Add synthetic financial ledger fixture with accounting negatives (#496)

[muhammad-muneeb3]

What changed?

• Added a new synthetic test fixture tests/fixtures/financial_ledger.csv and its accompanying expectations file tests/fixtures/financial_ledger.expectations.json[cite: 1, 3].
• Extended parse_currency_parts in src/freshdata/semantic/experts.py to identify and parse parenthesized accounting negative values (e.g., (1,250.00)) as valid negative numeric values[cite: 1, 2].
• Added financial identifier checks via _MONEY_NAME in src/freshdata/engine/context.py and src/freshdata/semantic/context.py so amount and balance columns are not misclassified as id or text roles due to high cardinality[cite: 2].
• Registered financial_ledger in tests/expectations.py, generated the golden snapshot, and added targeted test coverage in tests/test_currency_locale.py[cite: 1, 2, 3].

Why?

Ensures FreshData robustly handles localized financial conventions—specifically parenthesized accounting negatives and currency formats—without regressing semantic detection or data cleaning pipelines[cite: 1].

Fixes #496[cite: 1]

How was it tested?

• New unit tests added in tests/
• Ran fast CI lane locally: pytest -m "not online and not large"
• Ran linting and type checks: ruff check . and mypy src/freshdata.

Targeted test command run locally:

pytest tests/test_currency_locale.py tests/test_realworld.py -k financial_ledger tests/test_golden.py -k financial_ledger tests/test_experts_guard_mutants.py -k currency --no-cov

## Any performance impact?

<!-- Will this change affect wall-clock runtime, memory allocation, or startup time? If yes, provide timings. -->

- [x] None / negligible
- [ ] Measured with `benchmarks/bench.py` (details below):

## Any compatibility concerns?

<!-- Does this change public API signatures, default behavior, or supported Python/pandas versions? -->

- [x] None / fully backward-compatible
- [ ] Deprecation or behavior change documented below:

## Documentation updated?

<!-- If user-facing behavior changed, did you update docs/, examples/, or CHANGELOG.md? -->

- [ ] Documentation updated in `docs/`
- [ ] Examples verified or updated
- [x] Note added under `[Unreleased]` in `CHANGELOG.md`


<!-- This is an auto-generated comment: release notes by coderabbit.ai -->

## Summary by CodeRabbit

* **Bug Fixes**
  * Improved recognition of financial columns, including high-cardinality text columns with money-related names.
  * Currency parsing now handles parenthesized amounts as negative values, including amounts without a currency symbol or code.
* **Tests**
  * Added financial-ledger coverage for automatic amount and date conversion, expected transaction values, and repeatable results.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

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📝 Walkthrough

Walkthrough

The change updates monetary column classification and currency parsing for parenthesized accounting negatives. It adds a financial ledger fixture, expected results, a golden report, and an integration test.

Changes

Financial ledger handling

Layer / File(s)	Summary
Monetary column classification src/freshdata/engine/context.py, src/freshdata/semantic/context.py	Money-related column names no longer match two identifier-classification checks. Free-text columns can qualify as money-like when they meet the existing checks and are not identifier-like.
Accounting-negative currency parsing src/freshdata/semantic/experts.py	Currency parsing recognizes parenthesized amounts as negative values. Parentheses also count as a currency marker; other inputs still require a symbol or code.
Financial ledger fixture and integration test tests/expectations.py, tests/fixtures/financial_ledger.expectations.json, tests/fixtures/golden/financial_ledger.balanced.report.json, tests/fixtures/golden_diff_summary.jsonl, tests/test_currency_locale.py	Fixture expectations cover row counts, idempotence, conversions, and transaction values. The integration test checks cleaned row counts, dtype prefixes, and selected amounts.

Priority: ⬇️ Low

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Feature

Suggested reviewers: johnnywilson-portfolio, kevincostner17, johnnywilson16

Merge Risk: 🟠 High · up to 02d2f

The new accounting-negative parsing can change financial and unit values without warning. Unit values in parentheses can become negative amounts, ambiguous separators can be guessed and applied automatically, and a minus sign inside parentheses reverses the amount's sign. Columns such as payment_id can also lose identifier protection. These issues can corrupt cleaned ledger data and should be fixed before merge.

🚥 Pre-merge checks | ✅ 3 | ❌ 2

❌ Failed checks (1 warning, 1 inconclusive)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 5 files. (3 skipped: 3…	Write docstrings for the functions missing them to satisfy the coverage threshold.
Linked Issues check	❓ Inconclusive	The reviewable changes support #496. They add accounting-negative parsing, financial-name handling, fixture registration, expectations, golden data, and an integration test for fd.clean(). The CSV p…	Provide reviewable evidence for tests/fixtures/financial_ledger.csv, or remove its exclusion, so the row count and required financial conventions can be verified.

✅ Passed checks (3 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly identifies the main change: adding a synthetic financial ledger fixture with accounting negatives.
Description check	✅ Passed	The description covers the required sections and explains the changes, motivation, testing, performance, compatibility, and documentation status. It also states that linting and type checks were not r…
Out of Scope Changes check	✅ Passed	The reviewed changes stay within #496. Parser changes implement accounting negatives. Context and semantic changes reduce financial-column misclassification. Tests, expectations, golden data, fixture …

Full details: Linked Issues check

Explanation

The reviewable changes support #496. They add accounting-negative parsing, financial-name handling, fixture registration, expectations, golden data, and an integration test for fd.clean(). The CSV path tests/fixtures/financial_ledger.csv is intentionally excluded from review, so this assessment cannot verify its 20–50 rows or its required anomalies (EUR, $, thousands separators, and whitespace). The available evidence supports the code and test requirements, but it does not establish full fixture compliance.

