# 🎬 IMDB Scraper — Movies, Ratings & Box Office (`nexgendata/imdb-scraper`) Actor Extract movies & TV shows from IMDb — ratings, cast, crew, box office, plot summaries. TMDB, OMDb & JustWatch alternative for streaming apps, recommendation engines and entertainment data pipelines. Pay per title — no API key needed. - **URL**: https://apify.com/nexgendata/imdb-scraper.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Videos, Social media - **Stats:** 10 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## 🎬 IMDb Scraper — Movies, TV, Cast, Ratings, Box Office & Reviews at Scale Extract structured movie + TV data from IMDb — titles, year, runtime, genre, cast, crew, ratings, box-office, plot, reviews, parental guide. A drop-in **alternative to** IMDb's non-commercial datasets, TMDB API, OMDb API, and JustWatch — with full reviews + box-office data and no daily call quota. ### Why IMDb Scraper Beats IMDb Datasets, TMDB, OMDb & JustWatch | Feature | NexGenData IMDb Scraper | IMDb non-commercial datasets | TMDB API | OMDb API | JustWatch | |---|---|---|---|---|---| | Cost | $3 per 1,000 results, pay-per-event | Free but flat-file only | Free + paid tiers | $1+ / month with limits | Partner-only | | Commercial use | Yes | Non-commercial only | With API key | With API key | Partner contract | | Box-office data | Yes (opening, gross, budget) | No | Limited | Limited | No | | Full reviews | Yes | No | User-submitted | No | No | | Cast + crew | Full credits | Yes | Yes | Limited | Limited | | Ratings | IMDb rating + Metacritic + Rotten Tomatoes where shown | IMDb only | TMDB rating | IMDb + Metacritic | Yes | | Parental guide | Yes | No | Limited | No | No | | Bulk export | CSV / JSON / Excel / API | Flat file only | API | API | Partner contract | | Auth | Apify token | None | API key | API key | Partner contract | | Time-to-first-row | < 60 seconds | Download GB-size dumps | Signup | Signup | Sales cycle | Most media analytics + recommendation-engine teams pick this scraper because it is **commercial-use friendly** (unlike the IMDb non-commercial dumps), **broader than** OMDb's title-search response, and **richer than** TMDB's missing box-office numbers. JSON drops straight into your recommendation pipeline. ### What You Get Per title returned, the scraper includes: - **IMDb ID** + canonical IMDb URL - **Title** + original title + year + content type (movie, tv series, short, miniseries, video game) - **Genre** — array of genres - **Runtime** (minutes) + content rating (PG, PG-13, R, etc.) - **Plot summary** + full synopsis where available - **IMDb rating** (1–10) + vote count - **Metacritic score** + Rotten Tomatoes score where shown - **Release date(s)** — worldwide + per-country - **Cast** — array of name + role + actor IMDb ID - **Crew** — director, writer, producer, cinematographer, composer - **Production companies** + countries + languages - **Box office** — opening weekend, domestic gross, worldwide gross, budget - **Reviews** — array of user reviews (author, rating, date, text), configurable depth - **Awards** — wins + nominations summary - **Parental guide** — sex, violence, profanity, alcohol, frightening - **Where to watch** flags where shown - **Photos + posters** — image URLs - **Scrape timestamp** Output streams to a clean Apify dataset — CSV, JSON, Excel, RSS, or API. ### Use Cases - **Streaming services + content acquisition** — build a structured catalog of every title under consideration for licensing - **Recommendation engines** — train collaborative-filtering models on rating + genre + cast vectors - **Media analytics + journalism** — benchmark box-office performance across studios, years, genres - **Trivia + entertainment apps** — power the database behind a movie-trivia mobile app - **Academic research** — film studies, sociology of media, cinematic-language NLP - **Fan sites + verticals** — build a niche horror-genre database with full reviews - **Marketing intelligence** — monitor the review-sentiment swing of a launching title in week one ### Quick Start ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run_input = { "searchQueries": ["Christopher Nolan films"], "maxResults": 50, "includeReviews": True, "maxReviewsPerTitle": 5, } run = client.actor("nexgendata/imdb-scraper").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item.get("title"), item.get("year"), item.get("imdbRating")) ```` ### Pricing Pay-per-event. $3 per 1,000 results plus a small Actor Start fee. No monthly subscription. Compare to OMDb at $1+ per month per limit-tier or TMDB's paid plans — this actor stays flat-cost regardless of volume. ### Related NexGenData Actors | Use case | Actor | |----------|-------| | YouTube video metadata + download | [YT-DLP Video Tools](https://apify.com/nexgendata/yt-dlp-video-tools) | | Detect YouTube channel monetization signal | [YouTube Channel Monetization Detector](https://apify.com/nexgendata/youtube-channel-monetization-detector) | | Wikipedia structured-knowledge scraper | [Wikipedia Scraper](https://apify.com/nexgendata/wikipedia-scraper) | | Hacker News stories + comments scraper | [Hacker News Scraper](https://apify.com/nexgendata/hacker-news-scraper) | | Reddit subreddit + post trend tracker | [Reddit Subreddit Trends](https://apify.com/nexgendata/reddit-subreddit-trends) | | AI sentiment analysis on reviews | [AI Sentiment Analyzer](https://apify.com/nexgendata/ai-sentiment-analyzer) | | Google Scholar paper search | [Google Scholar Scraper](https://apify.com/nexgendata/google-scholar-scraper) | | Bilibili Chinese video search | [Bilibili Video Search](https://apify.com/nexgendata/bilibili-video-search) | ### FAQ **Is this legal?