974181674d
## Context
v1 shipped a Claude Haiku-based extractor that validated only 10/71
backfilled rows. Haiku fumbles the arithmetic on pension salary-sacrifice,
conflates RSU vest with regular earnings, and occasionally misreads YTD
vs this-period columns — so 86% of rows land with validated=false and the
downstream dashboards under-report take-home.
Meta UK uses a stable two-variant template (pre/post 2022-01-31 boundary),
so a regex parser is both faster (ms vs. 30-90s + $0.01-0.05/call) and
more accurate. v2 introduces that parser as the primary path, keeps
Claude as the fallback for non-Meta payslips, and surfaces new fields
the dashboard needs to attribute PAYE between cash salary and RSU vests
correctly.
## This change
### Parser (new)
`payslip_ingest/parsers/meta_uk.py` detects the layout variant by header
presence:
- **Variant A** (pre-2022): vertical Description/This Period/This Year.
`AE Pension EE` is a positive deduction against a pre-sacrifice gross —
maps to `pension_employee` for the existing validation formula to hold.
- **Variant B** (post-2022): side-by-side Payments | Deductions | Year to
Date. `AE Pension EE` is NEGATIVE in Payments (salary sacrifice) — maps
to `pension_sacrifice` and is already netted into Total Payment.
`rsu_vest = RSU Tax Offset + RSU Excs Refund` (Meta's template inflates
Taxable Pay without using a matching offset deduction).
Column boundaries come from the header row's anchor positions; each data
row slices into 3 cells and the last numeric token per cell is the amount.
Anchor misses raise ParserError so the caller falls back to Claude rather
than silently returning bad data.
### New fields
Schema + DB + Claude prompt gain:
- `salary`, `bonus`, `pension_sacrifice` — earnings decomposition for the
dashboard's bonus-sacrifice visibility and earnings-breakdown chart
- `taxable_pay`, `ytd_tax_paid`, `ytd_taxable_pay`, `ytd_gross` — powers
the YTD-effective-rate method of attributing cash tax vs RSU tax, which
is the only method that's accurate month-to-month
All new columns default to 0 / null so v1 rows continue to round-trip.
### Orchestration
processor.py tries `parse_meta_uk(pdftotext(pdf))` first. On success the
result goes straight to the DB — zero Claude tokens spent, extraction in
milliseconds. On ParserError it falls through to ClaudeExtractor as before.
ProcessResult gains an `extractor` field ("meta_uk_regex" | "claude") so
backfill logs show the hit rate.
## Tests
- `test_meta_uk_parser.py` — 11 tests covering variant A, variant B
(standard + bonus month + bonus-sacrificed month), malformed inputs,
and end-to-end totals validation for all 4 golden fixtures.
- `test_processor.py` — 2 new tests proving the regex-first short-circuit
and the Claude fallback on non-Meta inputs.
Fixtures under `tests/fixtures/` are hand-crafted `pdftotext -layout`
emulations — real Meta numbers from the plan's sample payslips for
variant B, synthesized realistic variant A and bonus-sacrificed samples.
0001_initial.py reformat is yapf cleanup touched during the session's
format pass; not a behavior change.
## Test Plan
### Automated
```
$ poetry run pytest
============================= test session starts ==============================
collected 53 items
tests/test_extractor.py ..... [ 9%]
tests/test_meta_uk_parser.py ........... [ 30%]
tests/test_paperless.py ...... [ 41%]
tests/test_processor.py .............. [ 67%]
tests/test_schema.py .... [ 75%]
tests/test_tax_year.py ........ [ 90%]
tests/test_webhook.py ..... [100%]
============================== 53 passed in 1.66s ==============================
$ poetry run ruff check .
All checks passed!
$ poetry run mypy .
Success: no issues found in 24 source files
$ poetry run yapf --style pyproject.toml --diff --recursive payslip_ingest tests
(no output — all files are yapf-clean)
```
### Manual Verification
Smoke-test the parser against a real Meta payslip PDF on the deploy host:
```
# After 0003 migration applied to prod DB
$ poetry run python -c "
from payslip_ingest.parsers import parse_meta_uk
import subprocess
text = subprocess.check_output(['pdftotext', '-layout', '/path/to/real.pdf', '-']).decode()
p = parse_meta_uk(text)
print(p.model_dump_json(indent=2))
"
```
Expected: JSON with salary/bonus/rsu_vest/pension_sacrifice populated and
`validate_totals(p)` returning True.
## Reproduce locally
1. `cd payslip-ingest && poetry install`
2. `poetry run pytest tests/test_meta_uk_parser.py -v`
3. Expected: 11 tests pass, each fixture validates totals within 2p.
Closes: code-un1
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
"""initial schema
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Revision ID: 0001
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Revises:
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Create Date: 2026-04-18 00:00:00.000000
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"""
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from collections.abc import Sequence
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import sqlalchemy as sa
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from sqlalchemy.dialects import postgresql
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from alembic import op
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revision: str = "0001"
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down_revision: str | None = None
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branch_labels: str | Sequence[str] | None = None
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depends_on: str | Sequence[str] | None = None
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SCHEMA = "payslip_ingest"
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def upgrade() -> None:
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op.execute(f"CREATE SCHEMA IF NOT EXISTS {SCHEMA}")
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op.create_table(
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"payslip",
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sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True),
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sa.Column("paperless_doc_id", sa.Integer(), nullable=False, unique=True),
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sa.Column("pay_date", sa.Date(), nullable=False),
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sa.Column("pay_period_start", sa.Date(), nullable=True),
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sa.Column("pay_period_end", sa.Date(), nullable=True),
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sa.Column("employer", sa.Text(), nullable=True),
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sa.Column("currency", sa.CHAR(3), nullable=False, server_default="GBP"),
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sa.Column("gross_pay", sa.Numeric(12, 2), nullable=False),
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sa.Column("income_tax", sa.Numeric(12, 2), nullable=False, server_default=sa.text("0")),
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sa.Column("national_insurance",
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sa.Numeric(12, 2),
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nullable=False,
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server_default=sa.text("0")),
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sa.Column("pension_employee",
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sa.Numeric(12, 2),
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nullable=False,
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server_default=sa.text("0")),
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sa.Column("pension_employer",
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sa.Numeric(12, 2),
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nullable=False,
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server_default=sa.text("0")),
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sa.Column("student_loan", sa.Numeric(12, 2), nullable=False, server_default=sa.text("0")),
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sa.Column("other_deductions", postgresql.JSONB(), nullable=True),
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sa.Column("net_pay", sa.Numeric(12, 2), nullable=False),
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sa.Column("tax_year", sa.Text(), nullable=False),
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sa.Column("raw_extraction", postgresql.JSONB(), nullable=False),
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sa.Column("validated", sa.Boolean(), nullable=False, server_default=sa.text("true")),
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sa.Column(
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"created_at",
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sa.TIMESTAMP(timezone=True),
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nullable=False,
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server_default=sa.text("now()"),
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),
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schema=SCHEMA,
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)
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op.create_index("idx_payslip_pay_date", "payslip", ["pay_date"], schema=SCHEMA)
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op.create_index("idx_payslip_tax_year", "payslip", ["tax_year"], schema=SCHEMA)
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def downgrade() -> None:
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op.drop_index("idx_payslip_tax_year", table_name="payslip", schema=SCHEMA)
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op.drop_index("idx_payslip_pay_date", table_name="payslip", schema=SCHEMA)
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op.drop_table("payslip", schema=SCHEMA)
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op.execute(f"DROP SCHEMA IF EXISTS {SCHEMA}")
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