Commit Graph

2 Commits

Author SHA1 Message Date
8dfc6ad8ae feat(analyze): add mixed_line_endings + near_duplicate_rows detectors
Two more detectors close the analyzer gap list:

mixed_line_endings (warn, tool=02): scans raw bytes for combinations of
  CRLF / LF / bare CR. Disaster pattern after multi-source concat
  (Windows + macOS + Linux exports stitched together). Operates on raw
  bytes only — DataFrame-mode analyze() skips it because raw bytes
  aren't available. _load_for_analysis now returns the raw bytes
  alongside the DataFrame and repair result so the detector has them.

near_duplicate_rows (info, tool=01): cheap dedup signal — strip and
  lowercase every string column, then count df.duplicated(). Catches the
  most common case (same customer entered twice with subtle formatting
  differences) without paying for fuzzy matching. Anything more
  sophisticated stays in tool 01.

Six new tests cover both detectors plus the dataframe-mode skip path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 16:09:42 +00:00
edf6ccf90b feat(analyze): upload-time data quality analyzer
Pure, advisory scan over an uploaded file or DataFrame that returns a list of
Finding objects naming each issue, the affected count, and which downstream
tool can fix it. The GUI uses this to badge tool nav items at upload; the CLI
will print findings as a table or JSON.

src/core/analyze.py:
  Finding dataclass (id, severity, tool, count, description, column, samples)
  analyze(source, *, sample_rows=1000, repair_result=None) -> list[Finding]
    - source: DataFrame, path, or str. Path scans first 1000 rows.
    - When source is a path, runs the same pre-parse repair the tool pages
      will use; the resulting RepairResult is auto-surfaced as csv_*
      findings. A caller-supplied repair_result wins so non-default repair
      flags are respected.
  Detectors (each independent, samples capped at 5):
    - smart_punctuation_in_data        -> 02
    - nbsp_or_unicode_whitespace       -> 02
    - zero_width_or_invisible          -> 02
    - dirty_column_headers             -> 02
    - whitespace_padding               -> 02
    - null_like_sentinels              -> 04
    - suspected_mojibake               -> 02 (Tier 2)
    - mixed_case_email_column          -> 02 case op
    - leading_zero_ids                 -> informational, no tool
  Helpers: findings_by_tool() for sidebar grouping, to_dict() for JSON.

Detectors are decoupled from the GUI display layer — they emit stable tool
ids ("02_text_cleaner") and the GUI maps those to display names.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 15:41:36 +00:00