fix(masking): validate unmatched columns and support snake_case matching

[kevincostner17]

Supersedes #269. This branch carries the original commit by @Voyagerroc-Code (opened as PR #269 by @Voyagerroc-Lab), with authorship preserved, plus review changes on top. Thank you for the fix!

Summary

A masking rule whose columns matched no column did nothing. For example, freshdata clean --mask Email:hash on a frame with an email column wrote the raw values and exited 0. Column resolution now matches by snake_case name, records names that match nothing, and can raise for them.

Behaviour changes

• A MaskingRule column name masks every column with the same name or the same snake_case form: "First Name" masks first_name, and "email" masks both email and Email.
• Listed names that match no column are recorded in the new MaskReport.unmatched_columns, which also appears in MaskReport.to_dict().
• New MaskingRule.strict, default False. With strict=True, or mask_dataframe(..., strict=True), unmatched names raise ValueError naming them. The mask_dataframe argument overrides the rule's setting.
• freshdata clean --mask COLUMN:STRATEGY rules are strict, so the command exits 1 with a one-line error when COLUMN matches no column.
• The duplicate-label pre-check in anonymize never raises for absent columns.

Commits

1. fix(masking): validate unmatched columns and support snake_case matching, by @Voyagerroc-Code (the original from fix(masking): validate unmatched columns and support snake_case matching #269).
2. fix(masking): non-strict by default, mask every snake_case match, strict CLI --mask. Review changes:
   • non-strict default, so shared rule sets keep working
   • mask every snake_case match instead of only the last one
   • strict CLI rules
   • non-raising pre-check in anonymize
   • E501 fixes, docstrings, changelog
3. test(masking): cover polars snake_case matching and strict rules in clean_enterprise. Adds tests and moves the changelog entry to Changed.

Tests

• mask_dataframe:
  • snake_case matching
  • strict mode raises
  • unmatched names recorded by default
  • the strict= argument overrides the rule
  • every snake_case twin masked
  • polars path with snake_case matching
• fd.anonymize: a shared rule with an absent column; a strict rule alongside duplicated labels elsewhere.
• clean_enterprise:
  • a strict rule with a missing column raises ValueError naming it
  • a non-strict run completes and reports the column in result.mask_report.unmatched_columns
• CLI:
  • --mask non_existent:hash exits 1 with a one-line error
  • --mask Email:hash masks email

Verification

Run on main cbd1967 plus these commits:

• ruff check .: all checks passed
• mypy src/freshdata: no issues
• pytest -m "not online and not large", Python 3.12: 5603 passed, 13 skipped
• pytest -m "not online and not large", Python 3.9 / pandas 1.5: 5599 passed, 17 skipped

Closes #251

[coderabbitai]

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[github-actions]

FreshData benchmark report — performance

• freshdata: ?
• python: ?
• platform: ?

fixture	n_rows	n_cols	p50 s	p95 s	peak MB	repair %	false-repair %	preserve %	trust	monotonic	export %

Authored-code reduction (Metric 6)