Unlocking the Power of Redux Logging

The Importance of Data Fetching

Fetching and sending data over the network is one of the most error-prone aspects of application development. Issues can arise from connectivity problems, unexpected data, or incorrect logic. To mitigate these risks, libraries like Apollo Client for GraphQL and Redux Query for REST provide a way to fetch data via Redux.

Redux Query: A Closer Look

Redux Query uses Redux as a persistence layer, allowing developers to inspect logs and see what data has been fetched and the status of in-flight requests. For example, when a query is initialized, Redux Query emits a REQUEST_START action with all the request information, making it easy to debug.

{
  type: 'REQUEST_START',
  payload: {
    request: {
      url: '/api/data',
      method: 'GET',
      headers: {
        'Content-Type': 'application/json'
      }
    }
  }
}

Storing State in Redux

Redux Query also stores its internal state in the Redux store, providing a wealth of information on in-flight requests, query count, and timings. This state object can be inspected to debug issues, putting full context on all network activity in the Redux logs.

{
  reduxQuery: {
    requests: {
      '/api/data': {
        status: 'in-flight',
        startTime: 1643723400,
        endTime: null
      }
    },
    queryCount: 1,
    timings: {
      '/api/data': 500
    }
  }
}

Rolling Your Own Data Fetching Framework

For a simpler approach, developers can create their own data fetching framework by dispatching explicit actions when querying and receiving data from the network. By being explicit with Redux actions for each part of the request lifecycle, it becomes easier to debug potential race conditions or network errors.

dispatch({
  type: 'FETCH_DATA_REQUEST',
  payload: {
    url: '/api/data',
    method: 'GET'
  }
});

dispatch({
  type: 'FETCH_DATA_SUCCESS',
  payload: {
    data: [...]
  }
});

dispatch({
  type: 'FETCH_DATA_FAILURE',
  payload: {
    error: 'Network error'
  }
});

Best Practices for Debugging

Using libraries and patterns that put data through Redux helps build more debuggable applications by leaving a rich audit trail. When architecting new features, ask yourself:

• Will this feature be error-prone?
• Would being able to view its state in the Redux logs help solve future bugs?

By following these best practices, you can create more robust and debuggable applications that make the most of Redux’s logging capabilities.