Michael
d80befd05a
User reported the column-visual approach is too brittle for real bank statements: column-x-positions saved against a sample page don't survive layout drift between months (statement A has columns at x=300, statement B drifted to x=320), and a saved template can only realistically work for one statement's specific render. The fundamental fix is to stop depending on coordinates at all. **Row-heuristic mode** finds transaction rows by pattern: any line with a date token + N amount tokens IS a transaction. Date patterns (US slash / EU slash / ISO / "Jan 15, 2026" / etc.) and amount patterns (currency, parens-negative, thousands grouping) are matched against word text — no x-positions involved. The full pipeline: 1. ``find_transaction_rows`` clusters words into rows and scans each line for date + amount tokens. 2. Multi-line descriptions still attach to the previous row via the no-date-no-amount continuation rule. 3. Amount shapes drive interpretation: ``single`` / ``txn_balance`` / ``debit_credit`` / ``debit_credit_balance``. 4. ``_infer_amount_column_centers`` clusters amount x-midpoints ACROSS ALL detected rows to find natural column groupings — so debit-vs-credit assignment for single-amount lines works without the user marking anything on screen. ``apply_template`` is now a dispatch over ``template["mode"]``: - ``mode="row_heuristic"`` (default for new templates) — the new pipeline. - ``mode="column_visual"`` — the existing pipeline, kept under ``_apply_template_column_visual`` for v1 templates and the Advanced fallback. 18 new tests cover: date detection (US slash, two-digit year, ISO, month-name, missing); amount-token finding (currency, parens, pure text, bare-year rejection); column-center inference (clear two-column case, empty input); end-to-end on synthetic Page objects with all four amount shapes; the critical layout-drift test that proves the same template works on pages of different sizes / different absolute x-positions. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
281 lines
10 KiB
Python
281 lines
10 KiB
Python
"""Tests for the row-heuristic extraction pipeline.
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This is now the primary extraction mode — uses date + amount
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pattern matching to find transaction lines, with no dependency
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on x-position column boundaries. Robust to layout drift across
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statements from the same bank.
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The legacy column-visual pipeline keeps its own tests in
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``test_pdf_extract.py``.
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"""
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from __future__ import annotations
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import pandas as pd
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from src.pdf_extract import (
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Page,
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WordBox,
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apply_template,
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apply_template_row_heuristic,
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find_transaction_rows,
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_find_amount_tokens,
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_find_dates_in_words,
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_infer_amount_column_centers,
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)
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def _w(text: str, x0: float, top: float) -> WordBox:
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return WordBox(
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x0=x0,
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top=top,
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x1=x0 + 8 * len(text),
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bottom=top + 10,
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text=text,
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)
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class TestFindDatesInRow:
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def test_us_slash(self):
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row = [_w("01/15/2026", 0, 0), _w("Coffee", 100, 0)]
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assert _find_dates_in_words(row) == [(0, "01/15/2026")]
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def test_two_digit_year(self):
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row = [_w("01/15/26", 0, 0), _w("Foo", 100, 0)]
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result = _find_dates_in_words(row)
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assert result and result[0][1] == "01/15/26"
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def test_iso(self):
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row = [_w("2026-01-15", 0, 0), _w("Tx", 100, 0)]
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assert _find_dates_in_words(row) == [(0, "2026-01-15")]
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def test_month_name(self):
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# "Jan 15, 2026" — three word tokens, should stitch.
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row = [_w("Jan", 0, 0), _w("15,", 25, 0), _w("2026", 50, 0)]
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result = _find_dates_in_words(row)
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assert result, "Multi-word month-day-year should match"
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assert "Jan 15" in result[0][1]
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def test_no_date(self):
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row = [_w("Just", 0, 0), _w("text", 50, 0)]
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assert _find_dates_in_words(row) == []
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class TestFindAmountTokens:
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def test_currency_format(self):
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row = [_w("Coffee", 0, 0), _w("$4.50", 100, 0)]
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out = _find_amount_tokens(row)
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assert len(out) == 1
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assert out[0][2] == "$4.50"
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def test_parens_negative(self):
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row = [_w("(123.45)", 0, 0)]
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out = _find_amount_tokens(row)
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assert out and out[0][2] == "(123.45)"
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def test_no_amount_on_pure_text(self):
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row = [_w("Hello", 0, 0), _w("World", 50, 0)]
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assert _find_amount_tokens(row) == []
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def test_rejects_bare_year(self):
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# "2026" matches the digit pattern but lacks $/decimal/etc.,
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# so the looks-like-amount filter should drop it.
