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EtherEye

An HTTP server used to keep an eye on gas prices for Ethereum.

Usage

  • /gas Returns current fast, average, and low price in Gwei. Example response:
{"error": false, "message": { "fast": 121, "average": 62, "low": 35, "blockNum": 14263482 }}
  • /average?fromTime=<ut>&toTime=<ut> Returns average gas price (average of recorded fast, average, and low in time period, averaged) recorded between two unix timestamps. Example response:
{"error": false, "message": { "averageGasPrice": 337, "fromTime": 123, "toTime": 1645461834 }}

Setup

  1. Copy .env.example to .env and replace the username and password to the desired credentials to the MongoDB database along with the database name (which will run in Docker, not a pre-existing database).
  2. Adjust FETCH_INTERVAL to configure how frequently the server reaches out to EthGasStation for new predictions (in seconds).
  3. Run docker-compose -f docker-compose.prod.yml up to run in production mode.
    • If you would like to run in development mode, run docker-compose up instead. This will watch and reload the code on changes and will enable debug logs.

Decisions & Reasoning

  • MongoDB isn't configured to store a log file on disk since Docker's log command reads from stdout (which MongoDB is logging to)
  • EthGasStation.info was utilized because it does not require an API key
  • All numbers returned from this API use Gwei to measure price of gas and
  • Average is rounded since the example response in the challenge had integers.

Troubleshooting

  • If you are having issues with running the server or if you made changes and they don't appear on production mode try running docker-compose build to rebuild the Docker image for the server.

Other notes

There are a few things that I would add before going to production with this:

  • Automatically catching exceptions server-wide and handling them like the API endpoints handle them.
  • Inquire about the usage of this API and consider returning cached responses if EthGasStation API is unavailable or a price was fetched within x seconds.
  • While there are error strings, ideally I would include stable machine-readable error codes to ease development for users of the API and minimize required changes.
  • Most importantly, I'd write tests for this code. If the API is going live it wouldn't be fun to know it's broken in production. However, I have not used Typescript before this challenge and did not have the time to explore testing.

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