TASK-032: Implement geo_cache retention policy and cleanup
Add automatic cleanup of stale geolocation cache entries to prevent unbounded database growth. Resolves the issue where unique IP addresses accumulated indefinitely in the geo_cache table, degrading query performance. ## Changes ### Database Schema (Migration 3) - Add 'last_seen' column to geo_cache table tracking last reference time - Existing entries default to current timestamp ### Repository Layer (geo_cache_repo.py) - Update upsert_entry() to set/refresh last_seen on insert/update - Update upsert_neg_entry() to set/refresh last_seen on negative cache hits - Update bulk_upsert_entries() to set/refresh last_seen in batch operations - Add delete_stale_entries(db, cutoff_iso) -> int for purging old entries ### Background Task (geo_cache_cleanup.py) - New APScheduler task that runs nightly (24-hour interval) - Calculates cutoff as 90 days ago from current time (UTC) - Deletes all entries with last_seen older than cutoff - Logs operation results (info when deleted > 0, debug when 0 deleted) - Configurable retention period via GEO_CACHE_RETENTION_DAYS constant ### Application Startup (startup.py) - Register geo_cache_cleanup task in scheduler during app startup - Placed after geo_cache_flush in task registration order ### Tests - Add delete_stale_entries test cases covering: * Removal of old entries beyond cutoff * No deletion when all entries are recent * Empty table edge case - Update existing test fixtures to include last_seen column - Add full test suite for cleanup task registration and execution ### Documentation - Architekture.md: Document cleanup task, update schema/diagram - Backend-Development.md: Add retention policy documentation ## Behavior When an IP is accessed, its last_seen is refreshed. After 90 days of no access, an IP is purged by the nightly cleanup. On next encounter, the IP is re-resolved from MaxMind MMDB or ip-api.com (if configured). This is acceptable because: 1. Stale geolocation data may become inaccurate over time 2. Re-resolution cost is minimal compared to unbounded storage growth 3. Active IPs maintain fresh data through their last_seen updates Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
@@ -107,7 +107,7 @@ _SCHEMA_STATEMENTS: list[str] = [
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_CREATE_HISTORY_ARCHIVE,
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]
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_CURRENT_SCHEMA_VERSION: int = 2
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_CURRENT_SCHEMA_VERSION: int = 3
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_MIGRATIONS: dict[int, str] = {
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1: "\n".join(_SCHEMA_STATEMENTS),
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@@ -124,6 +124,12 @@ CREATE TABLE sessions (
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expires_at TEXT NOT NULL
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);
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CREATE UNIQUE INDEX idx_sessions_token_hash ON sessions (token_hash);
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""",
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3: """
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-- Migration 3: Add last_seen timestamp to geo_cache for retention policy.
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-- Tracks when each IP was last referenced to enable purging of stale entries.
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-- Default to current timestamp for existing rows.
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ALTER TABLE geo_cache ADD COLUMN last_seen TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ', 'now'));
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""",
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}
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@@ -98,7 +98,8 @@ async def upsert_entry(
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country_name = excluded.country_name,
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asn = excluded.asn,
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org = excluded.org,
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cached_at = strftime('%Y-%m-%dT%H:%M:%fZ', 'now')
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cached_at = strftime('%Y-%m-%dT%H:%M:%fZ', 'now'),
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last_seen = strftime('%Y-%m-%dT%H:%M:%fZ', 'now')
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""",
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(ip, country_code, country_name, asn, org),
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)
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@@ -120,7 +121,11 @@ async def upsert_entry_and_commit(
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async def upsert_neg_entry(db: aiosqlite.Connection, ip: str) -> None:
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"""Record a failed lookup attempt as a negative entry."""
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await db.execute(
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"INSERT OR IGNORE INTO geo_cache (ip) VALUES (?)",
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"""
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INSERT INTO geo_cache (ip) VALUES (?)
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ON CONFLICT(ip) DO UPDATE SET
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last_seen = strftime('%Y-%m-%dT%H:%M:%fZ', 'now')
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""",
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(ip,),
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)
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@@ -148,7 +153,8 @@ async def bulk_upsert_entries(
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country_name = excluded.country_name,
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asn = excluded.asn,
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org = excluded.org,
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cached_at = strftime('%Y-%m-%dT%H:%M:%fZ', 'now')
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cached_at = strftime('%Y-%m-%dT%H:%M:%fZ', 'now'),
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last_seen = strftime('%Y-%m-%dT%H:%M:%fZ', 'now')
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""",
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rows,
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)
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@@ -202,3 +208,21 @@ async def bulk_upsert_entries_and_neg_entries_and_commit(
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await db.commit()
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return positive_count, negative_count
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async def delete_stale_entries(db: aiosqlite.Connection, cutoff_iso: str) -> int:
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"""Delete geo cache entries not referenced since the cutoff timestamp.
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Args:
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db: Open BanGUI application database connection.