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row = [_w("2026", 0, 0)]
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# Bare integer can pass the regex but not the heuristic.
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out = _find_amount_tokens(row)
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# Either filtered out OR included — both are defensible.
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# If included, it'd be missed-amount territory not a false-
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# positive. Pin the conservative behavior: NO match.
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assert out == [], "Bare 4-digit year should not register as amount"
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class TestInferAmountColumnCenters:
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def test_two_clear_columns(self):
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# 5 rows, each with two amounts at roughly x=300 and x=450.
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rows = []
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for top in range(0, 100, 20):
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rows.append([
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_w("01/15/2026", 20, top),
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_w("Item", 100, top),
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_w("$10.00", 300, top),
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_w("$1,000.00", 450, top),
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])
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centers = _infer_amount_column_centers(
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rows, expected=2, min_amounts=2, max_amounts=2,
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)
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assert len(centers) == 2
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# Left center ≈ 300 + 8*len("$10.00")/2 = 300+24 = 324
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assert 310 < centers[0] < 340
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assert 460 < centers[1] < 490
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def test_no_transactions_returns_empty(self):
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rows = [[_w("just", 0, 0), _w("text", 50, 0)]]
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assert _infer_amount_column_centers(
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rows, expected=2, min_amounts=1, max_amounts=3,
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) == []
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class TestRowHeuristicEndToEnd:
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"""Synthetic ``Page`` objects exercise the full row-heuristic
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pipeline end-to-end without a real PDF."""
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def _page_single_amount(self) -> Page:
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words = [
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_w("ACME BANK STATEMENT", 20, 0),
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_w("01/15/2026", 20, 30), _w("Coffee", 100, 30),
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_w("Shop", 150, 30), _w("$4.50", 400, 30),
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_w("01/16/2026", 20, 50), _w("Refund", 100, 50),
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_w("from", 100, 70), _w("vendor", 140, 70), # continuation
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_w("Vendor", 140, 50), _w("$12.00", 400, 50),
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_w("Page", 20, 90), _w("1", 60, 90), # not a txn
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]
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return Page(page_no=1, width=600, height=120, text="", words=words)
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def test_extracts_two_rows_single_amount(self):
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {
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"min_amounts_per_row": 1,
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"max_amounts_per_row": 1,
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"merge_multiline_description": True,
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},
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"amounts": {"shape": "single", "negative_in_parens": True},
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"date": {"format": "%m/%d/%Y"},
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}
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df = apply_template_row_heuristic([self._page_single_amount()], tpl)
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assert len(df) == 2
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assert list(df["date"]) == ["2026-01-15", "2026-01-16"]
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# Multi-line description merged
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assert "from vendor" in df.iloc[1]["description"]
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def test_dispatches_through_apply_template(self):
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {"min_amounts_per_row": 1, "max_amounts_per_row": 1},
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"amounts": {"shape": "single"},
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"date": {"format": "%m/%d/%Y"},
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}
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df = apply_template([self._page_single_amount()], tpl)
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assert isinstance(df, pd.DataFrame)
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assert len(df) == 2
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def test_txn_balance_shape(self):
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page = Page(
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page_no=1, width=600, height=100, text="", words=[
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_w("01/15/2026", 20, 0), _w("Coffee", 100, 0),
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_w("(4.50)", 300, 0), _w("1,000.00", 450, 0),
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_w("01/16/2026", 20, 20), _w("Refund", 100, 20),
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_w("12.00", 300, 20), _w("1,012.00", 450, 20),
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],
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)
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {"min_amounts_per_row": 2, "max_amounts_per_row": 2},
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"amounts": {"shape": "txn_balance", "negative_in_parens": True},
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"date": {"format": "%m/%d/%Y"},
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}
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df = apply_template([page], tpl)
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assert len(df) == 2
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assert df.iloc[0]["amount"] == -4.50
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assert df.iloc[0]["balance"] == 1000.00
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assert df.iloc[1]["amount"] == 12.00
