# PDF Link Extractor (`happitap/pdf-link-extractor`) Actor Deeply crawl any website to automatically extract all hidden and exposed PDF download links into a clean dataset - **URL**: https://apify.com/happitap/pdf-link-extractor.md - **Developed by:** [HappiTap](https://apify.com/happitap) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 ## PDF Link Extractor **Deeply crawl any website to automatically extract all hidden and exposed PDF download links into a clean dataset.** Whether you are building a repository of financial annual reports, hunting for product manuals, or scraping research papers from university portals, manually clicking through hundreds of web pages to find PDF links is tedious. This actor fully automates the process using a high-speed HTML crawler. ### What can this Actor do? - ✅ **Deep Website Crawling** - Give it a starting URL and it will autonomously navigate through the website's internal architecture to find every single `.pdf` link. - ✅ **Automatic Link Resolution** - Automatically converts messy relative paths (like `href="../../docs/report.pdf"`) into clean, clickable absolute URLs. - ✅ **Global Deduplication** - If the exact same PDF is linked in the footer of 100 different pages, this actor is smart enough to only extract it *once*, keeping your dataset perfectly clean. - ✅ **Anchor Text Extraction** - Extracts the text that was used to link to the PDF (e.g., "Download our 2023 Form 10-K") so you have context on what the file contains. ### Why scrape PDF links? - 🎯 **Financial Research** - Bulk scrape investor relations pages to gather quarterly earnings reports, SEC filings, and ESG reports. - 📊 **Academic Data** - Crawl university directories and research portals to compile datasets of academic papers and whitepapers. - 📍 **E-commerce & Manufacturing** - Automatically find and download product manuals, MSDS sheets, and technical spec sheets from manufacturer websites. ### How to use it 1. Enter your website URL into the **Start URLs** field. 2. Set the **Max Pages to Scan** to limit how deep the crawler goes (e.g., 500 pages). 3. Ensure **Deep Crawl** is enabled if you want it to navigate the site, or disable it if you only want to scan the exact URLs provided. 4. Click Start! ### How much does it cost? This actor uses a **Pay-Per-Event (PPE)** pricing model. You only pay for the HTML pages successfully scanned! - **$0.50 per 1,000 pages scanned.** ### Output Example When a unique PDF is found, the actor pushes this data to your dataset: ```json { "pageUrl": "https://example.com/investor-relations/reports", "pdfUrl": "https://example.com/assets/docs/2023-annual-report.pdf", "linkText": "Download 2023 Annual Report (PDF)", "scrapedAt": "2023-10-25T15:00:00.000Z" } ```` # Actor input Schema ## `startUrls` (type: `array`): List of URLs to start scanning for PDFs. The crawler will follow links on the same domain. ## `maxPagesPerCrawl` (type: `integer`): Maximum number of HTML pages to crawl across the entire site. ## `deepCrawl` (type: `boolean`): If enabled, the actor will follow internal links to find PDFs hidden deep in the site architecture. If disabled, it only scans the exact Start URLs provided. ## Actor input object example ```json { "startUrls": [ { "url": "https://example.com" } ], "maxPagesPerCrawl": 100, "deepCrawl": true } ``` # Actor output Schema ## `results` (type: `string`): Extracted data items stored in the default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://example.com" } ], "maxPagesPerCrawl": 100, "deepCrawl": true }; // Run the Actor and wait for it to finish const run = await client.actor("happitap/pdf-link-extractor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "startUrls": [{ "url": "https://example.com" }], "maxPagesPerCrawl": 100, "deepCrawl": True, } # Run the Actor and wait for it to finish run = client.actor("happitap/pdf-link-extractor").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 '{ "startUrls": [ { "url": "https://example.com" } ], "maxPagesPerCrawl": 100, "deepCrawl": true }' | apify call happitap/pdf-link-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=happitap/pdf-link-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PDF Link Extractor", "description": "Deeply crawl any website to automatically extract all hidden and exposed PDF download links into a clean dataset", "version": "0.0", "x-build-id": "C8p6dzP4FpjO7YHZt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/happitap~pdf-link-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-happitap-pdf-link-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/happitap~pdf-link-extractor/runs": { "post": { "operationId": "runs-sync-happitap-pdf-link-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/happitap~pdf-link-extractor/run-sync": { "post": { "operationId": "run-sync-happitap-pdf-link-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of URLs to start scanning for PDFs. The crawler will follow links on the same domain.", "default": [ { "url": "https://example.com" } ], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxPagesPerCrawl": { "title": "Max Pages to Scan", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Maximum number of HTML pages to crawl across the entire site.", "default": 100 }, "deepCrawl": { "title": "Deep Crawl", "type": "boolean", "description": "If enabled, the actor will follow internal links to find PDFs hidden deep in the site architecture. If disabled, it only scans the exact Start URLs provided.", "default": 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 } } } } } } } } } } ```