Files
signal-platform/app/services/sec_facts_parser.py
T
dennisthiessenandClaude Opus 4.8 4754dbc17b fix(sec): A3 slice-2a review — shares fallback, robust context, hardening
1. Multi-class shares: prefer the single dei:EntityCommonStockSharesOutstanding
   cover-page fact; else fall back to us-gaap:CommonStockSharesOutstanding at
   period end (Alphabet has no dei fact). Never sum class facts (companyfacts is
   non-dimensional) and never use weighted-average/diluted; conflicting values ->
   null, counted as an "ambiguous shares outstanding" note in validation. Plan's
   "sum class-specific" wording corrected. Verified live: Alphabet shares now
   populate (12.1B), Apple still uses its dei cover date.
2. Fiscal context is the majority (fy, fp) among facts ending at reportDate, with
   ties rejected — no longer the arbitrary first fact.
3. Hardening: catalog selectors require taxonomy == "us-gaap"; indexing drops
   malformed facts (missing accession/end, non-finite value) so a custom concept
   or bad date can't be selected.

Tests: +8 (dei precedence, us-gaap fallback, conflict->null, no weighted-average,
tie-context skip, foreign-taxonomy/malformed ignored, ambiguous-shares note).
14 passed, 1 skipped.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-22 16:40:05 +02:00

345 lines
13 KiB
Python

"""Pure parser: SEC companyfacts -> fundamental_snapshots rows.
Turns one issuer's `companyfacts` JSON (+ its submissions filing metadata) into
per-accession snapshot rows for the filing's **primary period**, following the
A3 design (docs/dolt-sec-a3-design.md). No I/O, no DB — unit-testable against a
fixture and verifiable against a real companyfacts pull.
The load-bearing rules (design Decision 2 + review):
- Period identity comes from `end == submissions.reportDate`, never `fy/fp`
(fy/fp is the *filing's* context; comparatives inside a filing repeat it).
- Duration facts are stored as **cumulative YTD**: pick the fact whose span
matches the fiscal-period-to-date length (Q1≈3mo … FY≈12mo) within tolerance.
If no YTD-length fact exists, store null — never a discrete masquerading as YTD.
- Balance-sheet instants are taken at `end == reportDate`; `shares_outstanding`
is the cover-page `dei` fact whose own `end` (cover date) is stored separately.
- Cash and debt composites are aggregate-first and mutually exclusive (each
source tag counted at most once).
"""
from __future__ import annotations
import logging
import math
from dataclasses import dataclass
from datetime import date, datetime
from typing import Any, NamedTuple
logger = logging.getLogger(__name__)
