Sheets Exporter Pro

Export an Apify dataset to Google Sheets in a new tab created for that transfer. Google Sheets Exporter Pro verifies previously written ranges before it resumes, preserves spreadsheet-sensitive values, and stops rather than writing into an existing tab.

• Protect existing tabs. A new transfer creates its own tab and records Google's numeric sheet ID. It does not select an existing tab as the destination for a new transfer.
• Resume with verification. Re-run the same unchanged dataset, spreadsheet, and transferId to verify completed ranges before continuing. A completed transfer returns ALREADY_COMPLETE without writing its rows again.
• Keep IDs and scraped text intact. String IDs such as "00123", large integer IDs, 0, and false are preserved. Formula-like strings are written with Google's RAW mode so Sheets stores them as text.

Export an Apify dataset to Google Sheets

This Apify Google Sheets integration maps each dataset object to one spreadsheet row.

Given this Apify dataset item:

{
  "customer_id": "00123",
  "order_id": 1152921504606846976,
  "active": false,
  "note": "=IMPORTXML(\"https://example.com\", \"//title\")"
}

The Actor creates a new tab with this shape:

customer_id	order_id	active	note
00123	1152921504606846976 (text)	FALSE	=IMPORTXML(...) (literal text)

Nested objects become dotted columns such as user.name. Arrays remain JSON in one cell. The Actor also writes one transfer report to the run's default dataset:

{
  "status": "COMPLETE",
  "tabTitle": "export_ffdcbd57a7e5",
  "rowsTotal": 1250,
  "rowsWrittenThisRun": 1250,
  "rowsChargedTotal": 1250
}

Run your Google Sheets export in 3 steps

1. Open the target spreadsheet and share it with sheets-exporter@dock-labs.iam.gserviceaccount.com as an Editor.
2. Copy the spreadsheet ID: the token between /d/ and /edit in its URL.
3. Choose the source Apify dataset, paste the Google Sheets spreadsheet ID, and run the Actor.

The first run creates a tab named export_<derived-id>. Remove the service-account email from the spreadsheet at any time to revoke future access.

Prevent duplicate rows and protect existing Google Sheets tabs

Each transfer has a durable manifest and a stable transferId. Before writing a batch, the Actor records its intended range. After an interrupted request, it reads that range and compares it with the expected values before continuing.

• A matching range is accepted and not written again.
• An empty reserved range can be written.
• Unexpected content stops the transfer as NEEDS_RECONCILIATION; it is not overwritten.
• A completed re-run with the same unchanged source, target, and transferId returns ALREADY_COMPLETE.

Use one active run per transferId. Verification-based recovery reduces duplicate writes; it is not a promise that platform or network failures are impossible.

Preserve JSON IDs and formula-like text in Google Sheets

For JSON to Google Sheets transfers, the Actor applies these conversion rules:

• String IDs keep leading zeroes: "00123" stays 00123.
• Integers outside JavaScript's safe integer range are stored as text to preserve their digits.
• 0 remains numeric zero and false remains Boolean FALSE.
• Formula-like strings beginning with =, +, -, or @ are sent as RAW values rather than executed as formulas.
• null, a missing value, and an empty string all appear as an empty cell.
• No automatic date, currency, or locale conversion is applied.

Google Sheets export limits

Version 1 accepts non-empty Apify datasets containing JSON-object rows and enforces these bounds before silently dropping data:

• Up to 100,000 dataset rows.
• Up to 500 columns.
• Up to 49,000 characters in one cell.
• Up to 8 nested object levels.
• Up to Google's 10,000,000 allocated-cell spreadsheet limit.

When fields is supplied, only those field paths are exported and every other source field is intentionally excluded. Without fields, columns are discovered in stable first-seen order. Use a completed source dataset: a dataset that is still receiving rows is not a consistent snapshot.

Version 1 does not append or synchronize into an existing tab, import Sheets data back into Apify, expand arrays into multiple rows, or reinterpret dates and currencies. A new snapshot needs a new transferId; schedules do not generate dated IDs or tab names automatically.

How much does it cost to export an Apify dataset to Google Sheets?

Pricing is pay per event and includes platform usage:

Event	Price
Actor start	$0.005 per invocation that reaches billing
Row written	$0.0002 per row ($0.20 per 1,000)

The start fee applies to each invocation, including an ALREADY_COMPLETE re-run or a run that fails after billing begins. Data batches written and committed before a later failure may already be charged; rows never written are not submitted as row charges.

