# IMDB 🎞️ Extractor (`jupri/imdb`) Actor πŸ’« Scrape IMDb.com - **URL**: https://apify.com/jupri/imdb.md - **Developed by:** [cat](https://apify.com/jupri) (community) - **Categories:** Videos, Social media - **Stats:** 19 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $35.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Welcome to IMDB Scraper ![dont be sad readme is here](https://raw.githubusercontent.com/JupriGH/resources/main/cats/catframe.png) ### About IMDB.com **IMDb** (an [initialism](https://en.wikipedia.org/wiki/Initialism "Initialism") for **Internet Movie Database**)[[2]](https://en.wikipedia.org/wiki/IMDb#cite_note-2) is an [online database](https://en.wikipedia.org/wiki/Online_database "Online database") of information related to films, television series, podcasts, home videos, video games, and streaming content online – including cast, production crew and personal biographies, plot summaries, trivia, ratings, and fan and critical reviews. IMDb began as a fan-operated movie database on the [Usenet](https://en.wikipedia.org/wiki/Usenet "Usenet") group "rec.arts.movies" in 1990, and moved to the Web in 1993. Since 1998, it has been owned and operated by **IMDb.com, Inc.**, a subsidiary of [Amazon](https://en.wikipedia.org/wiki/Amazon_(company) "Amazon (company)"). The site's message boards were disabled in February 2017. As of 2019, IMDb was the 52nd most visited website on the Internet, as ranked by [Alexa](https://en.wikipedia.org/wiki/Alexa_Internet "Alexa Internet").[[3]](https://en.wikipedia.org/wiki/IMDb#cite_note-3) As of March 2022, the database contained some 10.1 million titles (including television episodes), 11.5 million person records, and 83 million registered users.[[4]](https://en.wikipedia.org/wiki/IMDb#cite_note-stats_2022.12-4) ### πŸ‚ About This Actor Scrape movie data from **IMDb.com** ### πŸ‚ TUTORIAL #### 🍿 Parameters | Input| Type | Description | |-|-|-| | `query` | ***string array*** | Query, Search Terms or URL | | `limit` | ***integer*** | Number of results (per-query)| #### 🍿 Basic Usage Search Titles ```yaml { "query": "Sponge Bob", "limit": 10 } ```` #### 🍿 Advanced Usage ##### IMDb Query Language (`IMDQL`) ```html [ | # | @ ] [ | | | ] [ /
] ``` ##### Possible `QUERY` values | Format | Example | Description | |-|-|-| | **<*KEYWORDS*>** | `search terms` | ***Search Anything*** | | **<*TITLE\_ID*>** | `tt01234456` | ***Movie Data*** | | `/info` | `tt01234456/info` | Movie info | `/alias` | `tt01234456/alias` | Movie aliases (AKA) | `/plots` | `tt01234456/plots` | Movie plots | `/images` | `tt01234456/images` | Movie images | `/videos` | `tt01234456/videos` | Movie videos | `/clips` | `tt01234456/clips` | Movie clips | `/trailers` | `tt01234456/trailers` | Movie trailers | `/external-trailers` | `tt01234456/external-trailers` | Movie trailers (external) | `/soundtracks` | `tt01234456/soundtracks` | Movie soundtracks | `/episodes` | `tt01234456/episodes` | Movie episodes | `/reviews` | `tt01234456/reviews` | Movie reviews | `/similar` | `tt01234456/similar` | Similar movies | `/faqs` | `tt01234456/faqs` | Movie faqs | `/crews` | `tt01234456/crews` | Movie crews | `/cast` | `tt01234456/cast` | Movie casts (*actors & actress*) | `/actor` | `tt01234456/actor` | Movie actors | `/actress` | `tt01234456/actress` | Movie actress | `/credits` | `tt01234456/credits` | Movie full credits | `/uncredits` | `tt01234456/uncredits` | Movie credits un-credited | `/quotes` | `tt01234456/quotes` | Movie quotes | `/awards` | `tt01234456/awards` | Movie awards | `/trivia` | `tt01234456/trivia` | Movie trivia | `/goofs` | `tt01234456/goofs` | Related goofs | `/news` | `tt01234456/news` | Related news | **https:<*URL*>** | `https://www.imdb.com/...` | ***Start URL*** | ### πŸ‚ INPUT EXAMPLES #### 🍿 Example #1: Search Search Titles ```yaml { "query": "Sponge Bob", "limit": 10 } ``` ### πŸ‚ OUTPUT SAMPLES # Actor input Schema ## `query` (type: `array`): Search Terms ## `limit` (type: `integer`): Number of results ## `filters.sort` (type: `string`): No description ## `filters.order` (type: `string`): No description ## `filters.types` (type: `array`): No description ## `filters.genre` (type: `array`): No description ## `filters.sound` (type: `array`): No description ## `dev_proxy_config` (type: `object`): πŸ’‘ Supported protocol:

HTTP(S), SOCKS5
{http|socks5}://{user:pass}@{hostname|ip-address}:port

Example: socks5://example.com:9000 ## `dev_custom_headers` (type: `array`): πŸ’‘ Additional HTTP Headers ## `dev_custom_cookies` (type: `array`): πŸ’‘ Additional HTTP Cookies ## `dev_transform_fields` (type: `array`): πŸ’‘ Transform the resulting output. Select only needed fields.

