Timeleft Scraper - Events, Dinners & Schedules in 200 Cities

Timeleft Scraper at a glance

Timeleft Scraper is a ready-to-run Apify actor from abotapi for collecting web data. Its output documents 25 fields, including session id, city, country, city members and city lng, which you can export as JSON, CSV or Excel or read through the Apify API. It costs $3.00 per 1,000 results on the Apify Free plan and from $2.00 on paid plans, with smaller per-run or optional feature charges listed on Apify.

Runs on: Apify cloud: console, API, schedules and integrations
Data type: Web data
Pricing: $3.00 per 1,000 results (Free plan), from $2.00 on paid plans
Output: 25 documented fields · JSON, CSV, Excel
Inputs: 14 options

What Timeleft Scraper can do

Every city, one run. Sweep all 197 Timeleft cities or name the ones you care about (Paris, New York, London) and get roughly three weeks of scheduled sessions per city.
Booking momentum included. Each session carries its live booking headcount, so you can track which formats and cities fill fastest.
No credentials needed. Pick cities and run; access is handled automatically.
Built for schedules. Incremental mode returns only new, changed and expired sessions on recurring runs, and a resume option continues one interrupted sweep without re-collecting rows.
Honest limits. Venues, attendees and booking stay behind Timeleft's paid subscription, so this actor returns schedules only, and says so.

Choose what to collect

These inputs let you configure Timeleft Scraper - Events, Dinners & Schedules in 200 Cities. Open the actor on Apify to enter your values and review the current options.

Supported input fields
Input	What it controls
`cities`array	City names, numeric ids, or 'City, Country' form, e.g. 'Paris', '209', 'Paris, France'. Minor typos are tolerated and logged as read; abbreviations are not guessed. Every result holds up to ~3 weeks of scheduled sessions per city. Leave empty to sweep all 197 catalog cities (about 1,900 sessions). Unknown cities are skipped with a warning.
`eventTypes`array	Pick one or more formats to include; leave empty for all formats.
`maxItems`integer	Stop after this many sessions across all cities. 0 = unlimited full sweep of the scoped cities (about 1,900 sessions for all 197).
`fetchHeadcounts`boolean	Also read per-event booking totals (one extra read per city) into dayUsersBooked (day-level booking totals). Turn off for a lighter run with schedules only.
`accountKey`string	Gives each key its own saved state, so hundreds of monitors can run side by side without sharing or racing one. Leave default for single use.
`resumeFromRunId`string	Paste a previous run ID or dataset ID to continue one interrupted sweep. Sessions already collected there are skipped. Distinct from Incremental mode below, which tracks the same scope across scheduled runs by itself.
`incrementalMode`boolean	When ON, the actor remembers its sessions from the previous run of the same scope and tags every row with changeType: NEW, UPDATED, UNCHANGED, REAPPEARED or EXPIRED. Use with the Apify Scheduler to monitor schedules over time.

Show 7 more inputs

More input fields
Input	What it controls
`stateKey`string	A name for this monitor's saved state, e.g. 'paris-dinners'. Leave empty to key the baseline automatically to your exact cities, event types and headcount toggle (changing the scope then starts fresh). Set a key to pin one baseline across runs; use distinct keys for independent monitors.
`emitUnchanged`boolean	When ON, sessions with no detected change are still pushed (tagged UNCHANGED) instead of skipped. This returns, and bills, one extra row per unchanged session.
`emitExpired`boolean	When ON, sessions tracked before but no longer scheduled after a complete, uncapped scan are pushed once tagged EXPIRED. Only fires on a run that scans its whole scope.
`ignoreFieldsForChanges`array	Output field names that should NOT mark a session UPDATED. The scrape timestamp is always ignored. Add fields such as dayUsersBooked here if booking-count drift is not relevant to you.
`mcpConnectors`array	Optionally send the results into the apps you already use, via Model Context Protocol (MCP) connectors. Authorize a connector once under Apify → Settings → Integrations, then select it here. The connector receives a condensed, human-readable summary per session, not the full JSON, the complete record stays in the dataset. Leave empty to skip. Supported: Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/sse), Airtable (https://mcp.airtable.com/mcp), Apify (https://mcp.apify.com).
`notionParentPageUrl`string	URL (or id) of the Notion page under which item pages are created. Required to enable the Notion export; ignored by other connectors.
`maxNotifyListings`integer	Cap on items written to each connector per run. Does not affect the dataset.

