# Roku Discovery Parser Spider (`getdataforme/roku-discovery-parser-spider`) Actor The Roku Discovery Parser Spider is a versatile tool for scraping and parsing content from Roku’s platform, ideal for market research, competitive analysis, and content aggregation.... - **URL**: https://apify.com/getdataforme/roku-discovery-parser-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 --- ## Roku Discovery Parser Spider ### Introduction The Roku Discovery Parser Spider is a powerful tool designed to scrape and parse data from Roku's content discovery platform. By leveraging this actor, users can efficiently gather information on various TV shows and movies based on specified keywords. This tool is invaluable for market research, competitive analysis, and content aggregation. ### Features - **Keyword-Based Scraping**: Customize searches with specific keywords to target relevant content. - **High Data Quality**: Ensures reliable and accurate data extraction from Roku's platform. - **Flexible Item Limit**: Set a maximum number of items per run or allow unlimited scraping. - **Efficient Performance**: Optimized for speed and resource management during data collection. - **Comprehensive Output**: Provides detailed information including show names, images, links, and release dates. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|-----------------------------| | Keywords | array | No | The keywords for the spider. | `["bridgerton", "thriller"]`| | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Keywords": ["romantic"], "item_limit": 5 } ```` #### Output JSON ```json [ { "keyword": "romantic", "page": 1, "show_name": "Romantic Killer", "show_image": "https://images.sr.roku.com/idType/roku/context/global/id/0364027a2f2452278af913e72f088a92/images/gracenote/assets/p22991689_b_h8_aa.jpg", "details_link": "https://api2.sr.roku.com/homescreen/v2/plugins/collections/contentdetails?tpl_id=0364027a2f2452278af913e72f088a92&tpl_idType=roku", "released_date": "2022-2022", "actor_id": "vVamxaP1zjNpEEKFf", "run_id": "SPhs7GRTG7m2h8rwI" }, { "keyword": "romantic", "page": 1, "show_name": "Romantic Doctor", "show_image": "https://images.sr.roku.com/idType/roku/context/global/id/c63abbcb357a5c6da0446e6f6f8dc2b6/images/gracenote/assets/p13471939_b_h8_ae.jpg", "details_link": "https://api2.sr.roku.com/homescreen/v2/plugins/collections/contentdetails?tpl_id=c63abbcb357a5c6da0446e6f6f8dc2b6&tpl_idType=roku", "released_date": "2016-2023", "actor_id": "vVamxaP1zjNpEEKFf", "run_id": "SPhs7GRTG7m2h8rwI" }, { "keyword": "romantic", "page": 1, "show_name": "The Romantics and Us with Simon Schama", "show_image": "https://images.sr.roku.com/idType/roku/context/global/id/9bbf328ad511524dba8bd5b5c2f6bd83/images/gracenote/assets/p18723898_b_h10_ab.jpg", "details_link": "https://api2.sr.roku.com/homescreen/v2/plugins/collections/contentdetails?tpl_id=9bbf328ad511524dba8bd5b5c2f6bd83&tpl_idType=roku", "released_date": "2020-2020", "actor_id": "vVamxaP1zjNpEEKFf", "run_id": "SPhs7GRTG7m2h8rwI" } ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into trending content categories. - **Competitive Intelligence**: Monitor competitors' offerings on Roku. - **Price Monitoring**: Track pricing trends for various shows and movies. - **Content Aggregation**: Compile comprehensive lists of available content. - **Academic Research**: Support studies in media, entertainment, or digital marketing. - **Business Automation**: Automate data collection processes for strategic planning. ### Installation and Usage 1. Search for "Roku Discovery Parser Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output is a JSON array where each object contains: - `keyword`: The search keyword used. - `page`: Page number of the results. - `show_name`: Name of the TV show or movie. - `show_image`: URL to the image of the content. - `details_link`: Link to detailed information about the content. - `released_date`: Release date of the content. - `actor_id`: Unique identifier for the actor run. - `run_id`: Unique identifier for the specific run. ### Error Handling The actor is designed to handle common errors gracefully. If an error occurs, it will be logged in the Apify console with details on what went wrong and potential steps for resolution. Users are encouraged to review logs for troubleshooting. ### Rate Limiting and Best Practices To ensure optimal performance and avoid being blocked by Roku's servers: - Respect rate limits by spacing out requests. - Use appropriate headers and user-agent strings. - Monitor the actor's performance and adjust settings as needed. ### Limitations and Considerations - The actor relies on publicly available data, which may change over time. - Ensure compliance with Roku's terms of service when using this tool. - Performance may vary based on network conditions and server response times. # Actor input Schema ## `Keywords` (type: `array`): The keywords for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "Keywords": [ "bridgerton", "thriller", "comedy", "romantic" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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("getdataforme/roku-discovery-parser-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/roku-discovery-parser-spider").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 '{}' | apify call getdataforme/roku-discovery-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/roku-discovery-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Roku Discovery Parser Spider", "description": "The Roku Discovery Parser Spider is a versatile tool for scraping and parsing content from Roku’s platform, ideal for market research, competitive analysis, and content aggregation....", "version": "0.0", "x-build-id": "vyggbi1uNjKKvIXIJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~roku-discovery-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-roku-discovery-parser-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~roku-discovery-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-roku-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~roku-discovery-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-roku-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Keywords": { "title": "Keywords", "type": "array", "description": "The keywords for the spider.", "default": [ "bridgerton", "thriller", "comedy", "romantic" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "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 } } } } } } } } } } ```