Files
peter fad656988a fix(activity): runs keep their true outcome and spend, the page reaches every kept row, a closing dialog leaves the server log alone
Backend
- A run's outcome write sits outside the job's own try: a database blip after a run that
  succeeded no longer records it as failed (the row waits for the next start's sweep).
- An interrupted run keeps what it spent (the sweep sums its quota rows, as finish does).
- The Scheduler's ad-hoc row says running while any backfill runs, not only the newest.
- recent_runs reads each job's last runs off its index instead of ranking the whole table.
- An interval change is stored with its audit row in one transaction, then rescheduled.
- One API instance per database is the stated contract (.env.example, jobruns).
- Turning full history on for a channel already complete records no run.
- Migration 0109 round-trips interrupted and ad-hoc runs; the run words' DB CHECKs are
  test-held to the enums; the account filter is one helper for the four activity reads.
- An audit row says how many of its request's log lines are still kept.

Frontend
- An "All" period reaches every row still kept (runs and admin actions outlive 90 days).
- Back/Forward is followed in place by the server log: a closing dialog no longer turns
  Live off; a pivot still opens a fresh log.
- Runs moved over from the audit log read their one-liner in the reader's language.
- Filter choices or accounts that failed to load say so beside the filters, with a retry.
- An old server-log link keeps its account, text and range; a remembered retired page
  opens its tab.
- A request whose lines are gone says so instead of linking to an empty list.
- The log lines and the history rows share one row frame, and the server log one list
  frame with the other tabs; an empty list is announced; each day's quota is readable.
2026-10-18 15:38:32 +02:00

