The one-shot VERIFY_DELAY_MINUTES check was too rigid: MassPrice's processing time varies widely in practice (observed ~1 to over 20 minutes, and its queue can back up further under load — confirmed live, a run still sitting in "Queued" 15+ minutes in), so a single check window either misses slow-but-fine completions or has to be set needlessly long. Replaced with a poll loop: scheduler.py reschedules another one-off check every VERIFY_POLL_MINUTES (default 5) until automation's check_completion() reports "complete", up to VERIFY_MAX_ATTEMPTS (default 12, ~1 hour) before giving up and marking "not_confirmed" for good. verify_run() is split into a pure check_completion() (no storage side effects) so scheduler.py's loop owns the retry/give-up decision; automation.py just answers "is it done yet". Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01H6TgffxTvYhqxykAbVQg2v
13 KiB
MassPrice Scheduler
A Flask app that drives a real headless-Chromium session against
massprice.tcgplayer.com (TCGplayer's bulk pricing-rule tool) to click
"Run Rule" for each of the user's pricing rules on a schedule set through
this app's own web UI. Runs as one Docker container on the user's Unraid
home server, deployed the same way as the other projects on that box
(arr-summary, card-grader, lunch-notifier, n64-tracker).
Why this exists
MassPrice has its own native per-rule scheduler (day-of-week + one time-of-day), but it's capped at 15 active schedules account-wide and only allows one run per day per rule — no multiple runs/day. Native runs also showed real clock drift during discovery (6–22 minutes late against their scheduled time). This tool replaces native scheduling entirely: each rule's native schedule should be set to Inactive once this tool is confirmed working, so there's exactly one thing triggering runs.
Architecture
app.py— Flask app, single shared-password session auth (LOGIN_PASSWORDenv var,hmac.compare_digest) — this protects the admin UI itself, unrelated to the MassPrice/TCGplayer login below. Routes:/(Dashboard — rule cards with schedule editor),/activity(run history),/session(login-session import), and a small JSON API (/api/rules/refresh,/api/rules/<id>/schedule,/api/rules/<id>/run,/api/session/import) that the frontend JS calls without full page reloads.scheduler.py— an in-process APSchedulerBackgroundSchedulerholding oneCronTriggerjob per(rule, schedule entry)pair, rebuilt fromschedules.jsonon startup and whenever the webui saves a change. Triggered jobs (and manual "Run Now" clicks) are pushed onto onequeue.Queue, drained by a single dedicated worker thread — this guarantees only one Playwright browser session is ever active at a time, matching how a human would actually operate the site and avoiding concurrent-session weirdness.- Must run in exactly one process.
gunicorn.conf.pypinsworkers = 1for this reason — a second worker would instantiate a second scheduler and duplicate every run. Fine for a low-traffic single-user tool. - Also drives the completion poll loop: after a run is confirmed
sent, a one-off
verify-<entry_id>-<attempt>job (APSchedulerdatetrigger, not recurring) firesVERIFY_POLL_MINUTESlater and callsautomation.check_completion(). Not complete yet? Another one-off job reschedules the next check the same interval later —_run_verification_check()inscheduler.pyowns this loop — up toVERIFY_MAX_ATTEMPTStimes, after which it's marked"not_confirmed"for good.rebuild_jobs()only ever removesrule-*jobs, deliberately, so editing a schedule mid-flight can't cancel a poll loop that's already in progress for an earlier run. These one-off jobs live only in the scheduler's in-memory jobstore (no persistent jobstore is configured) — a container restart mid-poll silently drops that one entry's remaining checks, leaving it stuck on whatever state it was last in (usually "pending"). Low-impact (an hour-long window, restarts are infrequent) but worth knowing if an entry is ever seen stuck on "Pending" long after the fact.
