Use shared Redis cache for jhu data

[Kilo59]

implements #304

Formerly all gunicorn workers would have to independently make HTTP requests to the various data sources. This is very inefficient and the problem is compounded when an error pulling from one data source occurs, causing a working timeout, a new worker process to be started up and all caches have to be from scratch.

This PR uses redis to be used as a shared cache for all jhu data. It falls back to an in-memory cache if redis is not available at startup.

Other changes

• move pylint config to `pyproject.tomal
• use pydantic for config management

Future improvements

1. use redis for nyt, csbs data
2. update/simplify/refactor caching logic to work more seamlessly with either redis or in-memory fallback.
3. update Docker compose to use redis container
4. build the cache at application startup instead of waiting for workers to spinup.
5. optimize redis connection handling and pool management