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Object Storage API

This is a Python microservice created using FastAPI that provides a REST API to upload and download attachments and images to and from an S3 object store.

How to Run

This microservice requires a MongoDB and S3 object storage instance to run against.

Prerequisites

  • Docker and Docker Compose installed (if you want to run the microservice inside Docker)
  • Python 3.12, MongoDB 7.0 and MinIO 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 object_storage_api/.env.example object_storage_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 object_storage_api/logging.example.ini object_storage_api/logging.ini

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 start

  • A MongoDB instance that can be accessed at localhost:27018 using root as the username and example as the password
  • A MinIO instance at localhost:9000 with a console that can be accessed at localhost:9001 using root as the username and example_password as the password
  • 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:8002 and its Swagger UI could be accessed at http://localhost:8002/docs. A MongoDB instance should also be running at http://localhost:27018.

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 object_storage_api_image .

  2. Start the container using the image built and map it to port 8002 locally):

    docker run -p 8002:8000 --name object_storage_api_container object_storage_api_image

    or with values for the environment variables:

    docker run -p 8002:8000 --name object_storage_api_container --env DATABASE__NAME=ims object-storage_api_image

    The microservice should now be running inside Docker at http://localhost:8002 and its Swagger UI could be accessed at http://localhost:8002/docs.

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]
pip install -r requirements.txt

  3. Create a .env file alongside the .env.example file. Use the example file as a reference and modify the values accordingly. You may need to update the port in DATABASE__HOST_AND_OPTIONS if running the database outside of docker.

    cp object_storage_api/.env.example object_storage_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 object_storage_api/logging.example.ini object_storage_api/logging.ini

  5. Start the microservice using FastAPI's CLI:

    fastapi dev object_storage_api/main.py

    The microservice should now be running locally at http://localhost:8002. The Swagger UI can be accessed at http://localhost:8002/docs.

Using mock data for testing [Optional]

Generating mock data

To populate the database and object storage with mock data for testing IMS first ensure both inventory-management-api and object-storage-api are running in docker and then run.

python ./scripts/dev_cli.py generate -c

This will clear the database and MinIO storage, fetch existing entities from the inventory-management-system-api and generate and add mock data for them.

You can also generate mock attachments just for specific entities by repeatedly using -e ENTITY_ID. This will ensure the entity has at least one attachment and image.

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 Object Storage Service API
API__DESCRIPTION The description of the API which is added to the generated OpenAPI. No This is the API for the Object Storage Service
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
OBJECT_STORAGE__ENDPOINT_URL The URL of the object storage S3 endpoint. Yes
OBJECT_STORAGE__ACCESS_KEY The access key to use to authenticate with the S3 object storage. Yes
OBJECT_STORAGE__SECRET_ACCESS_KEY The secret access key to use to authenticate with the S3 object storage. Yes
OBJECT_STORAGE__BUCKET_NAME The name of the S3 bucket to use for object storage. Yes
OBJECT_STORAGE__PRESIGNED_URL_EXPIRY_SECONDS The expiry time of presigned URLs. Yes
ATTACHMENT__MAX_SIZE_BYTES The maximum file size of an attachment given in bytes. Note: File systems use a factor of 1024 for GB, MB and KB instead of 1000, so here the former is expected despite them really being GiB, MiB and KiB. Yes
IMAGE__THUMBNAIL_MAX_SIZE_PIXELS The maximum width/height of generated image thumbnails. The actual width and height should maintain the original aspect ratio but neither the width nor height will exceed this value. 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.