Changes in version 0.2.2                        

Major improvements

This release continues the transition to a catalog-driven workflow for
accessing NYC Open Data datasets in R, emphasizing transparency,
reproducibility, and streamlined API access.

  - nyc_list_datasets() now serves as the primary entry point for
    discovering datasets available through the live NYC Open Data
    catalog.
  - nyc_pull_dataset() provides a unified interface for downloading
    datasets using either human-readable catalog keys or Socrata dataset
    UIDs.
  - Dataset keys are generated dynamically using
    janitor::make_clean_names() based on live catalog metadata.
  - Expanded support for flexible dataset discovery and retrieval
    without requiring dedicated dataset wrapper functions.

New features

  - Added support for flexible dataset selection using either:
      - human-readable catalog keys (e.g.,
        "motor_vehicle_collisions_crashes")
      - or stable Socrata dataset UIDs (e.g., "h9gi-nx95")
  - Added support for date filtering using date, from, and to arguments
    with user-specified date_field.
  - Improved filtering support with vectorized filters translated into
    SQL-style IN clauses.
  - Improved support for direct Socrata endpoint access through
    nyc_any_dataset().

Documentation

  - Substantially expanded README documentation to clarify:
      - package architecture
      - Socrata API workflows
      - SoQL usage
      - dataset keys versus UIDs
      - catalog-driven dataset retrieval
      - type coercion behavior
  - Improved function documentation for:
      - nyc_list_datasets()
      - nyc_pull_dataset()
      - nyc_any_dataset()
  - Updated examples to demonstrate:
      - realistic catalog search workflows
      - filtering
      - date-based queries
      - direct endpoint access
  - Revised vignettes to align with the new catalog-driven architecture
    and remove outdated wrapper-function references.
  - Added additional development and testing documentation for vcr and
    webmockr.

Internal improvements

  - Refactored internal request handling to support dynamic catalog
    lookup.
  - Improved validation for dataset identifiers, filters, and
    date-filtering parameters.
  - Improved handling of conservative heuristic-based type coercion.
  - Reduced reliance on dedicated dataset wrapper functions in favor of
    a unified interface.

Maintenance

  - Updated package citation information and version consistency across
    package documentation.
  - Continued improvements to API reliability, documentation clarity,
    and internal utilities.