Fields in the output

The documented dataset includes the fields below. Availability can depend on the source page and selected mode.

idSession ID (text)

cityCity (text)

countryCountry (text)

cityUserCountCity members (number)

cityLongitudeCity lng (number)

cityLatitudeCity lat (number)

dateDate (date)

eventTypeFormat (text)

tagsTags (text)

statusStatus (text)

coverUrlCover (image)

introTitleTitle (text)

Show 13 more fields

introDescriptionDescription (text)

zoneIdZone (text)

dayUsersBookedBooked (day total) (number)

groupSizeGroup size (number)

maxParticipantsCapacity (number)

bookingCutoffISOBooking cutoff (date)

changeTypeChange type (incremental mode) (text)

waitlistOnlyGendersWaitlist genders (text)

hasBookingGateBooking gate (boolean)

partnerImageUrlPartner image (image)

changedFieldsChanged fields (text)

firstSeenAtFirst seen (date)

lastSeenAtLast seen (date)

Example output

An example from this actor’s documentation. Values are illustrative; this is not a fresh live result.

{
  "id": "3f9e8b2c-5d6a-4e7f-9a0b-c1d2e3f4a5b6",
  "city": "Sample City",
  "date": "2026-12-31",
  "eventType": "drinks",
  "zoneId": "100",
  "dayUsersBooked": 42,
  "groupSize": 7
}

Ways to use this data

Demand researchers: track event volume and booking momentum across cities to spot where social-dining demand runs hottest.
Travel and relocation planners: see which formats run in a destination city before a trip.
Competitive analysts: monitor how a subscription-based experiences marketplace paces its supply.
Data teams: feed a recurring schedule snapshot into dashboards via the API or scheduled runs.
Marketers: time outreach around high-momentum formats and cities.

Before you run

Start with a small input and check the resulting records against your expected fields. Source content and actor options can change; the current Apify listing is the reference for availability and pricing.

Questions about this actor

What data does Timeleft Scraper return?

Timeleft Scraper returns 25 documented fields, including session id, city, country, city members, city lng, city lat, date and format. Availability of each field depends on the source page and the selected mode.

How much does Timeleft Scraper cost?

It costs $3.00 per 1,000 results on the Apify Free plan and from $2.00 on paid plans, with smaller per-run or optional feature charges listed on Apify. The Apify listing shows the current rate for every plan.

Can it book dinners or show venues and attendees?

No. Booking, venues and attendee lists require Timeleft's paid subscription, which an actor cannot purchase. This actor returns schedules and booking headcounts only.

Why did my run return zero sessions?

Either every requested city name missed the catalog (check the run log for the unknown-cities warning), the scope filters excluded everything, or the source was temporarily unreachable, so rerun later.

How do scheduled runs work?

Turn on Incremental mode with a state key and schedule the actor: the first run tags everything NEW, later runs return only NEW, UPDATED and REAPPEARED sessions (plus EXPIRED when enabled) instead of the full snapshot.

Does it work with AI and MCP tools?

Yes. Select MCP connectors in the input to pipe per-session summaries into Notion, Linear, Airtable or Apify while the full JSON stays in the dataset. 🔗 Pair with more event data. Combine Timeleft schedules with these related scrapers from the same team: - 🎟️ Ticketmaster Events Scraper : concerts, festivals and sports with dates, venues and ticket tiers - 🎫 Eventim Scraper : German live events, dates and tickets - 🎸 Concert Archives Scraper : concert history, tours, venues and setlists