NEWS

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nycOpenData 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• Revised vignettes to align with the new catalog-driven architecture and remove outdated wrapper-function references.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.