# Expected YTD span (days) per fiscal period; a duration fact must land within
# tolerance of this to count as the period's cumulative value.
_EXPECTED_YTD_DAYS = {"Q1": 91, "Q2": 182, "Q3": 273, "FY": 365}
_YTD_TOLERANCE_DAYS = 20 # covers 52/53-week fiscal calendars
# us-gaap duration concepts (money), priority order; first present wins.
_DURATION_USD = {
"revenue": [
"RevenueFromContractWithCustomerExcludingAssessedTax",
"Revenues",
"SalesRevenueNet",
],
"net_income": ["NetIncomeLoss"],
"operating_income": ["OperatingIncomeLoss"],
"cfo": [
"NetCashProvidedByUsedInOperatingActivities",
"NetCashProvidedByUsedInOperatingActivitiesContinuingOperations",
],
"capex": [
"PaymentsToAcquirePropertyPlantAndEquipment",
"PaymentsToAcquireProductiveAssets",
],
"depreciation_amortization": [
"DepreciationDepletionAndAmortization",
"DepreciationAmortizationAndAccretionNet",
"DepreciationAndAmortization",
],
}
_EPS_CONCEPTS = ["EarningsPerShareDiluted"] # unit USD/shares
# us-gaap instant (balance-sheet) concepts, at end == reportDate.
_CASH = ["CashAndCashEquivalentsAtCarryingValue"]
_ST_INVESTMENTS = ["ShortTermInvestments", "MarketableSecuritiesCurrent"] # pick one
_LONG_TERM_DEBT_AGG = ["LongTermDebt"]
_LONG_TERM_DEBT_PARTS = ["LongTermDebtNoncurrent", "LongTermDebtCurrent"]
_SHORT_TERM_DEBT = ["ShortTermBorrowings", "CommercialPaper"] # pick one
class Fact(NamedTuple):
taxonomy: str
concept: str
unit: str
start: date | None # None => instant
end: date
val: float
fy: int | None
fp: str | None
@dataclass
class SnapshotRow:
cik: str
accession: str
form: str
filed_date: date
accepted_at: datetime
period_end: date
fiscal_year: int
fiscal_period: str
period_start: date | None = None
revenue: float | None = None
net_income: float | None = None
operating_income: float | None = None
diluted_eps: float | None = None
cfo: float | None = None
capex: float | None = None
depreciation_amortization: float | None = None
cash_and_st_investments: float | None = None
total_debt: float | None = None
shares_outstanding: float | None = None
shares_outstanding_date: date | None = None
@dataclass
class FilingMeta:
report_date: date
filing_date: date
accepted_at: datetime
form: str
def parse_snapshots(
companyfacts: dict[str, Any],
filings: dict[str, FilingMeta],
accessions: set[str],
) -> tuple[list[SnapshotRow], list[dict[str, str]]]:
"""Build snapshot rows for ``accessions`` (those with facts + filing meta).
Returns (rows, skips) where each skip is {accession, reason} for filings
with no usable period identity — the caller counts these in validation_json.
"""
cik = f"{int(companyfacts['cik']):010d}"
by_accn = _index_by_accession(companyfacts)
rows: list[SnapshotRow] = []
skips: list[dict[str, str]] = []
for accn in accessions:
meta = filings.get(accn)
facts = by_accn.get(accn)
if meta is None or not facts:
skips.append({"accession": accn, "reason": "no facts or filing metadata"})
continue
row, note = _parse_one(cik, accn, facts, meta)
if row is None:
skips.append({"accession": accn, "reason": note or "unparseable"})
continue
rows.append(row)
if note: # row produced, but a field-level issue to count in validation
skips.append({"accession": accn, "reason": note})
return rows, skips
def _index_by_accession(companyfacts: dict[str, Any]) -> dict[str, list[Fact]]:
"""One pass over companyfacts -> {accession: [Fact, ...]}."""
out: dict[str, list[Fact]] = {}
for taxonomy, concepts in companyfacts.get("facts", {}).items():
for concept, body in concepts.items():
for unit, facts in body.get("units", {}).items():
for f in facts:
accn = f.get("accn")
end = _d(f.get("end"))
val = f.get("val")
# Skip malformed facts so they can't be selected accidentally:
# every usable fact needs an accession, an end date, and a
# finite numeric value.
if not accn or end is None or not _finite(val):
continue
out.setdefault(accn, []).append(
Fact(
taxonomy=taxonomy,
concept=concept,
unit=unit,
start=_d(f.get("start")),
end=end,
val=val,
fy=f.get("fy"),
fp=f.get("fp"),
)
)
return out
def _parse_one(
cik: str, accn: str, facts: list[Fact], meta: FilingMeta
) -> tuple[SnapshotRow | None, str | None]:
"""Returns (row, note). row is None when there's no usable period identity;
note is a validation reason (row-skip reason when row is None, else a
field-level issue such as ambiguous shares)."""
fy, fp = _fiscal_context(facts, meta.report_date)
if fy is None or fp not in _EXPECTED_YTD_DAYS:
return None, "no usable period identity"
row = SnapshotRow(
cik=cik,
accession=accn,
form=meta.form,
filed_date=meta.filing_date,
accepted_at=meta.accepted_at,
period_end=meta.report_date,
fiscal_year=fy,
fiscal_period=fp,
)
# duration YTD facts (money) + EPS
for field_name, concepts in _DURATION_USD.items():
val, start = _select_ytd(facts, concepts, meta.report_date, fp, "USD")
setattr(row, field_name, val)
if field_name == "revenue" and start is not None:
row.period_start = start
eps, eps_start = _select_ytd(facts, _EPS_CONCEPTS, meta.report_date, fp, "USD/shares")
row.diluted_eps = eps
if row.period_start is None and eps_start is not None:
row.period_start = eps_start
# balance-sheet instants at reportDate
row.cash_and_st_investments = _compose_cash(facts, meta.report_date)
row.total_debt = _compose_debt(facts, meta.report_date)
shares, shares_date, ambiguous = _select_shares(facts, meta.report_date)
row.shares_outstanding = shares
row.shares_outstanding_date = shares_date
return row, ("ambiguous shares outstanding" if ambiguous else None)
def _fiscal_context(facts: list[Fact], report_date: date) -> tuple[int | None, str | None]:
"""The filing's (fy, fp) taken as the majority context among the facts that
end at reportDate (the current-period facts, which share the filing's
context). Reject a tie so a conflicting context is never chosen arbitrarily."""
