thermograph/data/store.py
Emi Griffith f504f7bda9 Containerize the app and move the databases to PostgreSQL 18 (#220)
Run Thermograph as a docker-compose stack (app + Postgres 18) and standardize the
data layer on Postgres, while keeping the test suite on SQLite.

- accounts/db.py: DSN-driven engines. On Postgres, a per-worker read-write +
  read-only asyncpg pair (the RO engine pins read-only transactions, used by the
  pure-GET endpoints) plus a sync psycopg engine for the notifier thread; the
  SQLite path is preserved for tests/local (selected when THERMOGRAPH_DATABASE_URL
  is unset). models.py: boolean server_default -> sa.false().
- store.py / metrics.py: dialect-flexible — Postgres UNLOGGED tables via psycopg
  when configured, else the existing raw-sqlite3 paths byte-for-byte; sync
  interfaces and every fail-soft contract preserved.
- Alembic (backend/alembic/) manages the accounts schema; the container entrypoint
  runs `alembic upgrade head` before uvicorn (4 workers). migrate_accounts_to_pg.py
  copies the accounts data SQLite->PG through the ORM (UUID/bool/JSON coerced),
  skips access_token, and resets identity sequences.
- Dockerfile + docker-compose.yml: app image (uvicorn, 4 workers, loopback 8137)
  and a Postgres 18 db (2 CPUs) running pg_duckdb (deploy/db/) so the parquet
  climate cache is queryable in-DB via read_parquet('/parquet/cache/*.parquet').
- deploy.sh/thermograph.service rewired to manage the compose stack; env example,
  Makefile targets (up/down/db-up), and deploy/POSTGRES-MIGRATION.md cutover runbook.

Tests stay on SQLite (dialect fallback) — 323 pass. The full Postgres stack was
verified via docker compose: alembic migrations, register/login, the RO endpoint,
store/metrics round-trips, and the accounts data migration.
2026-07-20 06:28:23 +00:00

265 lines
11 KiB
Python

"""Persistent derived-data store — SQLite (WAL) at data/thermograph.sqlite.
The raw per-cell parquet records stay the source of truth; this database holds
only what's *derived* from them, so expensive work is done once per cell and
survives restarts/deploys instead of being recomputed per request, per view:
* ``derived`` — finished API response payloads (grade / calendar / day /
forecast), zlib-compressed JSON keyed by (kind, cell, request key) and
guarded by a validity ``token``. The token encodes everything the payload
depends on (payload schema version, history end date, recent-fetch stamp…);
a row whose stored token doesn't match the caller's current token is simply
a miss, so stale data can never be served — freshness is driven by the token
advancing, never by clock-based expiry.
* ``revgeo`` — reverse-geocode labels ("City, State" per ~cell), previously an
in-memory dict that re-hit Nominatim after every restart.
The store is a pure accelerator: every reader falls back to recomputing from
parquet when the database is missing, locked, or corrupt (all helpers swallow
their own errors), and deleting data/thermograph.sqlite is a safe full reset.
On Postgres (``THERMOGRAPH_DATABASE_URL=postgresql://…``) the same two tables live
as UNLOGGED tables — fast and non-durable, which suits a rebuildable cache — and
the per-thread connection uses psycopg instead of sqlite3. Every fail-soft path is
identical: a connection or query that fails just degrades to recompute-from-parquet.
"""
import json
import os
import sqlite3
import threading
import time
import zlib
import paths
DB_PATH = os.path.join(paths.DATA_DIR, "thermograph.sqlite")
# Dialect selection mirrors accounts/db.py: a ``postgresql://`` URL in
# THERMOGRAPH_DATABASE_URL switches the store to Postgres; anything else keeps the
# SQLite file above. (This module uses the raw driver, not SQLAlchemy, so the DSN
# is a plain libpq URL — the ``+asyncpg`` / ``+psycopg`` SQLAlchemy suffix stripped.)
DATABASE_URL = os.environ.get("THERMOGRAPH_DATABASE_URL", "").strip()
IS_POSTGRES = DATABASE_URL.startswith("postgresql")
def _libpq_dsn(url: str) -> str:
"""A plain libpq URL that ``psycopg.connect`` accepts: drop the SQLAlchemy
driver suffix (``postgresql+asyncpg://`` / ``+psycopg://`` -> ``postgresql://``)."""
