Compass installed (if you want to interact with the database using a GUI)
• This repository cloned

Docker Setup

Ensure that Docker is installed and running on your machine before proceeding.

1. Create a .env file alongside the .env.example file. Use the example file as a reference and modify the values accordingly.

   cp inventory_management_system_api/.env.example inventory_management_system_api/.env

2. Create a logging.ini file alongside the logging.example.ini file. Use the example file as a reference and modify it accordingly:

   cp inventory_management_system_api/logging.example.ini inventory_management_system_api/logging.ini

3. Create a keyfile for mongodb to use for replica sets

   openssl rand -base64 756 > ./mongodb/keys/rs_keyfile
   chmod 0400 ./mongodb/keys/rs_keyfile
   sudo chown 999:999 ./mongodb/keys/rs_keyfile

4. (Required only if JWT Auth is enabled) Create a keys directory in the root of the project directory and inside it create a copy of the public key generated by the authentication component. This is needed for decoding of JWT access tokens signed by the corresponding private key.

Using docker-compose.yml

The easiest way to run the application with Docker for local development is using the docker-compose.yml file. It is configured to spin up a MongoDB instance that can be accessed at localhost:27017 using root as the username and example as the password. It also starts the application in a reload mode using the Dockerfile.

1. Build and start the Docker containers:

   docker-compose up

   The microservice should now be running inside Docker at http://localhost:8000 and its Swagger UI could be accessed at http://localhost:8000/docs. A MongoDB instance should also be running at http://localhost:27017.

2. Follow the post setup instructions

Using Dockerfile

Use the Dockerfile to run just the application itself in a container. Use this only for local development (not production)!

1. Build an image using the Dockerfile from the root of the project directory:

   docker build -f Dockerfile -t inventory_management_system_api_image .

2. Start the container using the image built and map it to port 8000 locally (please note that the public key volume is only needed if JWT Auth is enabled):

   docker run -p 8000:8000 --name inventory_management_system_api_container -v ./keys/jwt-key.pub:/inventory-management-system-api-run/keys/jwt-key.pub inventory_management_system_api_image

   or with values for the environment variables:

   docker run -p 8000:8000 --name inventory_management_system_api_container --env DATABASE__NAME=ims -v ./keys/jwt-key.pub:/inventory-management-system-api-run/keys/jwt-key.pub inventory_management_system_api_image

   The microservice should now be running inside Docker at http://localhost:8000 and its Swagger UI could be accessed at http://localhost:8000/docs.

3. Follow the post setup instructions

Using Dockerfile.prod

Use the Dockerfile.prod to run just the application itself in a container. This can be used for production.

1. Build an image using the Dockerfile.prod from the root of the project directory:

   docker build -f Dockerfile.prod -t inventory_management_system_api_image .

2. Start the container using the image built and map it to port 8000 locally:

   docker run -p 8000:8000 --name inventory_management_system_api_container -v ./keys/jwt-key.pub:/inventory-management-system-api-run/keys/jwt-key.pub inventory_management_system_api_image

   or with values for the environment variables:

   docker run -p 8000:8000 --name inventory_management_system_api_container --env DATABASE__NAME=test-ims -v ./keys/jwt-key.pub:/inventory-management-system-api-run/keys/jwt-key.pub inventory_management_system_api_image

   The microservice should now be running inside Docker at http://localhost:8000 and its Swagger UI could be accessed at http://localhost:8000/docs.

3. Follow the post setup instructions

Local Setup

Ensure that Python is installed on your machine before proceeding.

1. Create a Python virtual environment and activate it in the root of the project directory:

   python -m venv venv
   source venv/bin/activate

2. Install the required dependencies using pip:

   pip install .[dev]

3. Create a .env file alongside the .env.example file. Use the example file as a reference and modify the values accordingly.

   cp inventory_management_system_api/.env.example inventory_management_system_api/.env

4. Create a logging.ini file alongside the logging.example.ini file. Use the example file as a reference and modify it accordingly:

   cp inventory_management_system_api/logging.example.ini inventory_management_system_api/logging.ini

5. Create a keyfile for MongoDB to use for replica sets

   openssl rand -base64 756 > ./mongodb/keys/rs_keyfile
   sudo chmod 0400 ./mongodb/keys/rs_keyfile
   sudo chown 999:999 ./mongodb/keys/rs_keyfile

6. (Required only if JWT Auth is enabled) Create a keys directory in the root of the project directory and inside it create a copy of the public key generated by the authentication component. This is needed for decoding of JWT access tokens signed by the corresponding private key.

7. Start the microservice using FastAPI's CLI:

   fastapi dev inventory_management_system_api/main.py

   The microservice should now be running locally at http://localhost:8000. The Swagger UI can be accessed at http://localhost:8000/docs.

8. Follow the post setup instructions

9. To run the unit tests, run :

   pytest -c test/pytest.ini test/unit/

10. To run the e2e tests, run:

pytest -c test/pytest.ini test/e2e/

11. To run all the tests, run:

pytest -c test/pytest.ini test/

Post setup instructions

When running for the first time there are a few extra steps required to setup the database. These instructions assume the database is running via docker, although the commands themselves can be adapted for a separate instance by removing the docker parts.

