# Instagram Data Scraper (`seashell_knighthood/instagram-scraper-updated`) Actor Scrape public Instagram profile data, posts, captions, hashtags, engagement metrics, and profile information. Export results as JSON, CSV, or Excel. Fast, reliable, and easy to integrate into automation workflows. - **URL**: https://apify.com/seashell\_knighthood/instagram-scraper-updated.md - **Developed by:** [Mahir Sutar](https://apify.com/seashell_knighthood) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 2 total users, 1 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Instagram Scraper โ€” Crawlee + Playwright Search Instagram by **hashtag** or **keyword**, collect matching accounts, and extract their full profile info including **bio, followers, website, email, and more**. --- ### ๐Ÿ“ Project Structure ```` instagram-scraper/ โ”œโ”€โ”€ src/ โ”‚ โ”œโ”€โ”€ main.js โ† Entry point (run this) โ”‚ โ”œโ”€โ”€ config.js โ† โœ๏ธ Edit hashtags, keywords & settings here โ”‚ โ”œโ”€โ”€ routes.js โ† Page handlers (hashtag / search / profile) โ”‚ โ”œโ”€โ”€ parser.js โ† Profile data extractor โ”‚ โ”œโ”€โ”€ cookieLoader.js โ† Reads cookies.json โ”‚ โ””โ”€โ”€ exporter.js โ† Saves JSON + CSV output โ”œโ”€โ”€ cookies.json โ† โœ๏ธ Paste your Instagram cookies here โ”œโ”€โ”€ cookies.example.json โ† Format reference โ”œโ”€โ”€ output/ โ† Created automatically โ”‚ โ”œโ”€โ”€ results.json โ”‚ โ”œโ”€โ”€ results.csv โ”‚ โ””โ”€โ”€ summary.txt โ””โ”€โ”€ package.json ```` --- ### ๐Ÿš€ Quick Start #### 1. Install dependencies ```bash npm install npx playwright install chromium ```` #### 2. Configure what to scrape Edit **`src/config.js`**: ```js hashtags: ['#photography', '#travel'], // hashtags to search keywords: ['digital art', 'AI tools'], // keywords to search maxAccountsPerSource: 50, // accounts to collect per source ``` #### 3. Add your cookies (recommended) Instagram blocks unauthenticated scrapers aggressively. Using your account's cookies dramatically improves results. **How to get cookies (Chrome):** 1. Install the [EditThisCookie](https://chrome.google.com/webstore/detail/editthiscookie/) extension 2. Log in to Instagram in Chrome 3. Click EditThisCookie โ†’ Export (copies JSON to clipboard) 4. Paste into `cookies.json` **Or use the Cookie-Editor extension** โ€” export as JSON and paste into `cookies.json`. The minimum cookies needed are: `sessionid`, `csrftoken`, `ds_user_id` #### 4. Run ```bash npm start ``` *** ### ๐Ÿ“Š Output Results are saved to the `output/` folder: | File | Description | |------|-------------| | `results.json` | Full data, all fields | | `results.csv` | Spreadsheet-friendly | | `summary.txt` | Count per source | #### Fields collected per account | Field | Description | |-------|-------------| | `username` | Instagram handle | | `fullName` | Display name | | `bio` | Full biography text | | `website` | Bio website link | | `email` | Email extracted from bio | | `phone` | Phone from bio/business profile | | `followersCount` | Follower count | | `followingCount` | Following count | | `postsCount` | Number of posts | | `category` | Business category (if set) | | `isVerified` | Blue tick | | `isPrivate` | Private account flag | | `externalUrl` | Bio link | | `profileUrl` | Direct Instagram URL | | `source` | Which hashtag/keyword found this account | | `scrapedAt` | Timestamp | *** ### โš™๏ธ Configuration Options (`src/config.js`) | Setting | Default | Description | |---------|---------|-------------| | `hashtags` | `['#photography']` | Hashtags to scrape | | `keywords` | `['digital art']` | Keywords to search | | `maxAccountsPerSource` | `50` | Accounts per hashtag/keyword | | `maxPostsToScan` | `30` | Posts to check per hashtag page | | `maxRequests` | `500` | Hard cap on total requests | | `maxConcurrency` | `2` | Parallel browser tabs | | `headless` | `true` | Run without visible browser | | `delayMs` | `2000` | Base delay between requests (ms) | *** ### โš ๏ธ Tips & Troubleshooting - **Always use cookies** โ€” Instagram requires login for most data - **Keep concurrency low** (1โ€“2) to avoid rate limiting - **Check `output/debug-hashtag-*.png`** if a hashtag returns no results โ€” it shows what the browser saw - Crawlee stores intermediate data in `storage/` โ€” delete it with `npm run clean` between runs - Instagram frequently updates its page structure; the parser uses multiple fallback strategies *** ### ๐Ÿงช Test a single profile You can quickly test the profile parser by adding a profile URL directly: ```js // In src/main.js, add to startUrls: { url: 'https://www.instagram.com/natgeo/', label: 'PROFILE', userData: { source: 'manual-test' }, } ``` *** ### ๐Ÿ“ Legal This tool is for **personal research and educational use only**. Scraping Instagram may violate their [Terms of Service](https://help.instagram.com/581066165581870). Use responsibly and respect rate limits. ## Actor input object example ```json {} ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("seashell_knighthood/instagram-scraper-updated").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("seashell_knighthood/instagram-scraper-updated").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call seashell_knighthood/instagram-scraper-updated --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seashell_knighthood/instagram-scraper-updated", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Data Scraper", "description": "Scrape public Instagram profile data, posts, captions, hashtags, engagement metrics, and profile information. Export results as JSON, CSV, or Excel. Fast, reliable, and easy to integrate into automation workflows.", "version": "0.0", "x-build-id": "wxSja669zr4Qbf0Na" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seashell_knighthood~instagram-scraper-updated/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seashell_knighthood-instagram-scraper-updated", "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/seashell_knighthood~instagram-scraper-updated/runs": { "post": { "operationId": "runs-sync-seashell_knighthood-instagram-scraper-updated", "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/seashell_knighthood~instagram-scraper-updated/run-sync": { "post": { "operationId": "run-sync-seashell_knighthood-instagram-scraper-updated", "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", "properties": {} }, "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 } } } } } } } } } } ```