- Must run in exactly one process.
automation.py— all Playwright logic.list_rules()scrapeshttps://massprice.tcgplayer.com/Rule/Listfor the live rule id/name pairs (cached torules_cache.json, refreshed via the Dashboard's "Refresh Rules" button or on first boot).run_rule(id)finds that rule'sli.rule.widget-rulerow, clicks its.dropdown-ellipsisthree-dot toggle, clicks the row'sa.run-rule[data-rule-id=...]item — mirroring exactly what a human does in the UI — then must click through a confirmation modal (#ConfirmationModal→#Confirmation_Run; the same generic modal is reused for Delete Rule etc., so the confirm click is scoped to that specific modal instance). That confirmation step is not optional or cosmetic: confirmed by live testing that skipping it fires zero network requests and the rule silently never runs, even though the initial dropdown click "succeeds" with no error — an earlier version of this code did exactly that and every reported "success" was a false positive for a real stretch of production use. If a future site redesign changes this modal, watch for the same symptom: local history says success, MassPrice's own Activity Log never gets a matching entry. No public API was found or used — the "Run Rule" click handler is JS/AJAX-bound (no plain href, a delegated jQuery handler ondocument.body, not the element itself) and its request (POST /Rule/Run, confirmed by live network capture) is almost certainly anti-forgery-token protected, so automation drives the real page rather than replaying a raw HTTP POST.- Run verification — confirming the modal only means MassPrice
accepted the run; it still processes asynchronously on their side
(queued → running → Complete), taking anywhere from ~1 minute to over
20 in observed practice, and its queue can back up further under
load (observed directly: a run still sitting in "Queued" 15+ minutes
in).
run_rule()captures a "watermark" — thedata-activitylogidof that rule's current top entry on/Activity/List(a stable, monotonically increasing ID; deliberately not parsing the displayed timestamp string, which would need fragile date/timezone handling) — before submitting, logs the run asstatus: "sent"withverification: "pending", and the caller inscheduler.pystarts a poll loop (automation.check_completion(), everyVERIFY_POLL_MINUTES, up toVERIFY_MAX_ATTEMPTStimes — seescheduler.py's own section above for the mechanics). Each check re-scans/Activity/List: a new entry (higherdata-activitylogidthan the watermark) whose status text contains "Complete" →verification: "complete", loop stops; otherwise the loop keepsverification: "pending"and just updatesverify_messagewith the latest note, until attempts run out and it's markedverification: "not_confirmed"for good — which can mean "still processing somewhere past our patience", not necessarily "failed". Also worth knowing: a still-"Queued" MassPrice entry has nodata-activitylogidyet (no "View" link exists until it finishes), so_find_latest_activity()— shared by the watermark capture and every poll — correctly falls through to the previous completed entry rather than matching the in-flight one; that's why "no ID higher than the watermark" is the right "not done yet" signal, not a bug. The Activity page's "Complete" column surfaces all of this; "Status" shows whether the click itself was sent, independent of whether MassPrice finished it. - Session persistence — a Playwright
storage_state(cookies + localStorage) is saved to/data/auth_state.jsonand reused across runs: scheduled runs never touch the login form at all, they just load this saved session. When it's missing or has expired (detected by an unauthenticated visit to/Rule/Listsilently redirecting to the public marketing homepage/— there's no/loginURL to check against), the run fails with a clear "session expired or missing" error rather than attempting to log in — see below for why. storage.py— tiny JSON read/write helpers (temp-file +os.replace, so a crash mid-write can't corrupt state) for everything under/data:schedules.json,auth_state.json,run_history.json(bounded to the last 200 entries),rules_cache.json,notify_state.json(the session-expiry alert's send-once dedupe flag).templates//static/— a small, plain dark dashboard. This is a deliberately different, simpler visual identity than Arr Summary's teletext system — that design language is specific to that app, not a house style to reuse here.
