ad7c22d7fbba3ea608648b6b94f4195272806c9e
6 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
| ad7c22d7fb |
fix(pdf): consistent 2-decimal amount precision in display and CSV
User reported amounts losing trailing zeros — 4.50 rendering as
4.5, 1000.00 as 1000 — on the same statement. Classic float
display issue: Python's native ``repr(4.5)`` drops the
``.0``, and pandas / Streamlit happily show that
inconsistency cell-by-cell.
Two layers of fix, internal type stays ``float`` for arithmetic:
**Display.** ``st.column_config.NumberColumn(format="%.2f")``
applied programmatically to every ``amount_*`` column on the
data_editor. Every numeric amount now shows with exactly two
decimal places regardless of trailing zeros.
**CSV export.** Pandas' default float-to-CSV writer also drops
trailing zeros (the same issue an accountant would see when
opening the file in Excel). Before serialising, each amount
column is mapped through the new ``format_amount`` helper —
returns ``f"{v:.2f}"`` for numerics, empty string for
None/NaN/inf, ``str(value)`` for booleans (guards the
``True → "1.00"`` foot-gun since ``bool`` is an ``int``
subclass), and passes through any string the scanner kept
because parsing failed (e.g. ``(4.50)`` when parens-negative is
off — user can correct in the editor before re-exporting).
``format_amount`` lives in ``src/pdf_extract.py`` so it's
testable in isolation (the page module can't easily be unit
tested because of its Streamlit import chain). 8 new tests
cover the trailing-zeros case, negatives, None/empty,
string-passthrough, bool guard, NaN/inf, and the ``places``
parameter.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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| 155dd30746 |
feat(pdf): extract statement header (account + period) + date format
Two related additions for the accountant workflow:
**1. Statement header extraction.** New
``extract_statement_metadata(pages)`` pulls the account number
and statement period out of the first page (falls back to
page 1+2 if either is missing on page 1 — Wells Fargo business
accounts put header info on page 2). Detected fields are
stamped onto EVERY transaction row so a multi-statement CSV is
self-attributing per row::
{
"date": "20250113",
"description": "Coffee Shop",
"amount_1": -4.50,
"account_number": "****5678",
"statement_period_start": "20250101",
"statement_period_end": "20250131",
...
}
Account-number regex is tolerant of masks (``****1234``),
hyphens (``1234-5678-9012``), and spaces. Period regex looks
for "Statement Period" / "From" / "Period Covered" labels plus
the first 1-2 full-year dates that follow. If only one date is
present near the label, it's used for both start and end (some
statements show only the closing date).
**2. Year inference for short dates.** When the row date is a
short ``01/13`` or ``Jan 13`` without a year, the scanner now
binds the year from the statement period's end date BEFORE
formatting. Doesn't handle the December-in-January-statement
cross-year case (rare; user can edit in the table).
**3. Configurable output date format.** New
``output_date_format`` parameter on ``scan_pdf_for_transactions``
defaults to ``%Y%m%d``. Applied to: the transaction date column
AND the statement period start/end fields. The page surfaces a
dropdown in Scan options with common presets (YYYYMMDD,
YYYY-MM-DD, MM/DD/YYYY, DD/MM/YYYY, ``Mon DD, YYYY``) plus a
Custom option that accepts a raw strftime string.
New helper: ``format_date(iso_str, fmt)`` converts ISO
``YYYY-MM-DD`` to any strftime; passes invalid input through
unchanged so the user can see what was actually there rather
than getting silent empties.
20 new tests cover: format_date, account-number extraction
(masked / hyphenated / spaced / no-label / short), period
extraction (standard / from-to / single-date / no-label),
metadata orchestrator (full header / no pages / page-2
fallback), year inference (US / dash / month-name / no-period /
unparseable), plus an end-to-end class that builds a header'd
PDF with short-date transactions and confirms metadata
attribution + year inference + format round-trip.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
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| 3cf935c999 |
fix(pdf): drop zero-amount rows; multi-date rows clean description
Two corrections from real-statement feedback:
**1. Drop rows where the transaction amount is exactly 0.**
Bank statements include date+amount-shaped noise like
"INTEREST EARNED 0.00", "PAGE TOTAL 0.00", "BALANCE FORWARD
0.00 1,234.56" — all match the date+amount heuristic but
aren't transactions. New filter in
``scan_pdf_for_transactions``: drop rows whose ``amount_1``
parses to exactly 0. Non-zero balances in ``amount_2`` don't
rescue a zero amount_1 — leftmost amount is the canonical
transaction amount. Unparsed-but-non-empty amount strings are
kept (user verifies in the editor).
