# Python Website Scraper for B2B Leads (`complex_intricate_networks/python-web-scraper-and-data-engine`) Actor Extract high-intent B2B leads with this powerful Python web scraper. This data scraper automates the discovery of recently funded startups, identifies founders, and tracks hiring status. Turn any site into a structured database with this advanced website scraper and scraping tool. - **URL**: https://apify.com/complex\_intricate\_networks/python-web-scraper-and-data-engine.md - **Developed by:** [SK](https://apify.com/complex_intricate_networks) (community) - **Categories:** AI, Lead generation, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 ## πŸš€ Python Web Scraper: Hyper-Targeted Lead & Data Intelligence Engine ### πŸ’‘ Overview Stop manually hunting for leads. This **Python web scraper** is a high-performance **data scraper** designed to identify and extract high-value B2B opportunities in real-time. Whether you need a specialized **website scraper** to track startup funding rounds or a comprehensive **scraping tool** to monitor market shifts, this engine delivers "ready-to-close" leads directly into your dashboard. Built for speed and precision, it bypasses the limitations of generic **web scraper Python** scripts by utilizing advanced manual queue management and deep-text data enrichment. --- ### πŸ”₯ Key Features * **Hyper-Targeted Extraction:** More than just a simple **data scraper**β€”it identifies Founders, Funding Amounts, and Valuation data directly from the source. * **Hiring Intent Detection:** Automatically flags companies that are actively growing, giving you a massive advantage for recruitment or B2B sales. * **SEO & AEO Optimized:** Data is structured to be easily indexed by search engines and interpreted by AI-driven search models. * **Cost-Efficient Engine:** Optimized Cheerio-based logic significantly reduces compute costs compared to browser-heavy **scraping tools**. --- ### πŸ› οΈ How it Works (The Logic) This **website scraper** follows a three-stage intelligence protocol: 1. **Discovery:** Scans industry hubs (like TechCrunch Startups) to find the latest "Gold" articles. 2. **Extraction:** Uses specialized **web scraper Python** logic to pull names, funding numbers, and dates. 3. **Enrichment:** Visits the target company's actual website to verify LinkedIn profiles, tech stacks, and hiring status. --- ### πŸ“¦ Sample Data Output (High-Intent Leads) Users receive structured, actionable data ready for any CRM (Salesforce, Hubspot, etc.). Below is a live sample of the intelligence this **data scraper** provides: | Startup Name | Funding Amount | Founder Name | Hiring Status | LinkedIn Profile | Website | | :--- | :--- | :--- | :--- | :--- | :--- | | **Shield AI** | $12.7 Billion | Brandon Tseng | βœ… YES | [View Profile](https://www.linkedin.com/company/shield-ai/) | [Visit](https://shield.ai/) | | **Aetherflux** | $2 Billion | Manuel Kroiss | βœ… YES | [View Profile](https://www.linkedin.com/company/aetherflux/) | [Visit](https://www.aetherflux.com/) | | **Harvey** | $1.1 Billion | Winston Weinberg | βœ… YES | [View Profile](https://www.linkedin.com/company/harvey-ai/) | [Visit](https://www.harvey.ai/) | | **Deccan AI** | $25 Million | (Detected in Article) | βœ… YES | [View Profile](https://www.linkedin.com/company/deccan-ai/) | [Visit](https://www.deccan.ai/) | | **VITL** | $7.5 Million | (Detected in Article) | βœ… YES | [View Profile](https://www.linkedin.com/company/vitlrx/) | [Visit](https://vitlrx.com/) | --- ### πŸš€ Getting Started To use this **web scraper Python** tool on Apify: 1. **Input:** What kind of startups are you looking for? (e.g., 'Fintech startups funded last 7 days') 2. **Run:** The **data scraper** begins processing and enriching in the cloud. 3. **Export:** Download your "money-printing" leads in CSV, JSON, or Excel. ### πŸ›‘οΈ Disclaimer This **scraping tool** should be used in compliance with the Terms of Service of the target websites. Respect robots.txt and use professional proxies for large-scale **website scraper** tasks. --- *Developed for B2B Growth Hackers and Data Analysts.* # Actor input Schema ## `query` (type: `string`): What kind of startups are you looking for? (e.g., 'Fintech startups funded last 7 days') ## `maxResults` (type: `integer`): Number of startup websites to crawl. ## `proxyConfiguration` (type: `object`): Recommended to use Apify Proxy to avoid Google blocks. ## Actor input object example ```json { "query": "recently funded AI startups", "maxResults": 100, "proxyConfiguration": { "useApifyProxy": true } } ```` # 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 = { "query": "recently funded AI startups" }; // Run the Actor and wait for it to finish const run = await client.actor("complex_intricate_networks/python-web-scraper-and-data-engine").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 = { "query": "recently funded AI startups" } # Run the Actor and wait for it to finish run = client.actor("complex_intricate_networks/python-web-scraper-and-data-engine").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 '{ "query": "recently funded AI startups" }' | apify call complex_intricate_networks/python-web-scraper-and-data-engine --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=complex_intricate_networks/python-web-scraper-and-data-engine", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Python Website Scraper for B2B Leads", "description": "Extract high-intent B2B leads with this powerful Python web scraper. This data scraper automates the discovery of recently funded startups, identifies founders, and tracks hiring status. Turn any site into a structured database with this advanced website scraper and scraping tool.", "version": "0.0", "x-build-id": "KYevFTjziguvMwIs9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/complex_intricate_networks~python-web-scraper-and-data-engine/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-complex_intricate_networks-python-web-scraper-and-data-engine", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/complex_intricate_networks~python-web-scraper-and-data-engine/runs": { "post": { "operationId": "runs-sync-complex_intricate_networks-python-web-scraper-and-data-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/complex_intricate_networks~python-web-scraper-and-data-engine/run-sync": { "post": { "operationId": "run-sync-complex_intricate_networks-python-web-scraper-and-data-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search Query", "type": "string", "description": "What kind of startups are you looking for? (e.g., 'Fintech startups funded last 7 days')", "default": "AI startups funded this week, Recent Series A Fintech startups London" }, "maxResults": { "title": "Max Leads", "type": "integer", "description": "Number of startup websites to crawl.", "default": 100 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Recommended to use Apify Proxy to avoid Google blocks.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```