return url.replace("+asyncpg", "").replace("+psycopg", "")
_PG_DSN = _libpq_dsn(DATABASE_URL) if IS_POSTGRES else ""
_SCHEMA = """
CREATE TABLE IF NOT EXISTS derived (
kind TEXT NOT NULL, -- payload family: grade | calendar | day | forecast
cell_id TEXT NOT NULL,
key TEXT NOT NULL, -- request identity within the kind (dates/spans/params)
token TEXT NOT NULL, -- validity: mismatched token == miss (see module docstring)
payload BLOB NOT NULL, -- zlib-compressed JSON bytes
updated_at REAL NOT NULL,
PRIMARY KEY (kind, cell_id, key)
);
CREATE TABLE IF NOT EXISTS revgeo (
key TEXT PRIMARY KEY, -- "lat,lon" rounded to ~cell precision
label TEXT, -- NULL == lookup ran but found no label
updated_at REAL NOT NULL
);
"""
# Postgres mirror of _SCHEMA. UNLOGGED = fast, crash-non-durable (the cache is
# rebuildable, so "delete = safe reset" still holds); BLOB becomes BYTEA and REAL
# becomes DOUBLE PRECISION. psycopg's extended protocol runs one statement per
# execute, so the DDL is a tuple executed in turn (not one script like SQLite).
_PG_SCHEMA = (
"""
CREATE UNLOGGED TABLE IF NOT EXISTS derived (
kind TEXT NOT NULL,
cell_id TEXT NOT NULL,
key TEXT NOT NULL,
token TEXT NOT NULL,
payload BYTEA NOT NULL,
updated_at DOUBLE PRECISION NOT NULL,
PRIMARY KEY (kind, cell_id, key)
)
""",
"""
CREATE UNLOGGED TABLE IF NOT EXISTS revgeo (
key TEXT PRIMARY KEY,
label TEXT,
updated_at DOUBLE PRECISION NOT NULL
)
""",
)
# Statement text differs by dialect (placeholder style + upsert syntax); the SQLite
# strings are byte-for-byte the originals. Postgres uses %s params, an explicit
# column list, and ON CONFLICT ... DO UPDATE — which, like SQLite's INSERT OR
# REPLACE, overwrites *every* non-key column (token included, so a refreshed token
# supersedes the stored one and freshness keeps tracking the token, never the clock).
if IS_POSTGRES:
_SQL_GET_PAYLOAD = "SELECT token, payload FROM derived WHERE kind=%s AND cell_id=%s AND key=%s"
_SQL_PUT_PAYLOAD = (
"INSERT INTO derived (kind, cell_id, key, token, payload, updated_at) "
"VALUES (%s,%s,%s,%s,%s,%s) "
"ON CONFLICT (kind, cell_id, key) DO UPDATE SET "
"token=EXCLUDED.token, payload=EXCLUDED.payload, updated_at=EXCLUDED.updated_at"
)
_SQL_GET_REVGEO = "SELECT label, updated_at FROM revgeo WHERE key=%s"
_SQL_PUT_REVGEO = (
"INSERT INTO revgeo (key, label, updated_at) VALUES (%s,%s,%s) "
"ON CONFLICT (key) DO UPDATE SET label=EXCLUDED.label, updated_at=EXCLUDED.updated_at"
)
else:
_SQL_GET_PAYLOAD = "SELECT token, payload FROM derived WHERE kind=? AND cell_id=? AND key=?"
_SQL_PUT_PAYLOAD = "INSERT OR REPLACE INTO derived VALUES (?,?,?,?,?,?)"
_SQL_GET_REVGEO = "SELECT label, updated_at FROM revgeo WHERE key=?"
_SQL_PUT_REVGEO = "INSERT OR REPLACE INTO revgeo VALUES (?,?,?)"
# SQLite connections aren't shareable across threads; uvicorn serves requests on
# a thread pool, so each thread lazily opens its own connection. WAL lets those
# readers run concurrently with the (serialized) writers. The Postgres path keeps
# the same per-thread model (psycopg connections likewise aren't thread-safe).
_local = threading.local()
def _open_pg():
"""Open a thread-local psycopg connection and ensure the schema. autocommit so
reads never leave an idle-in-transaction and each write lands immediately (the
shared put/get code still calls ``.commit()``, a harmless no-op under autocommit)."""