**2. Multi-date rows: first date wins for the column, every
date excluded from the description.** Chase / BofA / Wells
commonly show both a transaction date and a posting date per
row:
01/13 01/14 COFFEE SHOP $4.50
Before this fix, ``_find_dates_in_words`` returned the first
date only and the second date leaked into description as
"01/14 COFFEE SHOP". Now it returns ALL dates with their word
ranges; the scanner uses ``dates[0]`` as the canonical date
and passes every range to the description builder for
exclusion.
The detector's two-pass strategy now also guards against
mixing full-year and short-date matches on the same row.
Previously, a header line like ``Page 1/2 of 3 ... Statement
Date 01/13/2026`` would return both ``1/2`` and ``01/13/2026``,
and ``1/2`` (being leftmost) would have won the date column.
Now: if any full-year date is found on the row, short patterns
are NOT also collected — full year anchors interpretation. A
row with no full-year date (Chase short-date case) still falls
back to short patterns and collects all of them.
New tests:
- ``test_multiple_dates_returned_in_position_order`` —
``01/13`` + ``01/14`` both returned, in order
- ``TestMultiDateRow.test_first_date_wins_second_excluded_from_description``
— end-to-end through ``scan_pdf_for_transactions``
- ``TestZeroAmountRowsAreDropped.test_zero_amount_row_dropped``
— "INTEREST EARNED 0.00" row dropped while real txn kept
- ``test_negative_amount_kept`` — pin that -40.00 is not
treated as zero by the filter
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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| 263af3c7c2 |
fix(pdf): short dates without year + diagnostic for "0 rows" runs
User uploaded a real Chase statement and got "0 rows detected."
Two bugs the rewrite shipped with, plus a diagnostic:
**1. Short dates without year weren't recognized.** Most bank
statements (Chase, Wells, BofA, …) display transaction dates as
``01/13`` or ``Jan 13`` because the year is implied by the
statement period. The original regex required ``\d{2,4}`` after
the second slash, so ``01/13`` failed to match and rows with no
detected date got dropped.
Split ``_DATE_RES`` into ``_FULL`` (with year) and ``_SHORT``
(no year), with a two-pass detector: pass 1 tries full-year
patterns across the whole row; pass 2 only tries short patterns
if pass 1 found nothing. This prevents a stray ``Page 1/2`` from
shadowing the real dated transaction on the same line.
Short patterns:
- ``\d{1,2}/\d{1,2}`` — Chase, etc.
- ``\d{1,2}-\d{1,2}``
- ``[A-Z][a-z]{2}\s+\d{1,2}`` — "Jan 13"
When parsing, short dates pass through ``parse_date`` and
return None (no year to bind to), so the scanner falls back to
the raw text — the user sees ``01/13`` in the date column and
can correct in the editor.
**2. Multi-word dates leaked the day token into the description.**
A pre-existing bug: ``_find_dates_in_words`` returned only the
START word index, and ``_description_from_row`` only excluded
that single word. For "Jan 13 Coffee $4.50", the description
became "13 Coffee" instead of "Coffee". Fixed by returning
``(start, end, text)`` with ``end`` exclusive (computed from
``len(m.group(1).split())`` so window-overrun doesn't
over-consume), and the description builder now skips the full
range.
**3. New diagnostic: ``diagnose_pdf_lines(pdf_bytes)``.** Returns
every clustered text line the scanner saw with ``has_date`` /
``has_amount`` flags. When the page's scan returns 0 rows, an
auto-expanded "what the scanner saw" expander now renders a
table of all extracted lines so the user can:
- Spot scanned-PDF cases (empty result → enable OCR)
- See which lines have a date but no amount (or vice versa)
- Eyeball the date / amount format the scanner missed
Without leaving the app or asking the developer for help.
Eight new tests cover: short US date (``01/13``), short month-
name date with two-word consumption (``Jan 13``), the
``Page 1/2 ... 01/13/2026`` shadowing case, and the multi-word-
date description fix.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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| bece2b4030 |
refactor(pdf): rip out templates; heuristic scan + selectable table
User feedback: the template / visual-picker / mode-dispatch
implementation was too complex for the actual workflow.
Statements drift between months, the canvas state didn't survive
multi-page navigation, and accountants don't want to maintain
per-bank configuration just to convert PDFs to CSV.
Start-over design — one public function, one page, no
persistence:
``scan_pdf_for_transactions(pdf_bytes) → (rows, warnings)``
A row is "any text line with a date pattern AND at least one
amount pattern." Each detected row is a dict shaped::
{
"date": "2026-01-15",
"description": "Coffee Shop",
"amount_1": -4.50,
"amount_2": 1000.00, # if a second amount was found
"page": 1,
"raw": "01/15/2026 Coffee Shop (4.50) 1,000.00",
"source_file": "chase-jan-2026.pdf",
}
Multi-line descriptions still merge (no-date no-amount lines
attach to the previous transaction). Multi-PDF batches share a
single combined table with a ``source_file`` column.
