# Dnb Discovery Parser Spider (`getdataforme/dnb-discovery-parser-spider`) Actor The Dnb Discovery Parser Spider extracts detailed company data from Dun & Bradstreet using customizable keywords, offering high-quality profiles in JSON, CSV, or Excel formats.... - **URL**: https://apify.com/getdataforme/dnb-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, 0 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 --- ## Dnb Discovery Parser Spider ### Introduction The Dnb Discovery Parser Spider is a powerful tool designed to extract comprehensive company data from Dun & Bradstreet's extensive database. It enables users to gather detailed information about companies based on specific keywords, providing valuable insights for market research and competitive analysis. ### Features - **Keyword-Based Extraction**: Customize searches using specific industry-related keywords. - **High Data Quality**: Reliable and accurate company profiles sourced directly from D&B. - **Configurable Limits**: Set item limits per run to control data volume efficiently. - **Flexible Output Formats**: Export results in JSON, CSV, or Excel for easy integration. - **Scalable Performance**: Designed to handle large datasets with optimal speed. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|------------------------------| | Keywords | array | No | The keywords for the spider. | `["cloud", "software"]` | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Keywords": ["cloud"], "item_limit": 5 } ```` #### Output JSON ```json [ { "company_name": "CLOUD NETWORK TECHNOLOGY SINGAPORE PTE. LTD.", "industry": "Computer and Peripheral Equipment Manufacturing", "location_type": "Subsidiary", "country_region": "Singapore, Singapore", "country": "Singapore", "city": "Singapore", "address": "54 Genting Lane", "zip_code": "349562", "duns": "9381221757bbb29976827e219a291e96", "profile_link": "https://www.dnb.com/business-directory/company-profiles.cloud_network_technology_singapore_pte_ltd.9381221757bbb29976827e219a291e96", "tags": [], "search_keyword": "cloud", "page": 1, "total_results": 123763, "total_pages": 4951, "actor_id": "XI70ISoGmFtsJPNnH", "run_id": "rfbpqVLpq55mdkEMZ" }, { "company_name": "GOOGLE CLOUD EMEA LIMITED", "industry": "Computer Systems Design and Related Services", "location_type": "Subsidiary", "country_region": "DUBLIN, Ireland", "country": "Ireland", "city": "DUBLIN", "address": "70 Sir John Rogerson's Quay", "zip_code": "D02 R296", "duns": "67c261e2d91465a089cbe5ecdd68af85", "profile_link": "https://www.dnb.com/business-directory/company-profiles.google_cloud_emea_limited.67c261e2d91465a089cbe5ecdd68af85", "tags": [], "search_keyword": "cloud", "page": 1, "total_results": 123763, "total_pages": 4951, "actor_id": "XI70ISoGmFtsJPNnH", "run_id": "rfbpqVLpq55mdkEMZ" }, { "company_name": "ALIBABA CLOUD (SINGAPORE) PRIVATE LIMITED", "industry": "Computer Systems Design and Related Services", "location_type": "Subsidiary", "country_region": "Singapore, Singapore", "country": "Singapore", "city": "Singapore", "address": "51 Bras Basah Road", "zip_code": "189554", "duns": "ef56bce33de21ec543f00031fd85a01c", "profile_link": "https://www.dnb.com/business-directory/company-profiles.alibaba_cloud_(singapore)_private_limited.ef56bce33de21ec543f00031fd85a01c", "tags": [], "search_keyword": "cloud", "page": 1, "total_results": 123763, "total_pages": 4951, "actor_id": "XI70ISoGmFtsJPNnH", "run_id": "rfbpqVLpq55mdkEMZ" } ] ``` ### Use Cases - **Market Research and Analysis**: Identify potential business opportunities by analyzing competitor data. - **Competitive Intelligence**: Gain insights into competitors' operations, locations, and industry standings. - **Price Monitoring**: Track pricing strategies of companies within specific sectors. - **Content Aggregation**: Compile comprehensive datasets for reports or presentations. - **Academic Research**: Support studies with reliable company information from diverse industries. - **Business Automation**: Integrate data extraction into automated workflows for continuous monitoring. ### Installation and Usage 1. Search for "Dnb 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 of company profiles with fields such as `company_name`, `industry`, `location_type`, `country_region`, `address`, and more. Each entry includes metadata like `search_keyword`, `page`, `total_results`, and unique identifiers (`actor_id`, `run_id`). ### Error Handling - **Invalid Keywords**: Ensure keywords are relevant to avoid empty results. - **Rate Limiting**: Monitor for rate limit errors; adjust parameters or request higher limits if necessary. - **Network Issues**: Check connectivity and retry if network-related errors occur. ### Rate Limiting and Best Practices - Be mindful of the D\&B website's rate limits. Adjust `item_limit` to manage data volume efficiently. - Use appropriate intervals between requests to avoid being blocked. - Regularly review logs for any warnings or errors related to rate limiting. ### Limitations and Considerations - The Actor relies on publicly available data from D\&B, which may not cover all companies comprehensively. - Ensure compliance with D\&B's terms of service when using the extracted data. - Performance can 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": [ "cloud", "software" ], "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/dnb-discovery-parser-spider").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("getdataforme/dnb-discovery-parser-spider").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 getdataforme/dnb-discovery-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/dnb-discovery-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Dnb Discovery Parser Spider", "description": "The Dnb Discovery Parser Spider extracts detailed company data from Dun & Bradstreet using customizable keywords, offering high-quality profiles in JSON, CSV, or Excel formats....", "version": "0.0", "x-build-id": "VbyQrpxjTv8hRPzjJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~dnb-discovery-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-dnb-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~dnb-discovery-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-dnb-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~dnb-discovery-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-dnb-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "cloud", "software" ], "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 } } } } } } } } } } ```