# Google Sheets Import & Export (`eszetael_lab/google-sheets-import-export`) Actor Import a Google Sheet range into a clean dataset, or export data (JSON/dataset) to a sheet. Service-account auth, no OAuth flow. Reliable, flat, AI-ready. - **URL**: https://apify.com/eszetael\_lab/google-sheets-import-export.md - **Developed by:** [Radosław Szal](https://apify.com/eszetael_lab) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Google Sheets Import & Export Move data between **Google Sheets** and Apify — no OAuth dance, no browser: - **Import** — read a sheet range into a clean, flat dataset (JSON/CSV/Excel). - **Export** — write JSON data (or a whole Apify dataset) into a sheet, overwrite or append. Pairs with any scraper: **scrape → export to a sheet**, or **import a sheet → feed your pipeline**. ### Setup (once, ~2 min) — service account The actor authenticates with a **Google service account** (a robot Google account), so it only ever touches sheets you explicitly share with it: 1. In **Google Cloud Console** → *APIs & Services* → enable the **Google Sheets API**. 2. *IAM & Admin* → **Service Accounts** → create one → **Keys** → *Add key* → **JSON** → download. 3. Open the JSON, copy its contents into the **Google service account key** input (stored as a secret). 4. **Share your spreadsheet** with the service account's e-mail (the `client_email` in the JSON) — *Viewer* for import, *Editor* for export. ### Import ```json { "mode": "import", "spreadsheetId": "1AbC…xyz", "range": "Sheet1!A:Z", "firstRowAsHeader": true } ```` Row 1 becomes the field names; each following row becomes a record (plus `_row`, the sheet row number). With `firstRowAsHeader: false` the columns are named `A`, `B`, `C`… ### Export ```json { "mode": "export", "spreadsheetId": "1AbC…xyz", "range": "Sheet1!A1", "data": [ { "name": "Ada", "score": 91 }, { "name": "Alan", "score": 88 } ], "includeHeader": true, "append": false } ``` - **Objects** → keys become the header row (order = first seen, or set `columns`). - **Arrays** → written positionally, no header. - `append: true` adds rows after the existing data instead of overwriting the range. - Or set `sourceDatasetId` instead of `data` to export a whole Apify dataset. Each written row comes back as a dataset record (a receipt of exactly what was sent to the sheet). ### Notes - **Integration, not scraping** — reads/writes only sheets you share with the service account. No public scraping, no personal data harvested from third parties. - Backs off automatically on Google API rate limits (HTTP 429). - **Pricing** — pay per row (result-item), flat. The first rows of every run are free to test. - Migration-safe imports (a restarted run resumes without duplicating rows) and **overwrite**-mode exports (idempotent). **Append**-mode export is best-effort at-least-once — for exactly-once on a platform restart, use overwrite mode (`append: false`). # Actor input Schema ## `mode` (type: `string`): import = read a sheet range into the dataset. export = write rows to a sheet. ## `spreadsheetId` (type: `string`): The ID from the sheet URL: docs.google.com/spreadsheets/d//edit ## `range` (type: `string`): e.g. 'Sheet1!A:Z' to import a whole area, or 'Sheet1!A1' as the export anchor. ## `serviceAccountJson` (type: `object`): Paste the full JSON key of a Google Cloud service account. Create it in GCP → IAM → Service Accounts → Keys, enable the Google Sheets API, and SHARE the spreadsheet with the account's email (client\_email). Stored as a secret. ## `firstRowAsHeader` (type: `boolean`): Import: use row 1 as field names. Off = columns become A, B, C… ## `data` (type: `array`): Export: rows to write — array of objects (keys become the header) or array of arrays. ## `sourceDatasetId` (type: `string`): Export alternative to 'data': pull rows from an existing Apify dataset. ## `columns` (type: `array`): Optional explicit column order for object rows. Default = order first seen. ## `append` (type: `boolean`): Export: append after existing rows instead of overwriting the range. ## `includeHeader` (type: `boolean`): Export: write a header row of column names above the data (for object rows). ## `maxItems` (type: `integer`): Cap on rows imported/exported (0 = up to the safety limit of 50000). ## Actor input object example ```json { "mode": "import", "range": "Sheet1!A:Z", "firstRowAsHeader": true, "append": false, "includeHeader": true, "maxItems": 10000 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "range": "Sheet1!A:Z" }; // Run the Actor and wait for it to finish const run = await client.actor("eszetael_lab/google-sheets-import-export").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "range": "Sheet1!A:Z" } # Run the Actor and wait for it to finish run = client.actor("eszetael_lab/google-sheets-import-export").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "range": "Sheet1!A:Z" }' | apify call eszetael_lab/google-sheets-import-export --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=eszetael_lab/google-sheets-import-export", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Sheets Import & Export", "description": "Import a Google Sheet range into a clean dataset, or export data (JSON/dataset) to a sheet. Service-account auth, no OAuth flow. Reliable, flat, AI-ready.", "version": "0.2", "x-build-id": "bvtamKArmccatytbg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/eszetael_lab~google-sheets-import-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-eszetael_lab-google-sheets-import-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/eszetael_lab~google-sheets-import-export/runs": { "post": { "operationId": "runs-sync-eszetael_lab-google-sheets-import-export", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/eszetael_lab~google-sheets-import-export/run-sync": { "post": { "operationId": "run-sync-eszetael_lab-google-sheets-import-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "spreadsheetId", "range", "serviceAccountJson" ], "properties": { "mode": { "title": "Mode", "enum": [ "import", "export" ], "type": "string", "description": "import = read a sheet range into the dataset. export = write rows to a sheet.", "default": "import" }, "spreadsheetId": { "title": "Spreadsheet ID", "type": "string", "description": "The ID from the sheet URL: docs.google.com/spreadsheets/d//edit" }, "range": { "title": "Range (A1 notation)", "type": "string", "description": "e.g. 'Sheet1!A:Z' to import a whole area, or 'Sheet1!A1' as the export anchor." }, "serviceAccountJson": { "title": "Google service account key (JSON)", "type": "object", "description": "Paste the full JSON key of a Google Cloud service account. Create it in GCP → IAM → Service Accounts → Keys, enable the Google Sheets API, and SHARE the spreadsheet with the account's email (client_email). Stored as a secret." }, "firstRowAsHeader": { "title": "First row as header (import)", "type": "boolean", "description": "Import: use row 1 as field names. Off = columns become A, B, C…", "default": true }, "data": { "title": "Data to write (export)", "type": "array", "description": "Export: rows to write — array of objects (keys become the header) or array of arrays." }, "sourceDatasetId": { "title": "Source dataset ID (export)", "type": "string", "description": "Export alternative to 'data': pull rows from an existing Apify dataset." }, "columns": { "title": "Column order (export)", "type": "array", "description": "Optional explicit column order for object rows. Default = order first seen.", "items": { "type": "string" } }, "append": { "title": "Append (export)", "type": "boolean", "description": "Export: append after existing rows instead of overwriting the range.", "default": false }, "includeHeader": { "title": "Write header row (export)", "type": "boolean", "description": "Export: write a header row of column names above the data (for object rows).", "default": true }, "maxItems": { "title": "Max items", "type": "integer", "description": "Cap on rows imported/exported (0 = up to the safety limit of 50000).", "default": 10000 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```