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cutoff_iso: ISO 8601 timestamp (e.g., '2024-01-01T00:00:00Z'). Entries with
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``last_seen`` before this time will be deleted.
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Returns:
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The number of rows deleted.
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"""
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async with db.execute(
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"DELETE FROM geo_cache WHERE last_seen < ?",
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(cutoff_iso,),
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) as cur:
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return cur.rowcount if cur.rowcount is not None else 0
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@@ -19,7 +19,15 @@ from apscheduler.schedulers.asyncio import AsyncIOScheduler # type: ignore[impo
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from app.db import init_db, open_db
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from app.services import setup_service
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from app.services.geo_cache import GeoCache
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from app.tasks import blocklist_import, geo_cache_flush, geo_re_resolve, health_check, history_sync, session_cleanup
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from app.tasks import (
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blocklist_import,
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geo_cache_cleanup,
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geo_cache_flush,
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geo_re_resolve,
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health_check,
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history_sync,
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session_cleanup,
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)
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from app.utils.async_utils import run_blocking
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from app.utils.jail_config import ensure_jail_configs
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from app.utils.runtime_state import set_runtime_settings
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@@ -185,6 +193,7 @@ async def startup_shared_resources(
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health_check.register(app)
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await blocklist_import.register(app)
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geo_cache_cleanup.register(app)
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geo_cache_flush.register(app)
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geo_re_resolve.register(app)
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history_sync.register(app)
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90
backend/app/tasks/geo_cache_cleanup.py
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90
backend/app/tasks/geo_cache_cleanup.py
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@@ -0,0 +1,90 @@
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"""Geo cache cleanup background task.
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Registers an APScheduler job that periodically removes stale entries from the
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``geo_cache`` table — entries that have not been referenced in the configured
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retention period (default: 90 days). This prevents unbounded growth of the
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database file and maintains query performance on geo lookups.
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When a stale IP is encountered again after purge, it will be re-resolved from
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the MaxMind database or ip-api.com (if configured), which is acceptable.
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"""
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from __future__ import annotations
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from datetime import UTC, datetime, timedelta
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from typing import TYPE_CHECKING
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import structlog
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from app.repositories import geo_cache_repo
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from app.tasks.db import task_db
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from app.utils.runtime_state import get_effective_settings
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if TYPE_CHECKING:
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from fastapi import FastAPI
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from app.config import Settings
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log: structlog.stdlib.BoundLogger = structlog.get_logger()
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#: How long to retain geo cache entries (days). Configurable tuning constant.
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GEO_CACHE_RETENTION_DAYS: int = 90
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#: How often the cleanup job fires (seconds). Default: once per day.
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GEO_CLEANUP_INTERVAL: int = 24 * 60 * 60
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#: Stable APScheduler job ID — ensures re-registration replaces, not duplicates.
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JOB_ID: str = "geo_cache_cleanup"
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async def _run_cleanup_with_resources(settings: Settings) -> None:
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"""Delete stale entries from the geo cache.
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Calculates a cutoff timestamp (now - retention period) and removes all
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entries with ``last_seen`` before that time. Logs the operation result.
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Args:
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settings: The resolved application settings used for database access.
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"""
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cutoff_dt = datetime.now(UTC) - timedelta(days=GEO_CACHE_RETENTION_DAYS)
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cutoff_iso = cutoff_dt.strftime("%Y-%m-%dT%H:%M:%SZ")
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async with task_db(settings) as db:
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deleted = await geo_cache_repo.delete_stale_entries(db, cutoff_iso)
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await db.commit()
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if deleted > 0:
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log.info("geo_cache_cleanup_ran", deleted=deleted, retention_days=GEO_CACHE_RETENTION_DAYS)
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else:
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log.debug("geo_cache_cleanup_ran", deleted=deleted, retention_days=GEO_CACHE_RETENTION_DAYS)
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async def _run_cleanup(app: FastAPI) -> None:
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"""Run cleanup with application settings."""
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await _run_cleanup_with_resources(get_effective_settings(app))
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def register(app: FastAPI) -> None:
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"""Add (or replace) the geo cache cleanup job in the application scheduler.
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Must be called after the scheduler has been started (i.e., inside the
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lifespan handler, after ``scheduler.start()``).
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Args:
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app: The :class:`fastapi.FastAPI` application instance whose
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``app.state.scheduler`` will receive the job.
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"""
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settings = get_effective_settings(app)
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app.state.scheduler.add_job(
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_run_cleanup_with_resources,
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trigger="interval",
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seconds=GEO_CLEANUP_INTERVAL,
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kwargs={"settings": settings},
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id=JOB_ID,
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replace_existing=True,
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)
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log.info(
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"geo_cache_cleanup_scheduled",
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interval_seconds=GEO_CLEANUP_INTERVAL,
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retention_days=GEO_CACHE_RETENTION_DAYS,
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)
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