Filtering strategy

Summary

Problem statement

The CommonGrants protocol needs a standardized approach to filtering across endpoints that balances consistency, flexibility, and ease of implementation.

Sub-questions

• Should filters be passed in the request body or as query parameters?
• If the request body accepts a filters parameter, should it be an object or an array?
• Which filter operators (e.g. eq, neq, gt, etc.) should be supported?
• How should the protocol support implementation-defined filters?

Decision drivers

• Consistency: Filters should be consistent across endpoints.
• Flexibility: Filters should support complex queries while keeping implementation straightforward.
• Compatibility: Filters should be easy to combine with pagination and sorting.
• Extensibility: Filters should provide a way to support implementation-defined filters.

Decision outcome

API endpoints that support filtering should be POST operations that accept a filters parameter in the request body. Filters will be defined using a standard schema to ensure consistency across different endpoints.

Filtering approach

• The filters parameter MUST be included at the root of the request body.
• Each filter MUST conform to the Filter schema, which contains:

Property	Type	Required	Description
operation	enum	Yes	The operation to perform on the value
value	any	Yes	The data to use for the filter operation

• Supported operations:

Operation	Description	Supported value types
eq	Equal to	string, number, boolean, date
neq	Not equal to	string, number, boolean, date
gt	Greater than	number, date
gte	Greater than or equal to	number, date
lt	Less than	number, date
lte	Less than or equal to	number, date
like	Contains	string
in	In list	array
not_in	Not in list	array
between	Between two values	range object with min and max properties

Custom filters

• If a route supports implementation-defined filters, it MUST include a customFilters property.
• This property must be an object whose values match the Filter schema.
• Unsupported custom filters should be ignored and reported in the filterInfo.errors property.

Examples

An example of a request body that includes a standard filter:

{
  "filters": {
    "title": {
      "value": "example",
      "operation": "like"
    },
    "closedDateRange": {
      "value": {
        "min": "2024-01-01",
        "max": "2024-01-31"
      },
      "operation": "between"
    }
  }
}

An example of a request body that includes both standard and custom filters:

{
  "filters": {
    "title": {
      "value": "example",
      "operation": "like"
    },
    "customFilters": {
      "agency": {
        "value": ["Department of Transportation"],
        "operation": "in"
      }
    }
  }
}

Consequences

• Positive
  • Establishes a consistent pattern for filtering across endpoints.
  • Supports more complex filters than query parameters.
  • Provide a consistent way to extend the protocol with implementation-defined filters.
• Negative
  • Passing filters in the request body makes it harder to cache requests.
  • Using an object to represent filters makes it harder to support complex queries that include multiple filters with the same property name.

Options considered

These are the other options we considered but did not choose.

Query parameters only

• Pros
  • Easy to implement for simple filters.
  • Fully cacheable in HTTP caches.
• Cons
  • Difficult to support complex filtering.
  • Doesn’t provide a way to support implementation-defined filters.

A filter request body parameter of type array

• Pros
  • Easy to understand.
  • Supports complex filtering with multiple filters for the same property.
  • Could support index-based filter logic (e.g. (1 AND 2) OR (3 AND 4)).
• Cons
  • Doesn’t provide a way to support implementation-defined filters.
  • Makes it harder to define standard and custom filters in the OpenAPI document.
  • Makes it harder for API servers to parse request bodies in a deterministic way.