**Page UX:**
- Upload PDF(s) → optional Options expander (parens-negative,
use-OCR) → click Scan → see all detected rows in an
``st.data_editor``.
- The editor has an ``Include`` checkbox column (default on),
plus user-editable date / description / amount cells and a
read-only ``raw`` column showing the original PDF text for
verification.
- A ``Columns to include in CSV`` multiselect hides
``page`` / ``raw`` from the download by default; user can
re-add either.
- Download CSV gets only the checked rows.
No template save/load. No visual picker. No mode dispatch. No
column boundaries. No schema migration. No per-bank
configuration files.
**Deletions:**
- ``src/pdf_templates.py`` — template storage layer
- ``src/gui/_drawable_canvas_compat.py`` — Streamlit compat shim
for the canvas (no canvas now)
- ``tests/test_pdf_templates.py``, ``test_pdf_row_heuristic.py``,
``test_drawable_canvas_compat.py`` — covered the removed APIs
- ``build/hooks/hook-streamlit_drawable_canvas.py`` — hook for
the removed dep
- ``streamlit-drawable-canvas==0.9.3`` from ``requirements.txt``
- The drawable-canvas references in ``build/datatools.spec``
**``src/pdf_extract.py``** shrinks from ~30 helper functions to
~10. Keeps: value parsers, row clusterer, date/amount token
finders, OCR pipeline, dependency guards. The one new public
function ``scan_pdf_for_transactions`` glues them together.
**Tests** (59 passing): the unit layer keeps full coverage of
the building blocks; the smoke layer pins the end-to-end PDF
roundtrip, OCR discovery, dependency-import behavior, and the
multi-line-description merge. The fpdf2-generated fixture PDF
still drives the real-PDF test.
Rollback: ``git revert HEAD`` brings back the template system if
needed — but the simpler model should make that unlikely.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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| b8aff862ed |
feat(pdf): add pure PDF→DataFrame extraction module
Phase 1/6 of the PDF Extractor tool. Pure module — no Streamlit,
no user-config I/O — that turns a PDF blob plus a template dict
into a ``pandas.DataFrame`` of transaction rows. Primary use case
is accountant-style extraction of bank-statement transactions,
where each bank's format is encoded as a reusable template.
Pipeline:
1. ``extract_pages(pdf_bytes)`` reads with pdfplumber and surfaces
words with bounding boxes.
2. ``cluster_rows(words)`` groups words into rows by ``top``
tolerance — no reliance on PDF table-line detection (most bank
statements have no visible cell borders).
3. ``assign_columns(row_words, boundaries)`` buckets each word by
its horizontal midpoint into N+1 columns defined by N interior
x-boundaries.
4. ``_within_table_window`` slices to the band between the header
line and the end-marker (e.g. "Closing balance").
5. ``apply_template`` orchestrates the above, handling:
- parens-style negative amounts, currency stripping, custom
decimal/thousands separators
- separate debit + credit columns combined into a single signed
``amount`` (credit positive, debit negative — accounting
register convention; matches QuickBooks/Xero imports)
- multi-line description wrapping (rows with empty date column
attach to the previous row's description)
- row-level regex skip filters (e.g., "Total", "Subtotal")
- page-range filters ("all", "2-", "1,3-5")
Optional OCR fallback for scanned statements:
- ``page_has_extractable_text`` heuristic flags pages with <5
words as likely-scanned.
- ``ocr_available()`` checks both the ``pytesseract`` Python
binding and the Tesseract binary; surfaces a clear reason
string when either is missing.
- ``extract_pages_auto`` does text-first, OCR-the-blanks, and
returns warnings the UI can surface.
29 unit tests cover the parsing pipeline against synthetic
WordBox/Page data — no fixture PDFs required, runs in 0.1s. Real
PDF extraction is exercised by hand on the user's statements.
Dependencies added:
- ``pdfplumber>=0.10,<1`` — text + position extraction
- ``pypdfium2>=4,<6`` — page rasterization for OCR + visual picker
- ``streamlit-drawable-canvas>=0.9,<1`` — visual region picker
(used in commit 5)
- ``pytesseract>=0.3,<1`` — OCR (used in commit 6; system
Tesseract binary required separately)
- ``cryptography>=41,<49`` — bumped upper bound; pdfminer.six
transitively requires a recent release. Internal ed25519
license-signing usage is API-stable across the bump.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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