dqcheckr 0.2.0

New features

• New compare_snapshots() and list_snapshots() functions for drift analysis. Compares any two historical snapshots and optionally renders an HTML drift report with per-column statistical drift, schema changes, and trend charts.
• New resolve_col_type() function: returns the effective type for a column, respecting per-column type overrides set in the column_types config key.
• New QC-15 outlier detection check (check_outliers()). Configured via max_z_score and/or iqr_fence_multiplier; skipped silently when neither is set.
• check_key_uniqueness() (QC-12) now supports composite keys: set key_columns to a character vector in the dataset YAML.
• check_min_row_count() (QC-14) gains max_row_count and max_file_size_mb thresholds.
• col_threshold() and table_threshold() added as internal helpers; column_rules per-column threshold overrides are now correctly stored in column_snapshots.threshold (G-01).

Behaviour changes

• Reports migrated from rmarkdown to Quarto. render_report() uses quarto::quarto_render() and returns NULL with a warning when Quarto CLI is not installed.
• compare_schema() (CP-02) split into three separate result objects: CP-02a (new columns), CP-02b (dropped columns), CP-02c (type changes).
• compare_non_numeric_rate() (CP-07) now always emits a result for every eligible column, including PASS for columns where the rate did not increase (G-02).
• run_timestamp is now stored in ISO-8601 UTC format (2026-01-01T12:00:00Z) rather than local time (RC-07).
• snapshots table gains three columns on first use: comparison_mode, render_status, and type_changed_cols_vs_previous. Existing 0.1.x databases are auto-migrated on the first 0.2.0 run.
• SQLite foreign key enforcement is now explicitly enabled on every connection (PRAGMA foreign_keys = ON).
• detect_files() uses filename as a secondary sort when two files share the same modification time, making folder-mode ordering deterministic (RC-01).
• check_allowed_values() (QC-09), compare_new_values() (CP-05), and compare_dropped_values() (CP-06) cap observed at 20 values with an "... and N more" suffix (RC-04, RC-05).
• check_non_numeric() (QC-11) gains a warn_non_numeric_rate config key for a separate WARN threshold (C-01).
• compare_missing_rate() (CP-03) gains a missing_rate_change_severity config key (warn / fail) (B-07).
• compare_column_order() (CP-08) gains a column_order_severity config key that overrides the format-based default (C-02).
• compute_col_stats() stores the numeric mean under the key numeric_parseable_mean (renamed from numeric_mean) to clarify that non-parseable values are excluded from the calculation (C-04).
• Comparison summary in the HTML report now lists all FAIL/WARN messages as a bullet list rather than picking the single worst result (C-05).
• compare_snapshots() uses the full merged per-dataset config for drift threshold comparisons, so *** markers match the original check run for datasets with rule_overrides (G-05/G-06).
• compute_col_stats() unused qc_results parameter removed (D-01).

dqcheckr 0.1.1

• flag_new_columns, flag_dropped_columns, flag_type_changes (in CP-02) and flag_column_order_change (CP-08) are now honoured. Setting any flag to false suppresses the corresponding check from the report. Schema changes are still tracked in the SQLite snapshot regardless of flags.
• type_inference_threshold is now configurable per dataset via rule_overrides in the dataset YAML (or default_rules in the global config). Previously fixed at 90%, it now defaults to 90% if not set. Affects QC-06, QC-07, QC-08, QC-11, CP-02, CP-04, CP-05, CP-06, and CP-07.

dqcheckr 0.1.0

Initial release.

• Single-snapshot quality checks: QC-01 to QC-14 (missing rate, empty columns, duplicate rows, row/column counts, inferred types, numeric stats, distinct counts, allowed values, numeric bounds, non-numeric rate, key uniqueness, regex pattern, minimum row count) and SC-01/SC-02 (schema contract).
• Version comparison checks: CP-01 to CP-08 (row count change, schema diff, missing rate change, numeric mean shift, new/dropped distinct values, non-numeric rate change, column order).
• Custom organisation-specific checks via a plain R file.
• Self-contained HTML report with check tables, historical trend charts, and column statistics appendix.
• SQLite snapshot database for long-term trend tracking.
• Supports CSV and fixed-width (FWF) file formats.
• Configuration via global dqcheckr.yml and per-dataset YAML files.