Setting up the database

Using dev_cli

For development the easiest way to setup the database is to use the included dev_cli script assuming you are using Linux. To initialise the database use

python ./scripts/dev_cli.py db-init

Manually

Initialising the replica set

For development replica sets are required to be able to use transactions. Once the mongodb instance is running use mongosh to login and run

rs.initiate( {
   _id : "rs0",
   members: [
      { _id: 0, host: "<hostname>:27017" }
   ]
})

replacing <hostname> with the actual hostname for the replica set.

For docker you may use

docker exec -i ims_api_mongodb_container mongosh --username 'root' --password 'example' --authenticationDatabase=admin --eval "rs.initiate({ _id : 'rs0', members: [{ _id: 0, host: 'ims_api_mongodb_container:27017' }]})"

Using mock data for testing [Optional]

Populating the database

The simplest way to populate the database with mock data is to use the already created database dump. If using docker for development you may use

python ./scripts/dev_cli.py db-import

to populate the database with mock data.

If you wish to do this manually the full command is

docker exec -i ims_api_mongodb_container mongorestore --username "root" --password "example" --authenticationDatabase=admin --db ims --archive < ./data/mock_data.dump

Otherwise there is a script to generate mock data for testing purposes given in ./scripts/generate_mock_data.py. To use it from your development environment first ensure the API is running and then execute it with

python ./scripts/generate_mock_data.py

Generating new mock data

Using dev_cli

The easiest way to generate new mock data assuming you are using Linux is via the dev_cli script. To do this use

python ./scripts/dev_cli.py db-generate

This will clear the database, import the default data e.g. units and then generate mock data. If the generate_mock_data.py script is changed, or if there are database model changes please use

python ./scripts/dev_cli.py db-generate -d

to update the ./data/mock_data.dump file and commit the changes.

Manually

The parameters at the top of the file can be used to change the generated data. NOTE: This script will simply add to the existing database instance. So if you wish to update the mock_data.dump, you should first clear the database e.g. using

docker exec -i ims_api_mongodb_container mongosh ims --username "root" --password "example" --authenticationDatabase=admin --eval "db.dropDatabase()"

Then generate the mock data, import the units and then update the ./data/mock_data.dump file using mongodump via

docker exec -i ims_api_mongodb_container mongodump --username "root" --password "example" --authenticationDatabase=admin --db ims --archive > ./data/mock_data.dump

Notes

Application Configuration

The configuration for the application is handled using Pydantic Settings. It allows for loading config values from environment variables or the .env file. Please note that even when using the .env file, Pydantic will still read environment variables as well as the .env file, environment variables will always take priority over values loaded from the .env file.

Listed below are the environment variables supported by the application.

Environment Variable	Description	Mandatory	Default Value
API__TITLE	The title of the API which is added to the generated OpenAPI.	No	Inventory Management System API
API__DESCRIPTION	The description of the API which is added to the generated OpenAPI.	No	This is the API for the Inventory Management System
API__ROOT_PATH	(If using a proxy) The path prefix handled by a proxy that is not seen by the app.	No
API__ALLOWED_CORS_HEADERS	The list of headers that are allowed to be included in cross-origin requests.	Yes
API__ALLOWED_CORS_ORIGINS	The list of origins (domains) that are allowed to make cross-origin requests.	Yes
API__ALLOWED_CORS_METHODS	The list of methods that are allowed to be used to make cross-origin requests.	Yes
AUTHENTICATION__ENABLED	Whether JWT auth is enabled.	Yes
AUTHENTICATION__PUBLIC_KEY_PATH	The path to the public key to be used for decoding JWT access token signed by the corresponding private key.	If JWT auth enabled
AUTHENTICATION__JWT_ALGORITHM	The algorithm to use to decode the JWT access token.	If JWT auth enabled
DATABASE__PROTOCOL	The protocol component (i.e. mongodb) to use for the connection string for the MongoClient to connect to the database.	Yes
DATABASE__USERNAME	The database username to use for the connection string for the MongoClient to connect to the database.	Yes
DATABASE__PASSWORD	The database password to use for the connection string for the MongoClient to connect to the database.	Yes
DATABASE__HOST_AND_OPTIONS	The host (and optional port number) component as well specific options (if any) to use for the connection string for the MongoClient to connect to the database. The host component is the name or IP address of the host where the mongod instance is running, whereas the options are <name>=<value> pairs (i.e. ?authMechanism=SCRAM-SHA-256&authSource=admin) specific to the connection. For a replica set mongod instance(s), specify the hostname(s) and any options as listed in the replica set configuration - prod-mongodb-1:27017,prod-mongodb-2:27017,prod-mongodb-3:27017/?authMechanism=SCRAM-SHA-256&authSource=admin For a standalone mongod instance, specify the hostname and any options - prod-mongodb:27017/?authMechanism=SCRAM-SHA-256&authSource=admin	Yes
DATABASE__NAME	The name of the database to use for the MongoClient to connect to the database.	Yes

JWT Authentication/Authorization

This microservice supports JWT authentication/authorization and this can be enabled or disabled by setting the AUTHENTICATION__ENABLED environment variable to True or False. When enabled, all the endpoints require a JWT access token to be supplied. This ensures that only authenticated and authorized users can access the resources. To decode the JWT access token, the application needs the public key that corresponding to the private key used for encoding the token. Once the JWT access token is decoded successfully, it checks that it has a username in the payload, and it has not expired. This means that any microservice can be used to generate JWT access tokens so long as it meets the above criteria. The LDAP-JWT Authentication Service is a microservice that provides user authentication against an LDAP server and returns a JWT access token.