counts: dict[tuple[int, str], int] = {}
for f in facts:
if f.end == report_date and f.fy is not None and f.fp:
counts[(f.fy, f.fp)] = counts.get((f.fy, f.fp), 0) + 1
if not counts:
return None, None
ranked = sorted(counts.items(), key=lambda kv: kv[1], reverse=True)
if len(ranked) > 1 and ranked[0][1] == ranked[1][1]:
return None, None # tie → conflicting contexts, reject
return ranked[0][0]
def _select_ytd(
facts: list[Fact], concepts: list[str], report_date: date, fp: str, unit: str
) -> tuple[float | None, date | None]:
"""First present concept whose duration fact ends at reportDate and whose span
matches the fiscal-period-to-date length. Returns (val, period_start)."""
expected = _EXPECTED_YTD_DAYS[fp]
for concept in concepts:
best: Fact | None = None
best_diff: int | None = None
for f in facts:
if (
f.taxonomy != "us-gaap"
or f.concept != concept
or f.unit != unit
or f.start is None
or f.end != report_date
):
continue
diff = abs((f.end - f.start).days - expected)
if diff <= _YTD_TOLERANCE_DAYS and (best_diff is None or diff < best_diff):
best, best_diff = f, diff
if best is not None:
return float(best.val), best.start
return None, None
def _select_instant(facts: list[Fact], concepts: list[str], report_date: date) -> float | None:
"""First present instant (balance-sheet) fact at end == reportDate, unit USD."""
for concept in concepts:
for f in facts:
if (
f.taxonomy == "us-gaap"
and f.concept == concept
and f.unit == "USD"
and f.start is None
and f.end == report_date
):
return float(f.val)
return None
def _compose_cash(facts: list[Fact], report_date: date) -> float | None:
cash = _select_instant(facts, _CASH, report_date)
st = _select_instant(facts, _ST_INVESTMENTS, report_date) # first present of the two
if cash is None and st is None:
return None
return (cash or 0.0) + (st or 0.0)
def _compose_debt(facts: list[Fact], report_date: date) -> float | None:
long_term = _select_instant(facts, _LONG_TERM_DEBT_AGG, report_date)
if long_term is None:
nc = _select_instant(facts, ["LongTermDebtNoncurrent"], report_date)
cur = _select_instant(facts, ["LongTermDebtCurrent"], report_date)
long_term = None if nc is None and cur is None else (nc or 0.0) + (cur or 0.0)
short_term = _select_instant(facts, _SHORT_TERM_DEBT, report_date)
if long_term is None and short_term is None:
return None
return (long_term or 0.0) + (short_term or 0.0)
def _select_shares(
facts: list[Fact], report_date: date
) -> tuple[float | None, date | None, bool]:
"""Issuer-wide shares outstanding as a single consolidated value (never a
class sum — companyfacts is non-dimensional — and never weighted-average/
diluted). Returns (value, shares_date, ambiguous).
1. Prefer the `dei:EntityCommonStockSharesOutstanding` cover-page instant;
its own end is the shares date (cover date != period_end).
2. Else fall back to `us-gaap:CommonStockSharesOutstanding` at period end
(e.g. Alphabet has no dei fact); shares date = reportDate.
Conflicting values within the chosen source → (None, None, True) to be
counted in validation.
"""
dei = [
f
for f in facts
if f.taxonomy == "dei"
and f.concept == "EntityCommonStockSharesOutstanding"
and f.unit == "shares"
and f.start is None
]
if dei:
if len({f.val for f in dei}) > 1:
return None, None, True
best = max(dei, key=lambda f: f.end)
return float(best.val), best.end, False
gaap = [
f
for f in facts
if f.taxonomy == "us-gaap"
and f.concept == "CommonStockSharesOutstanding"
and f.unit == "shares"
and f.start is None
and f.end == report_date
]
if gaap:
if len({f.val for f in gaap}) > 1:
return None, None, True
return float(gaap[0].val), report_date, False
return None, None, False # simply absent — not a conflict
def _d(value: Any) -> date | None:
if not value:
return None
try:
return date.fromisoformat(str(value)[:10])
except ValueError:
return None
def _finite(value: Any) -> bool:
"""True for a finite numeric value (rejects None, bool, strings, NaN/inf)."""
return isinstance(value, (int, float)) and not isinstance(value, bool) and math.isfinite(value)