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describe() to describe a datasetcheck_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 checksstop_on_schema_fail to check_data() to
optionally stop when schema checks failfilter_fails() to ignore schema/reference rows
and only process row rules from check_data() resultsdetect_backend()
fallback to dplyr when input is a data.frame
and data.table is unavailabledata_column(), rule_meta()) and reference
checks (reference_rule())ruleset(), check_data(),
read_rules(), and write_rules() for v1
schema-aware workflows; keep rule() as row-level API (no
col_rule())sample_data dataset (mixed types, NAs,
datetime) for examples and testsreference_rule() and extend examples in
ruleset(), check_data(),
reference_rule(), and data_column() to show
combined schema + relational workflows>= 1.5.1.9002 in all
DuckDB-backed tests via
skip_if_not_installed("duckdb", "1.5.1.9002")fail_on_X to stop_on_Xstop_on_fail to [check_data()], so
that the examples using read_custom() make sense (eg in the
Readme); thanks FedericoComoglio for
pointing it out!detect_backend()] to allow user the check which
backend is usedfilter_fails() allows the first argument to be a
ruleset and not only a result of
check_data()NEWS.md file to track changes to the
package.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.