Examples:

• 1,000 written rows: $0.005 + (1,000 × $0.0002) = $0.205.
• 30 separate 500-row exports: 30 × ($0.005 + 500 × $0.0002) = $3.15.
• A 20,000-row transfer with maxChargedRows: 10000 stops before the next batch would exceed the 10,000-row transfer cap. At 10,000 written rows it costs $2.005.

maxChargedRows caps row charges across that transfer; it does not include Actor start fees. Because writes are batched, a transfer can stop below the requested cap rather than split a batch.

Google Sheets export inputs

Input	Required	Meaning
datasetId	Yes	Source Apify dataset. The Actor requests read access only to this selected dataset.
spreadsheetId	Yes	Target Google Sheets spreadsheet ID, not the full URL or gid.
fields	No	Exact flattened field paths and column order. Unlisted fields are excluded.
transferId	No	Stable ID used to resume the same logical transfer. A new ID creates a new tab.
maxChargedRows	No	Maximum data rows this transfer may write and charge across runs; excludes start fees.
mode	No	export, the only version 1 mode.

Google Sheets export statuses and recovery

Status	Meaning
COMPLETE	All source rows were committed.
ALREADY_COMPLETE	The same completed transfer was verified; no data rows were written again.
PARTIAL	A row-charge cap stopped the transfer before the next batch. Re-run the same unchanged transfer with a higher cap to continue.
NEEDS_RECONCILIATION	A reserved range or transfer-owned tab differed from the saved manifest. The Actor stopped instead of overwriting it.
FAILED	Input, access, capacity, source-change, Google API, or platform processing failed. Earlier committed batches can remain in the tab.

Handled outcomes produce one report record in the run's default dataset. A forced platform termination can end a process before it writes that final record.

Access and data handling

The Actor runs with limited Apify permissions and requests read access to the selected source dataset. Google access uses a creator-managed service account; sharing a spreadsheet grants that Google identity Editor access until you remove it. The implementation is designed to write only to the spreadsheet ID supplied for the run and only to a tab created for the transfer.

The Actor reads source rows during the run and does not log row contents. To support later recovery, it stores transfer metadata in an Apify key-value store: transfer and spreadsheet IDs, column headers, tab identity, batch checksums and statuses, and charge-journal records. This transfer metadata is retained indefinitely so that any future re-run of the same transferId stays safe and idempotent; it contains no row contents. To have a transfer's metadata deleted, open an issue on the Actor with the transferId and it will be removed within 3 business days.

Do not submit a dataset or share a spreadsheet unless you are authorized to process its contents. Never place a Google credential in the Actor input.

Google Sheets exporter FAQ

What happens if I run the same export twice?

With the same unchanged dataset, spreadsheet, and transferId, a completed transfer returns ALREADY_COMPLETE: it writes no data rows again and creates no second tab. The new invocation can still incur its $0.005 start fee. A different transferId creates a different snapshot tab.

Can the Actor write into an existing tab?

A new transfer creates its own tab. On resume, the Actor targets that tab by Google's numeric sheet ID. If the tab is missing, its header changed, or a reserved range contains unexpected values, the Actor stops instead of overwriting that content.

How do I schedule an Apify dataset export?

Trigger the Actor after the source dataset is complete. Reusing the same transferId resumes or verifies the same snapshot. To create a new snapshot on each schedule, pass a new deterministic transferId for that period, such as orders-2026-09-06. The current Actor does not generate dated IDs automatically.

Why does the Actor use a service account?

You do not provide a Google OAuth token or service-account key. You grant and revoke the Actor's Google access through the spreadsheet's Share dialog. The creator-managed service account can access every spreadsheet shared with it, so only share an intended target and remove it when no longer needed.

What should I do after PARTIAL?

Re-run the same unchanged transfer with a higher maxChargedRows. Completed batches are verified before the Actor continues. If the source content changed, start a new transfer rather than forcing it into the existing snapshot.

Why did the Actor stop at NEEDS_RECONCILIATION?

The saved manifest and the Google Sheet did not match. Do not delete a tab until you confirm whether it contains needed data. Use a new transferId for a separate snapshot; report a reproducible case without posting sheet contents or credentials in a public issue.