import psycopg # local import: only the Postgres path needs it
conn = psycopg.connect(_PG_DSN, autocommit=True)
for stmt in _PG_SCHEMA:
conn.execute(stmt)
return conn
def _conn():
conn = getattr(_local, "conn", None)
if conn is not None:
# A dropped Postgres connection would otherwise disable the cache for the
# life of the thread; retire it so the next call reconnects.
if IS_POSTGRES and getattr(conn, "closed", False):
_local.conn = None
else:
return conn
try:
if IS_POSTGRES:
conn = _open_pg()
else:
os.makedirs(os.path.dirname(DB_PATH), exist_ok=True)
conn = sqlite3.connect(DB_PATH, timeout=5.0)
conn.execute("PRAGMA journal_mode=WAL")
conn.execute("PRAGMA synchronous=NORMAL")
conn.executescript(_SCHEMA)
_local.conn = conn
return conn
except Exception: # noqa: BLE001 - the store is optional; readers fall back
return None
# --- derived payloads -------------------------------------------------------
def get_payload(kind: str, cell_id: str, key: str, token: str) -> bytes | None:
"""Raw JSON bytes of a cached payload, or None when absent or token-invalid."""
conn = _conn()
if conn is None:
return None
try:
row = conn.execute(_SQL_GET_PAYLOAD, (kind, cell_id, key)).fetchone()
if row is None or row[0] != token:
return None
# psycopg returns bytea as bytes/memoryview; bytes() normalizes both.
data = bytes(row[1]) if IS_POSTGRES else row[1]
return zlib.decompress(data)
except Exception: # noqa: BLE001
return None
def get_json(kind: str, cell_id: str, key: str, token: str) -> dict | None:
"""Like get_payload but decoded — for callers assembling composite responses."""
body = get_payload(kind, cell_id, key, token)
return json.loads(body) if body is not None else None
def put_payload(kind: str, cell_id: str, key: str, token: str, payload: dict,
cache: bool = True) -> bytes:
"""Encode ``payload`` to compact JSON, persist it, and return the encoded bytes
(so the caller can serve the exact same bytes without re-serializing).
Pass ``cache=False`` to serve the payload without persisting it — used when a
best-effort field (the reverse-geocoded place name) failed to resolve, so the
incomplete result isn't cached for the life of the token.
allow_nan=False mirrors Starlette's JSONResponse: a NaN slipping through
grading should fail loudly here, not be cached as JS-unparseable `NaN`."""
body = json.dumps(payload, default=str, allow_nan=False,
separators=(",", ":")).encode()
conn = _conn()
if cache and conn is not None:
try:
conn.execute(
_SQL_PUT_PAYLOAD,
(kind, cell_id, key, token, zlib.compress(body, 6), time.time()),
)
conn.commit()
except Exception: # noqa: BLE001 - failing to cache must not fail the request
pass
return body
# --- reverse-geocode labels --------------------------------------------------
REVGEO_MISS_TTL = 3600.0 # a "no label" result may be transient (rate limit) — retry hourly
def revgeo_key(lat: float, lon: float) -> str:
# The "v2:" prefix versions the label format: v1 rows (no country) are bypassed
# and re-fetched so names pick up the trailing country component.
return f"v2:{round(lat, 3)},{round(lon, 3)}"
def get_revgeo(key: str) -> tuple[bool, str | None]:
"""(found, label). A stored NULL label counts as found (a cached miss) until
it ages past REVGEO_MISS_TTL, when the lookup becomes retryable."""
conn = _conn()
if conn is None:
return (False, None)
try:
row = conn.execute(_SQL_GET_REVGEO, (key,)).fetchone()
if row is None:
return (False, None)
if row[0] is None and time.time() - row[1] > REVGEO_MISS_TTL:
return (False, None)
return (True, row[0])
except Exception: # noqa: BLE001
return (False, None)
def put_revgeo(key: str, label: str | None) -> None:
conn = _conn()
if conn is None:
return
try:
conn.execute(_SQL_PUT_REVGEO, (key, label, time.time()))
conn.commit()
except Exception: # noqa: BLE001
pass
def stats() -> dict:
"""Row counts + on-disk size, for the migrate script's summary output."""
conn = _conn()
out = {"db_path": os.path.abspath(DB_PATH), "derived": 0, "revgeo": 0, "bytes": 0}
if conn is None:
return out
try:
out["derived"] = conn.execute("SELECT COUNT(*) FROM derived").fetchone()[0]
out["revgeo"] = conn.execute("SELECT COUNT(*) FROM revgeo").fetchone()[0]
# Recent writes may still live in the WAL sidecar — count both files.
out["bytes"] = sum(os.path.getsize(p) for p in (DB_PATH, DB_PATH + "-wal")
if os.path.exists(p))
except Exception: # noqa: BLE001
pass
return out