Changelog • dataverifyr

dataverifyr 0.1.11

Add describe() to describe a dataset
check_data() now includes schema checks in the output by default (check_type as first result column), including explicit rows for column existence and declared type checks
add stop_on_schema_fail to check_data() to optionally stop when schema checks fail
update filter_fails() to ignore schema/reference rows and only process row rules from check_data() results
Add explicit regression test for detect_backend() fallback to dplyr when input is a data.frame and data.table is unavailable
Add structured ruleset internals for schema metadata (data_column(), rule_meta()) and reference checks (reference_rule())
Extend ruleset(), check_data(), read_rules(), and write_rules() for v1 schema-aware workflows; keep rule() as row-level API (no col_rule())
Add exported sample_data dataset (mixed types, NAs, datetime) for examples and tests
export reference_rule() and extend examples in ruleset(), check_data(), reference_rule(), and data_column() to show combined schema + relational workflows
Require DuckDB version >= 1.5.1.9002 in all DuckDB-backed tests via skip_if_not_installed("duckdb", "1.5.1.9002")

CRAN release: 2024-01-10

rename args fail_on_X to stop_on_X
adds stop_on_fail to [check_data()], so that the examples using read_custom() make sense (eg in the Readme); thanks FedericoComoglio for pointing it out!
fix bug when dplyr backend is used + add tests; thanks FedericoComoglio for reporting the bug!
expose [detect_backend()] to allow user the check which backend is used

allow multiline rules in yaml file
fix bug where no fails in filter_fails would result in error
Fix bug where multiline rules would break
fix minor error in Readme
filter_fails() allows the first argument to be a ruleset and not only a result of check_data()