Full details: Docstring Coverage

Explanation

Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 5 files. (3 skipped: 3 unsupported.)

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Actionable comments posted: 5

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Inline comments:
In `@src/freshdata/engine/context.py`:
- Line 143: Update the identifier classification condition in the context logic
so names matching `_ID_NAME` retain the identifier role even when they also
match `_MONEY_NAME`. Keep the monetary-name exclusion limited to value-based
identifier inference, preserving the existing explicit `config.id_columns`
behavior.

In `@src/freshdata/semantic/context.py`:
- Line 180: Update CurrencyStringExpert.applies() to allow free-text columns
when they are marked money_like, while retaining strict value-format validation
for free-text values before proposing conversion.

In `@src/freshdata/semantic/experts.py`:
- Around line 232-233: Update the sign handling near accounting_negative so an
already-negative parsed value inside accounting parentheses cannot become
positive. Reject the conflicting sign combination or preserve the negative
result, while keeping the existing conversion for unsigned values.
- Line 228: Update the parenthetical-value eligibility check near `has_symbol`,
`has_code`, and `accounting_negative` so an unmarked parenthetical is accepted
only when its body is a valid accounting number and independent monetary context
supports conversion. Preserve handling of values with explicit currency symbols
or codes, and prevent unit-bearing values such as `(10 kg)` from being parsed as
negative currency.
- Line 231: Update CurrencyStringExpert to consume parse_currency_parts() and
inspect its ambiguity flag instead of relying on parse_currency(), which
discards that information. Route ambiguous unmarked accounting amounts to review
rather than proposing or applying a guessed value.

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📥 Commits

Reviewing files that changed from the base of the PR and between e4a8819 and 02d2f48.

⛔ Files ignored due to path filters (1)

• tests/fixtures/financial_ledger.csv is excluded by !**/*.csv

📒 Files selected for processing (8)

• src/freshdata/engine/context.py
• src/freshdata/semantic/context.py
• src/freshdata/semantic/experts.py
• tests/expectations.py
• tests/fixtures/financial_ledger.expectations.json
• tests/fixtures/golden/financial_ledger.balanced.report.json
• tests/fixtures/golden_diff_summary.jsonl
• tests/test_currency_locale.py

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[JohnnyWilson16]

Thanks for contributing the financial ledger test fixture and accounting negative support!

The test fixture additions in tests/fixtures/financial_ledger.* and tests/test_currency_locale.py are great, but the core engine and parser changes introduce critical data corruption risks that need to be addressed before this can be merged:

1. Sign Reversal on Explicit Negatives (semantic/experts.py):
   value = -value flips values with an existing minus sign to positive:
   parse_currency_parts("(-$1,250.00)") returns +1250.0 instead of -1250.0.
   Fix: Ensure negative values remain negative: value = -abs(value).

2. Unit Stripping and False-Positive Currency (semantic/experts.py):
   Allowing any parenthetical string through accounting_negative causes re.sub to strip all letters:

   • "(10 kg)" is parsed as currency -10.0.
   • "(page 3)" is parsed as -3.0.
   • In datasets containing unit measurements in parentheses, this causes the column to be misclassified as money_like, stripping units and converting positive quantities to negative floats.
     Fix: Reject strings containing words outside _CURRENCY_CODES (codes - _CURRENCY_CODES), and require accounting punctuation (. or ,) for unmarked parenthetical numbers.

3. Identifier Veto Regression (engine/context.py):
   _ID_NAME.search(label) and not _MONEY_NAME.search(label) strips the id role from payment_id, charge_id, fee_id, etc., causing them to fall back to categorical and lose never-impute protection.
   Fix: Remove and not _MONEY_NAME.search(label) from the _ID_NAME check; keep it only on the cardinality-based heuristic (nunique == non_null).

4. Ambiguity Flag Discarded (semantic/experts.py):
   CurrencyStringExpert.propose() calls parse_currency() instead of parse_currency_parts(), throwing away the ambiguous flag. An unmarked (1,250) or (1.250) gets automatically converted with 0.96 confidence instead of routed to human review.
   Fix: Inspect the ambiguity flag and set risk_override="high" for ambiguous numbers.

[muhammad-muneeb3]

Thanks for the detailed review and feedback, @JohnnyWilson16!

I have addressed all the raised issues and pushed the updates:

1. Sign Reversal on Explicit Negatives: Enforced value = -abs(value) if value != 0 else 0.0 for accounting negatives so that explicitly signed values like (-$1,250.00) remain negative.
2. Unit Stripping and False-Positive Currency:
   • Alphabetic tokens outside _CURRENCY_CODES (e.g., (10 kg), (page 3)) now immediately return (None, False).
   • Unmarked parentheticals now require valid decimal/thousands punctuation (. or ,) and matching accounting numeric structure.
3. Identifier Role Retention: Restored unconditional _ID_NAME pattern matching in infer_role so columns like payment_id and fee_id retain their id role and protection.
4. Preserved Locale Ambiguity: CurrencyStringExpert.propose() now consumes parse_currency_parts() directly and flags ambiguous unmarked numbers with risk_override="high" and lower confidence (0.60) for review.
5. Tests & Coverage: Added unit tests covering all these edge cases in tests/test_currency_locale.py and included docstrings to satisfy the coverage threshold.

[JohnnyWilson16]

LGTM! Thanks @muhammad-muneeb3 for the rapid and thorough follow-up on the review feedback.

• Explicit negatives like (-$1,250.00) correctly remain negative.
• Unit-bearing parentheticals like (10 kg) and plain numbers like (10) are properly rejected from currency conversion.
• payment_id and other *_id columns retain their id role and protection.
• Ambiguous unmarked numbers like (1,250) are properly routed to human review.
• All 7,400+ unit tests and new edge-case tests pass cleanly.

Ready to merge!