# Fast Instagram Reel Scraper (`scrapecraze/instagram-reel-scraper`) Actor Instagram Reel Scraper extracts reel data including captions, hashtags, views, likes, comments, audio details, publish dates, and video URLs. Ideal for influencer research, competitor analysis, content strategy, trend monitoring, and social media analytics. - **URL**: https://apify.com/scrapecraze/instagram-reel-scraper.md - **Developed by:** [ScrapeCraze](https://apify.com/scrapecraze) (community) - **Categories:** Social media, Videos, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Reel Scraper ⚡ Scrolling through Instagram Reels one by one is slow and doesn’t scale. **Instagram Reel Scraper** pulls Reels and Posts data by username so you can collect metadata fast for analysis, reporting, or outreach. It’s an Instagram reel scraper tool and Instagram reels video downloader built for teams who need Instagram reel data scraper results without manual copy-paste. It’s a great fit for marketers, data analysts, and researchers who want structured output from public Instagram content at speed—get up to the first **max_posts** results in a single run. --- ### See the Data: Sample Output Here’s a real record from a single run: ```json { "id": "12345678901234567", "type": "Video", "shortCode": "AbCDefGhIjK", "caption": "New drops today! #fitness #reels @brand", "hashtags": ["fitness", "reels"], "mentions": ["brand"], "url": "https://www.instagram.com/p/AbCDefGhIjK/", "commentsCount": 24, "dimensionsHeight": 1920, "dimensionsWidth": 1080, "images": [], "videoUrl": "https://video.example.com/video.mp4", "likesCount": 1530, "timestamp": "2026-05-20T14:22:11.000Z", "ownerFullName": "Jane Doe", "ownerUsername": "janedoe", "ownerId": "99887766554433", "isPinned": false, "productType": null, "videoDuration": 37.5, "inputUrl": "https://www.instagram.com/janedoe", "firstComment": "Amazing 🔥", "latestComments": [ { "id": "55566677788899", "text": "Amazing 🔥", "ownerUsername": "someone_else", "ownerProfilePicUrl": "https://example.com/pic.jpg", "timestamp": "2026-05-20T14:30:05.000Z", "repliesCount": 0, "replies": [], "likesCount": 3, "owner": { "id": "33322211100099", "is_verified": false, "profile_pic_url": "https://example.com/pic2.jpg", "username": "someone_else" } } ], "displayUrl": null, "audioUrl": null, "alt": "New drops today!", "videoViewCount": 120034, "videoPlayCount": 98002, "childPosts": [], "taggedUsers": [ { "full_name": "Brand Partner", "id": "11223344556677", "is_verified": false, "profile_pic_url": "https://example.com/partner.jpg", "username": "brandpartner" } ], "musicInfo": { "artist_name": "Original Artist", "song_name": "Original audio", "uses_original_audio": true, "should_mute_audio": false, "should_mute_audio_reason": "", "audio_id": "audio_123" }, "isCommentsDisabled": false, "status": "success", "error_message": null } ```` | Field | Type | What It Tells You | |---|---|---| | `id` | string | Stable identifier for the media item you scraped | | `type` | string | Media type classification (e.g., Video, Image, Carousel) | | `shortCode` | string | Short code used to construct or reference the post URL | | `caption` | string | The post’s caption text (useful for content analysis and tagging) | | `hashtags` | array | Hashtags extracted from the caption for clustering and reporting | | `mentions` | array | Mentioned usernames parsed from the caption | | `url` | string | Canonical Instagram URL for the scraped post/reel | | `commentsCount` | number | How much discussion the post has attracted | | `likesCount` | number | Engagement level for likes | | `timestamp` | string | UTC timestamp derived from `taken_at`, useful for time-series analysis | | `ownerFullName` | string | Display name of the account that posted the media | | `ownerUsername` | string | The Instagram username associated with the media | | `videoUrl` | string | null | Direct video URL when available (handy for downstream processing) | | `firstComment` | string | null | The first comment text found (when comment data is present) | | `latestComments` | array | A list of comment objects captured from the response | | `musicInfo` | object | Extracted music metadata when the media includes music information | | `status` | string | Indicates the record succeeded in producing output | | `error_message` | string | null | Populated when an error occurs (otherwise `null`) | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "username": "cristiano", "max_posts": 10 } ``` | Parameter | Required | What It Does | |---|---|---| | `username` | ✅ | The Instagram username to scrape without the `@` symbol (for example, `cristiano`) | | `max_posts` | ⬜ | Maximum number of reels to scrape (minimum 1). Default is `10`. | *** ### What It Does Instagram Reel Scraper collects structured media data from a given public Instagram profile by username. #### Scrape Reels and Posts metadata by username You provide a single `username`, and the actor gathers media items up to your `max_posts` limit. The output includes engagement stats like likes and comments, plus core content fields such as caption, hashtags, and mentions. #### Produces clean, integration-ready JSON The dataset record includes practical fields like `url`, `timestamp`, `ownerUsername`, and media-specific assets such as `videoUrl` when available. It also extracts `taggedUsers` and `musicInfo` so you can analyze content themes without extra parsing. #### Includes hashtags and mentions from captions To help you quickly segment and understand content, it extracts hashtags and mentions directly from the `caption`. This is useful for building trend reports, mapping brand collaborations, or enriching datasets for downstream analytics. #### Captures comments details when available If comment data is present in the scraped content, it stores `firstComment` and a `latestComments` array with comment-level information. Each comment object includes `text`, `timestamp`, `ownerUsername`, and an `owner` sub-object with basic profile fields. #### Built-in proxy support for reliable scraping The actor supports proxy configuration via `proxyConfiguration` in the input. It uses proxy routing to keep requests reliable during larger runs and repeated page access. #### Handles missing data safely When specific content isn’t available for a media item (for example, images or certain music metadata), the related fields can be `null` or empty (like `images: []`). This keeps each record shaped for analysis without forcing you to clean up inconsistent schemas manually. Overall, Instagram reel scraper results land as structured records you can export and use immediately for reporting or research. *** ### Why Instagram Reel Scraper? There are plenty of ways to pull data from Instagram—here’s why Instagram Reel Scraper stands out. #### Built specifically for reel and post data extraction This actor is designed to scrape Reels and Posts data “including comments, likes, and more by username.” That focus makes it easier to build reel-focused analytics workflows without stitching together multiple tools. #### Writes each successful result as it goes Results are pushed to the dataset after each successful scrape. That means you don’t have to wait for a whole run to finish to start exporting or analyzing partial outputs. #### Resilient request flow with clear failure handling The actor includes retry logic when fetching post page data and returns `None` when it can’t produce output for a given URL. Your dataset export stays consistent, and you can re-run for missing items by adjusting inputs like `max_posts`. *** ### Real-World Use Cases Here's how different teams put Instagram Reel Scraper to work: **Marketing Analysts**\ A marketing analyst monitors content performance across a set of creator accounts. They run Instagram reel export jobs for each username, then analyze engagement patterns using `likesCount`, `commentsCount`, and `timestamp` from the dataset. The hashtags and mentions extracted from `caption` help them identify repeat themes and collaborations. **Sales Prospecting Teams**\ A sales development team wants to find who’s getting attention and who might have collaborators. They scrape multiple public profiles, then use `taggedUsers` and `musicInfo` to build a shortlist of accounts producing standout reel content. Exporting the dataset lets them enrich CRM fields without manual browsing. **Freelance Researchers**\ A researcher studying creator ecosystems needs a repeatable way to collect public Instagram reel data scraper outputs for longitudinal research. They run the actor with a chosen `max_posts`, export to JSON or CSV, and track changes in captions, mentions, and comment activity over time using the `timestamp` field. **Agencies Running Competitive Audits**\ An agency doing influencer and content audits needs consistent metadata across accounts. They use Instagram reel URL extractor output (`url`, `shortCode`, `displayUrl`) and engagement metrics to compare posts quickly, then share a single export file with clients for internal review. **Data Engineers Building Pipelines (Technical)**\ A data engineer wants to automate ingestion into an internal analytics warehouse. They trigger the actor and pull results programmatically via the Apify API, then map the JSON fields (`ownerUsername`, `caption`, `hashtags`, `latestComments`) into their schema for dashboards and notebooks. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify**\ Go to the actor page on [console.apify.com](https://console.apify.com). 2. **Enter your inputs**\ Set `username` (required) and optionally `max_posts` to control how many reels/posts to scrape. 3. **Configure proxy settings (recommended for reliability)**\ In the input, you can use `proxyConfiguration` to enable proxy routing for the run. 4. **Start the run and watch the live log**\ The actor logs progress as it processes each media item. 5. **Open the Dataset tab to see results immediately**\ Each successful record is pushed into the dataset during the run. 6. **Export your data**\ Download from the Apify dashboard as JSON, CSV, or Excel. 7. **Refine and re-run if needed**\ If you need deeper coverage, increase `max_posts` and run again for the same or additional usernames. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Instagram Reel Scraper fits directly into your existing workflow. You can export your dataset from the Apify dashboard as **JSON, CSV, or Excel** from the dataset tab. For analysis, this makes Instagram reel scraping software outputs easy to load into spreadsheets, notebooks, or reporting tools. For automation, you can use **Apify API** to access results programmatically, and integrate with downstream systems using **webhooks** or no-code automation via **Zapier / Make**. *** ### Pricing Instagram Reel Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. The free tier includes **$5 platform credits on sign-up**, which is enough for several real test runs. For heavier workloads, you’ll pay as you go based on Apify Actor compute units (CU), with subscription plans available for larger needs. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Platform rate limits | Built-in pacing and resilient request handling | | Proxy support | You can provide `proxyConfiguration` for more reliable runs | | Temporary fetch failures | Post page fetching uses up to 3 attempts | | Partial run recovery | Each successful scrape is pushed to the dataset during the loop | | Missing fields | Fields may be `null` or empty when the source data doesn’t contain that information | | Scale safety | The actor uses a safety limit on pagination while collecting post URLs | **Limitations:** The actor works on publicly accessible Instagram profile content and returns `None` for items it can’t extract. It won’t access private or login-gated content, so results depend on what’s publicly available for the target username. For enterprise-scale needs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify offers a free tier with platform credits on sign-up, which is typically enough to validate your workflow with a few real test runs. #### Do I need to log in or create an account on Instagram? No. This Instagram reel scraper tool is intended for public Instagram content, so you don’t need to provide an Instagram login to start. #### How accurate is the extracted data? Accuracy is based on what’s present in the public page data the actor retrieves. Fields like `caption`, engagement counts, hashtags, mentions, and `musicInfo` are extracted from the available structured content. #### How many results can I get per run? You control that with `max_posts`. The input schema defines it as “Maximum reels” with a default of `10` and a minimum of `1`. #### How fresh is the data? The data freshness matches the time when the actor runs. If you re-run later, you’ll capture updated captions, engagement, and comments that are publicly visible at that moment. #### Is this legal? Does it comply with GDPR / CCPA? You should treat this as a tool for extracting **publicly available data**. Whether your use complies with GDPR, CCPA, Instagram’s Terms of Service, and applicable regulations is your responsibility. #### Can I export to Google Sheets or Excel? Yes. You can export from the Apify dataset tab as JSON, CSV, or Excel, then import into Google Sheets or any compatible system. #### Can I schedule this to run automatically? Yes. On Apify you can set the actor to run on a schedule so it refreshes your Instagram reel export outputs automatically. #### Can I access results via the API? Yes. You can pull results programmatically via the Apify API, which is useful for building pipelines that ingest Instagram reels metadata scraper outputs into your systems. #### What happens when the actor encounters an error? For a given media item, the actor may return `None` if it can’t extract data after its attempts. Successful results are still pushed to the dataset during the run, so you keep what was already collected. *** ### Get Help & Use Responsibly Got a question about Instagram Reel Scraper or a feature you'd like added? Reach out at . We welcome requests like supporting additional fields in the export or improving how reel-related metadata is represented, and we actively maintain the actor based on user feedback. *** **This actor collects publicly available data**. It does not access private accounts, login-gated pages, or password-protected content. It’s your responsibility to comply with GDPR, CCPA, platform Terms of Service, and applicable laws when using or storing the data. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `username` (type: `string`): The Instagram username to scrape without the @ symbol (e.g., cristiano) ## `max_posts` (type: `integer`): Maximum number of reels to scrape ## Actor input object example ```json { "username": "cristiano", "max_posts": 10 } ``` # 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 = { "username": "cristiano" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapecraze/instagram-reel-scraper").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 = { "username": "cristiano" } # Run the Actor and wait for it to finish run = client.actor("scrapecraze/instagram-reel-scraper").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 '{ "username": "cristiano" }' | apify call scrapecraze/instagram-reel-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapecraze/instagram-reel-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fast Instagram Reel Scraper", "description": "Instagram Reel Scraper extracts reel data including captions, hashtags, views, likes, comments, audio details, publish dates, and video URLs. Ideal for influencer research, competitor analysis, content strategy, trend monitoring, and social media analytics.", "version": "1.0", "x-build-id": "4gMdWyE3Ehmlwei1m" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapecraze~instagram-reel-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapecraze-instagram-reel-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapecraze~instagram-reel-scraper/runs": { "post": { "operationId": "runs-sync-scrapecraze-instagram-reel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapecraze~instagram-reel-scraper/run-sync": { "post": { "operationId": "run-sync-scrapecraze-instagram-reel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "Instagram Username", "type": "string", "description": "The Instagram username to scrape without the @ symbol (e.g., cristiano)" }, "max_posts": { "title": "Maximum reels", "minimum": 1, "type": "integer", "description": "Maximum number of reels to scrape", "default": 10 } } }, "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 } } } } } } } } } } ```