For nested object use DOT. For example: 
address.streetAddress

For nested array use NUMBER (index of array element starting from index=0). For example: 
images.0.url
## `dev_dataset_name` (type: `string`): πŸ’‘ Save results into custom named Dataset, use mask to customize dataset name

{ACTOR} = actor name
{DATE} = date (YYYYMMDD)
{TIME} = time (HHMMSS)

This masks can be used to autogenerate Dataset Name.

example: data-{DATE}
Depending on today date the dataset name will be: data-20230603

default: data-{ACTOR}-{DATE}-{TIME} ## `dev_dataset_clear` (type: `boolean`): Clear Dataset before insert/update. ## `dev_no_strip` (type: `boolean`): πŸ’‘ Keep/Save empty values (NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING) ## Actor input object example ```json { "limit": 5 } ``` # 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 = { "limit": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("jupri/imdb").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "limit": 5 } # Run the Actor and wait for it to finish run = client.actor("jupri/imdb").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "limit": 5 }' | apify call jupri/imdb --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jupri/imdb", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "IMDB 🎞️ Extractor", "description": "πŸ’« Scrape IMDb.com", "version": "0.0", "x-build-id": "36VeH8QwiUH9ophin" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jupri~imdb/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jupri-imdb", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/jupri~imdb/runs": { "post": { "operationId": "runs-sync-jupri-imdb", "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/jupri~imdb/run-sync": { "post": { "operationId": "run-sync-jupri-imdb", "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": { "query": { "title": "❓ Query", "type": "array", "description": "Search Terms", "items": { "type": "string" } }, "limit": { "title": "♾️ Limit", "type": "integer", "description": "Number of results" }, "filters.sort": { "title": "❓ Sorting", "enum": [ "BOX_OFFICE_GROSS_DOMESTIC", "POPULARITY", "RANKING", "RELEASE_DATE", "RUNTIME", "TITLE_REGIONAL", "USER_RATING", "USER_RATING_COUNT", "YEAR" ], "type": "string", "description": "" }, "filters.order": { "title": "", "enum": [ "ASC", "DESC" ], "type": "string", "description": "" }, "filters.types": { "title": "❓ Type", "type": "array", "description": "", "items": { "type": "string", "enum": [ "movie", "tvSeries", "short", "tvEpisode", "tvMiniSeries", "tvMovie", "tvSpecial", "tvShort", "videoGame", "video", "musicVideo", "podcastSeries", "podcastEpisode" ], "enumTitles": [ "Movie", "TV Series", "Short", "TV Episode", "TV Mini Series", "TV Movie", "TV Special", "TV Short", "Video Game", "Video", "Music Video", "Podcast Series", "Podcast Episode" ] } }, "filters.genre": { "title": "❓ Genre", "type": "array", "description": "", "items": { "type": "string", "enum": [ "Action", "Talk-Show", "News", "Game-Show", "Crime", "Adventure", "Animation", "Biography", "Comedy", "Documentary", "Drama", "Family", "Fantasy", "Film-Noir", "History", "Horror", "Music", "Musical", "Mystery", "Reality-TV", "Romance", "Sci-Fi", "Short", "Sport", "Thriller", "War", "Western" ] } }, "filters.sound": { "title": "❓ Sound", "type": "array", "description": "", "items": { "type": "string", "enum": [ "12-Track Digital Sound", "3 Channel Stereo", "4-Track Stereo", "6-Track Stereo", "70 mm 6-Track", "AGA Sound System", "Auro 11.1", "CDS", "Chronophone", "Cinematophone", "Cinephone", "Cinerama 7-Track", "Cinesound", "D-Cinema 48kHz 5.1", "Datasat", "De Forest Phonofilm", "Digitrac Digital Audio System", "Dolby", "Dolby Atmos", "Dolby Digital", "Dolby Digital EX", "Dolby SR", "Dolby Stereo", "Dolby Surround 7.1", "DTS", "DTS 70 mm", "DTS Stereo", "DTS-ES", "IMAX 6-Track", "Kinoplasticon", "LC-Concept Digital Sound", "Matrix Surround", "Mono", "Perspecta Stereo", "Phono-Kinema", "SDDS", "Sensurround", "Silent", "Sonics-DDP", "Sonix", "Stereo", "Ultra Stereo", "Vitaphone" ] } }, "dev_proxy_config": { "title": "🌐 PROXY NETWORKING", "type": "object", "description": "πŸ’‘ Supported protocol:

HTTP(S), SOCKS5
{http|socks5}://{user:pass}@{hostname|ip-address}:port

Example: socks5://example.com:9000" }, "dev_custom_headers": { "title": "πŸ“œ HTTP HEADERS", "type": "array", "description": "πŸ’‘ Additional HTTP Headers", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_custom_cookies": { "title": "🍰 HTTP COOKIES", "type": "array", "description": "πŸ’‘ Additional HTTP Cookies", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_transform_fields": { "title": "♻️ CUSTOM FIELD", "type": "array", "description": "πŸ’‘ Transform the resulting output. Select only needed fields.

For nested object use DOT. For example: 
address.streetAddress

For nested array use NUMBER (index of array element starting from index=0). For example: 
images.0.url
", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_dataset_name": { "title": "πŸ“ CUSTOM STORAGE", "type": "string", "description": "πŸ’‘ Save results into custom named Dataset, use mask to customize dataset name

{ACTOR} = actor name
{DATE} = date (YYYYMMDD)
{TIME} = time (HHMMSS)

This masks can be used to autogenerate Dataset Name.

example: data-{DATE}
Depending on today date the dataset name will be: data-20230603

default: data-{ACTOR}-{DATE}-{TIME}" }, "dev_dataset_clear": { "title": "Clear Storage", "type": "boolean", "description": "Clear Dataset before insert/update." }, "dev_no_strip": { "title": "Disable data cleansing", "type": "boolean", "description": "πŸ’‘ Keep/Save empty values (NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING)" } } }, "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 } } } } } } } } } } ```