178 lines
7.3 KiB
Python

"""The admin diagnostics console's read side: query `log_events`, the server's stored log.
Admin-only and read-only — rows leave the table through the retention job (`log_retention_days`),
never through here. Reading is not audited: it changes nothing, and the console's live tail polls,
so a row per read would bury the audit log's real entries.
What a row holds was redacted when it was written (`logs.record_fields`, and the ingest route for a
browser's rows), so this serves the columns as they are; a value the redactor took out reads as
`[redacted]` / `[email]`, which is the point — the console shows that something was there.
Paging is a keyset over `(ts desc, id desc)` (`_keyset`). The live tail re-reads the first page rather than asking for "ids after N":
several processes write this table, and a batch's ids are taken when it inserts, not when it
commits, so a slower batch can land below an id the tail already passed — and would never show.
"""
from dataclasses import dataclass
from datetime import datetime
from typing import Literal
from fastapi import APIRouter, Depends, Query
from sqlalchemy import Text, cast, func, or_, select
from sqlalchemy.orm import Session
from app import logsink
from app.auth import admin_user
from app.db import get_db
from app.models import LogEvent, User
from app.routes import _account as account
from app.routes._keyset import PAGE_MAX, accounts, older_than, page, utc
from app.utils import like_escape
router = APIRouter(prefix="/api/admin/logs", tags=["admin"])
# A facet list is a chip row, not a report: past this many distinct events the rest are reachable
# through the free-text search, and the response stays small whatever a self-host logs.
FACET_EVENTS_MAX = 100
Level = Literal["TRACE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
# The filters a facet can leave out of its own count (`LogFilters.conditions`).
Facet = Literal["levels", "sources", "user", "event"]
# `none` selects the rows that have no event code, as the account filter's `none` (app/routes/_account)
# selects the rows of no account — a real value to filter on, not the absence of a filter.
NONE = account.NONE
@dataclass(frozen=True)
class LogFilters:
"""The console's filters, shared by the page and its facet counts."""
levels: list[str]
sources: list[str]
user: str | None
event: str | None
request_id: str | None
job_id: int | None
run_id: int | None
q: str | None
since: datetime | None
until: datetime | None
def conditions(self, skip: Facet | None = None) -> list:
"""The WHERE conditions, ANDed by the caller. `skip` leaves one filter out: a facet counts
its own values under every OTHER filter, so picking a level does not zero the other
levels' counts (the way back), while a request pivot does narrow them (honest counts)."""
out = []
if self.levels and skip != "levels":
out.append(LogEvent.level.in_(self.levels))
if self.sources and skip != "sources":
out.append(LogEvent.source.in_(self.sources))
if self.user is not None and skip != "user":
out.append(account.condition(LogEvent.user_id, self.user))
if self.event is not None and skip != "event":
out.append(
LogEvent.event.is_(None) if self.event == NONE else LogEvent.event == self.event
)
if self.request_id is not None:
out.append(LogEvent.request_id == self.request_id)
if self.job_id is not None:
out.append(LogEvent.job_id == self.job_id)
if self.run_id is not None:
out.append(LogEvent.run_id == self.run_id)
if self.since is not None:
out.append(LogEvent.ts >= utc(self.since))
if self.until is not None:
out.append(LogEvent.ts < utc(self.until))
if self.q and self.q.strip():
like = f"%{like_escape(self.q.strip())}%"
out.append(
or_(
LogEvent.msg.ilike(like),
LogEvent.event.ilike(like),
LogEvent.request_id.ilike(like),
LogEvent.exc.ilike(like),
cast(LogEvent.attrs, Text).ilike(like),
)
)
return out
def log_filters(
levels: list[Level] = Query(default=[]),
sources: list[str] = Query(default=[], max_length=8),
user: str | None = Query(default=None, pattern=account.PATTERN),
event: str | None = Query(
default=None, max_length=64, pattern=r"^(none|[a-z][a-z0-9_]*(\.[a-z0-9_]+)*)$"
),
request_id: str | None = Query(default=None, pattern=r"^[A-Za-z0-9._-]{8,64}$"),
job_id: int | None = Query(default=None, ge=1),
run_id: int | None = Query(default=None, ge=1),
q: str | None = Query(default=None, max_length=200),
since: datetime | None = None,
until: datetime | None = None,
) -> LogFilters:
return LogFilters(
list(levels), list(sources), user, event, request_id, job_id, run_id, q, since, until
)
@router.get("")
def list_logs(
filters: LogFilters = Depends(log_filters),
before: str | None = Query(default=None, max_length=200),
limit: int = Query(default=100, ge=1, le=PAGE_MAX),
_: User = Depends(admin_user),
db: Session = Depends(get_db),
) -> dict:
"""One page of rows, newest first, matching every filter given (they AND together); `before`
continues from a previous page's `next_cursor`."""
query = select(LogEvent).where(*filters.conditions())
if before is not None:
query = query.where(older_than(LogEvent.ts, LogEvent.id, before))
rows, cursor = page(
list(
db.execute(query.order_by(LogEvent.ts.desc(), LogEvent.id.desc()).limit(limit + 1))
.scalars()
.all()
),
limit,
lambda r: r.ts,
)
return {
"items": [logsink.serialize(r) for r in rows],
"accounts": accounts(db, {r.user_id for r in rows if r.user_id is not None}),
"next_cursor": cursor,
}
@router.get("/facets")
def log_facets(
filters: LogFilters = Depends(log_filters),
_: User = Depends(admin_user),
db: Session = Depends(get_db),
) -> dict:
"""What the filter chips offer, with counts: the levels, sources and accounts present, and the
most frequent events — each counted under every filter but its own (`LogFilters.conditions`).
`total` is the "all levels" count: every filter but the level one."""
def counts(col, skip: Facet, cap: int | None = None) -> list[dict]:
n = func.count().label("n")
stmt = select(col, n).where(*filters.conditions(skip)).group_by(col).order_by(n.desc(), col)
if cap is not None:
stmt = stmt.limit(cap)
return [
{"value": NONE if value is None else value, "count": count}
for value, count in db.execute(stmt).all()
]
users = counts(LogEvent.user_id, "user")
total = select(func.count()).select_from(LogEvent).where(*filters.conditions("levels"))
return {
"levels": counts(LogEvent.level, "levels"),
"sources": counts(LogEvent.source, "sources"),
"events": counts(LogEvent.event, "event", FACET_EVENTS_MAX),
"users": [{**u, "value": str(u["value"])} for u in users],
"accounts": accounts(db, {u["value"] for u in users if u["value"] != NONE}),
"total": db.scalar(total) or 0,
}