OpenAQ API

Overview

This repository contains the source code for the OpenAQ API, a publicly-accessible API that provides endpoints to query the real-time and historical air quality measurements on the OpenAQ platform.

[!NOTE] This repository is for setting up and deploying the OpenAQ API. If you just wish to access the public API to query data from the OpenAQ platform, visit https://api.openaq.org or https://docs.openaq.org to learn more.

Package management

We are currently using Poetry to manage our dependencies and run locally.

Local development

In production, the OpenAQ API runs on AWS Lambda with the help of the mangum library. This allows the application to run in a serverless environment and take advantage of async Python and FastAPI routing. Despite the serverless deployment, running the API locally as a standard FastAPI application is largely unchanged, making local development much easier.

Settings

Settings can be loaded using .env files, and multiple files can be kept and used. The easiest way to manage multiple environment files is to add an extension describing your environment. For example, if I wanted to keep a production, staging and local environment, I would save them as .env.production, .env.staging and .env.local each with their own settings.

DATABASE_READ_USER=database-read-user DATABASE_WRITE_USER=database-write-user DATABASE_READ_PASSWORD=database-read-password DATABASE_WRITE_PASSWORD=database-write-password DATABASE_DB=database-name DATABASE_HOST=localhost DATABASE_PORT=5432 LOG_LEVEL=info

Running locally

The easiest way to run the API locally is to use uvicorn. Make sure that you have your settings (.env) file setup. Once that is done, you can run the following from the openaq_api directory. Variables from the .env files can be overrode by setting them inline.

```bash

Run using the default .env file

poetry run uvicorn openaq_api.main:app --reload --lifespan on `` You can also specify which.envfile to load by passing theENVvariable. This should not include the.env.` prefix

bash DOTENV=local poetry run uvicorn openaq_api.main:app --reload --lifespan on If you are connecting to our production environment you will AWS credentials therefor you may need to provdide the profile name to access the right credentials.

AWS_PROFILE=optional-profile-name \ DOTENV=production \ poetry run uvicorn openaq_api.main:app --reload --lifespan on And you can always override variables by setting them inline. This is handy for when you want to change something for the purpose of debugging. ```

Run the staging environment and add verbose logging

ENV=staging LOGLEVEL=debug uvicorn main:app --reload DOTENV=staging \ LOGLEVEL=debug \ poetry run uvicorn openaq_api.main:app --reload --lifespan on ```

Testing

From the root directory bash DOTENV=local poetry run pytest tests/

Rate limiting

In the production environment, rate limiting is handled in two places, AWS WAF and at the application level with Starlette Middleware. The application rate limiting is configurable via environment variables. The rate limiting middleware requires access to an instance of a redis cluster. For local development, docker can be a convenient method to set up a local redis cluster. With docker, use the following command:

sh docker run -e "IP=0.0.0.0" -p 7000-7005:7000-7005 grokzen/redis-cluster:7.0.7

Now a redis instance will be available at http://localhost:7000. Configure the REDISHOST to localhost and REDISPORT to 7000.

[!TIP] On some macOS systems port 7000 is used by Airplay which can complicate the mapping of ports from the Docker container. The easiest option is to disable the Airplay reciever in system settings. System settings -> General -> Airplay receiver (toggle off)

Rate limiting values

Rate limiting can be toggled off for local develop via the RATE_LIMITING environment variable. Other rate limiting values are: * RATE_AMOUNT_KEY - The number of requests allowed with a valid API key * RATE_TIME - The number of minutes for the rate

e.g. RATE_AMOUNT_KEY=5 and RATE_TIME=1 would allow 5 requests per 1 minute.

[!NOTE] With AWS WAF, rate limiting also occurs at the cloudfront stage. The application level rate limiting should be less than or equal to the value set at AWS WAF.

Deployment

Deployment is managed with Amazon Web Services (AWS) Cloud Development Kit (CDK). Additional environment variables are required for a full deployment to the AWS Cloud.

Deploying

python AWS_PROFILE=optional-profile-name DOTENV=production cdk deploy openaq-api-production

Platform Overview

openaq-fetch and openaq-fetch-lcs take care of fetching new data and writing to S3. Lambda functions defined in openaq-ingestor, then load data into the database, defined in openaq-db.

Contributing

There are many ways to contribute to this project; more details can be found in the contributing guide.