Login — why it's manual, and how it works
MassPrice's login (store.tcgplayer.com/oauth/login, TCGplayer's shared
OAuth identity provider) is protected by hCaptcha. Two automated
approaches were tried and confirmed broken by live testing during
development — there is no selector fix for either, fully automated
login is not achievable here, full stop:
- Filling in the real username/password and clicking Submit — the
invisible captcha check silently never resolves for a headless/
automated browser, and the form just refuses to submit. An earlier
version of this app tried
MASSPRICE_USERNAME/MASSPRICE_PASSWORDthis way; removed once confirmed broken. - Driving a real human's clicks through a headless Chromium exposed via
Chrome remote debugging (
chrome://inspect) — also removed after testing. Still fails hCaptcha, because the browser itself (aHeadlessChromeuser-agent,navigator.webdriver = true) is what gets flagged, independent of who's actually clicking. Deliberately not pursued further than that one test: disguising that browser to get past hCaptcha's bot detection would be captcha evasion, not a session-handling technique, regardless of how legitimate running automation on your own account is.
What actually works: log in with an ordinary, non-automated browser — hCaptcha passes the way it always does for a real person, because nothing about that browser looks automated — then copy that session's cookies over. The Session page in the webui drives this:
- The user logs into massprice.tcgplayer.com in their own regular Chrome and exports its cookies with a browser extension (Cookie-Editor, "Export as JSON").
- They paste that JSON into the Session page and click "Import Session".
automation.import_cookies()parses it, converts each cookie from Cookie-Editor's shape into Playwright'sstorage_statecookie shape (_convert_cookie()— mainly thesameSiteenum values and theexpirationDate→expiresfield rename), and — critically — verifies it actually authenticates (a real headless request to/Rule/List, checked with the same_is_logged_out()used everywhere else) before saving it to/data/auth_state.json. A bad paste never overwrites a working session.
This session is a real, live bearer credential for the user's MassPrice
account for as long as it's valid — same trust model as LOGIN_PASSWORD/
SECRET_KEY in .env (server-only, gitignored, never in git), not
something to treat as inert config. It isn't permanent: every successful
automated run re-saves it (_save_state()), which tends to slide a
"remember me"-style cookie's expiration forward, but it will eventually
expire (inactivity, a password change, TCGplayer forcing re-auth) and
need re-importing.
The Dashboard shows a red banner (_session_warning() in app.py) when
the most recent run/refresh failed specifically because of a missing/
expired session, so this doesn't just look like "no rules found."
Session-expiry email alert
notify.py — a thin Gmail-SMTP-with-app-password sender, the same
pattern lunch-notifier already uses on this box (reused deliberately
rather than adding a second notification channel). GMAIL_USER/
GMAIL_APP_PASSWORD (a Gmail app password, not the real account
password — Gmail blocks plain SMTP auth otherwise) and optional
ALERT_EMAIL (defaults to GMAIL_USER). send_alert() is a best-effort
no-op — returns False and just logs — if those env vars aren't set or
the send fails, since a broken mail config shouldn't break automation.
Fires exactly once per expiry, not on every failed scheduled run
while it's down: automation._notify_session_expired_once() is called
from _ensure_authenticated() right before it raises, checks/sets a
session_expired_notified flag in notify_state.json, and only sends
if that flag isn't already set. The flag resets to False the moment
import_cookies() successfully saves a fresh session, so the next
expiry gets its own alert. The flag is only set True after a
confirmed-sent email — if mail is misconfigured, every failing run keeps
retrying the send rather than silently giving up after the first one.
Local development
pip install -r requirements.txt
playwright install chromium # only needed if testing automation.py directly
python3 app.py
Runs on port 5000 (PORT env to change). Without Chromium installed and
without a saved auth_state.json, the Dashboard still boots —
_bootstrap() in app.py best-effort-catches the initial rule sync, so
local UI/schedule-editing work doesn't require Docker or a real MassPrice
session at all. DATA_DIR env var overrides where JSON state is
read/written (defaults to /data, which won't exist locally — point it
at a scratch directory).
Every commit should be matched with a version bump —
APP_VERSION/APP_VERSION_DATE near the top of app.py — the same
"does the footer prove this deploy landed" signal used on Arr Summary.
Deployment
See the deploy-massprice skill for the Forgejo push-to-deploy
pipeline and manual container restart steps.
Never put real credentials in the repo. .env and data/ are
gitignored and excluded from the deploy rsync precisely so
LOGIN_PASSWORD/SECRET_KEY and the saved
MassPrice session (data/auth_state.json) have somewhere to live
outside git.