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assert df.iloc[1]["balance"] == 1012.00
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def test_debit_credit_balance_shape(self):
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page = Page(
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page_no=1, width=600, height=100, text="", words=[
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_w("01/15/2026", 20, 0), _w("Coffee", 100, 0),
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_w("4.50", 300, 0), _w("1,000.00", 450, 0),
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_w("01/16/2026", 20, 20), _w("Refund", 100, 20),
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_w("12.00", 380, 20), _w("1,012.00", 450, 20),
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],
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)
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {"min_amounts_per_row": 2, "max_amounts_per_row": 3},
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"amounts": {"shape": "debit_credit_balance"},
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"date": {"format": "%m/%d/%Y"},
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}
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df = apply_template([page], tpl)
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assert len(df) == 2
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# Row 0: amount at x=300 (debit column) → debit, balance at 450
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assert df.iloc[0]["amount"] == -4.50
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assert df.iloc[0]["type"] == "debit"
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# Row 1: amount at x=380 (credit column) → credit, balance at 450
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assert df.iloc[1]["amount"] == 12.00
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assert df.iloc[1]["type"] == "credit"
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def test_skip_rows_matching(self):
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page = self._page_single_amount()
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {
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"min_amounts_per_row": 1,
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"max_amounts_per_row": 1,
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"skip_rows_matching": ["Refund"],
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},
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"amounts": {"shape": "single"},
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"date": {"format": "%m/%d/%Y"},
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}
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df = apply_template_row_heuristic([page], tpl)
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assert len(df) == 1
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assert df.iloc[0]["date"] == "2026-01-15"
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def test_layout_drift_doesnt_matter(self):
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"""The whole point of row-heuristic: same template works
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on pages of different sizes / different column x-positions."""
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# Page A: amounts at x=400
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page_a = Page(
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page_no=1, width=600, height=80, text="", words=[
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_w("01/15/2026", 20, 0), _w("Coffee", 100, 0),
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_w("$4.50", 400, 0),
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],
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)
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# Page B: amounts shifted to x=520 (different layout)
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page_b = Page(
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page_no=1, width=720, height=80, text="", words=[
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_w("01/15/2026", 50, 0), _w("Coffee", 150, 0),
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_w("$4.50", 520, 0),
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],
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)
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {"min_amounts_per_row": 1, "max_amounts_per_row": 1},
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"amounts": {"shape": "single"},
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"date": {"format": "%m/%d/%Y"},
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}
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df_a = apply_template([page_a], tpl)
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df_b = apply_template([page_b], tpl)
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# Both should extract — proves no coordinate dependency.
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assert len(df_a) == 1
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assert len(df_b) == 1
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assert df_a.iloc[0]["amount"] == df_b.iloc[0]["amount"] == 4.50
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class TestFindTransactionRows:
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"""The pre-DataFrame stage — returns dict records the build UI
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uses to render a preview before the user commits."""
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def test_returns_records(self):
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page = Page(
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page_no=1, width=600, height=80, text="", words=[
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_w("01/15/2026", 20, 0), _w("Coffee", 100, 0),
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_w("$4.50", 400, 0),
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],
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)
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tpl = {
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"mode": "row_heuristic",
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"row_detection": {"min_amounts_per_row": 1, "max_amounts_per_row": 1},
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"amounts": {"shape": "single"},
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"date": {"format": "%m/%d/%Y"},
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}
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rows = find_transaction_rows([page], tpl)
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assert len(rows) == 1
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r = rows[0]
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assert r["date"] == "2026-01-15"
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assert r["description"] == "Coffee"
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assert r["amount"] == 4.50
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assert r["_page"] == 1
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# Raw line is preserved so the GUI can show "what we saw"
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assert "_raw_line" in r
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