** This actor reads publicly displayed IMDb pages. IMDb publishes non-commercial flat-file datasets for free; commercial use of those is prohibited. This actor reads the live HTML the same way a browser would and is suitable for commercial use under your own jurisdiction's rules — we recommend checking IMDb's terms for your use case. **How fresh is the data?** Live on every run. Each invocation pulls the current IMDb page at runtime — critical for box-office numbers that change weekly. **Does it include reviews?** Yes — set `includeReviews: true` and `maxReviewsPerTitle: N` to attach up to N user reviews per title with author / rating / date / full text. **Does it include cast and crew?** Yes — every result includes the full top-billed cast and key crew with their IMDb IDs so you can resolve actor-graph relationships. **TV series support?** Yes — series + season + episode metadata are all supported. **Can I schedule it weekly?** Yes — native Apify scheduling. Common pattern: refresh every Friday for box-office update. **Output formats?** JSON by default; CSV / Excel / RSS via the dataset API. ### About NexGenData NexGenData publishes 260+ buyer-intent actors covering SEC filings, YC alumni, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, and more. All pay-per-result. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b *** ### How NexGenData Pricing Works Every NexGenData actor uses **pay-per-event** pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills. - **Actor Start:** a single-event charge each time you spin the actor up (scaled to memory size) - **Result:** charged per item written to the default dataset - **No charge** for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform If you only need the data once a quarter, you only pay once a quarter. If you scale to millions of records, the unit cost stays the same. ### Apify Platform Bonus New to Apify? Sign up with the NexGenData [referral link](https://www.apify.com/?fpr=2ayu9b) — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet. ### Integration Surface Every actor in the NexGenData catalog can be triggered from: - **Apify console** — point-and-click run - **Apify API** — REST + webhooks - **Apify Python / JS SDKs** — programmatic batch - **Zapier, Make.com, n8n** — official integrations - **MCP** — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents - **Schedules** — built-in cron for daily / weekly / monthly runs - **Webhooks** — POST results to any HTTPS endpoint on dataset write ### Support NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version. Home: [thenextgennexus.com](https://thenextgennexus.com) Full catalog: [apify.com/nexgendata](https://apify.com/nexgendata?fpr=2ayu9b) # Actor input Schema ## `searchQuery` (type: `string`): Movie or TV show to search for ## `maxResults` (type: `integer`): Maximum number of results to extract ## Actor input object example ```json { "searchQuery": "Inception", "maxResults": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/imdb-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 = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/imdb-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 '{}' | apify call nexgendata/imdb-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/imdb-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🎬 IMDB Scraper — Movies, Ratings & Box Office", "description": "Extract movies & TV shows from IMDb — ratings, cast, crew, box office, plot summaries. TMDB, OMDb & JustWatch alternative for streaming apps, recommendation engines and entertainment data pipelines. Pay per title — no API key needed.", "version": "0.0", "x-build-id": "hSmpmalu8BsHhIiaj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~imdb-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-imdb-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~imdb-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-imdb-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~imdb-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-imdb-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Movie or TV show to search for", "default": "Inception" }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 25, "type": "integer", "description": "Maximum number of results to extract", "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 } } } } } } } } } } ```