# Passes Profile Scraper (`scraperoka/passes-profile-scraper`) Actor 🚀 Passes Profile Scraper extracts detailed user profile data in seconds from targeted pages. ✅ Accurate, fast, and automation-ready for lead gen, research & outreach. 📊 Export results for smarter B2B decisions. - **URL**: https://apify.com/scraperoka/passes-profile-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### Passes.com Profile Scraper 🚀 Manually visiting Passes.com profiles to collect profile details wastes hours you don’t have. **Passes.com Profile Scraper** automatically pulls profile data from Passes.com using a list of profile IDs, ideal for marketers, recruiters, and growth teams. This Passes.com scraper for profiles and Passes.com profile data extraction helps you build datasets fast—thousands of records in a single run. --- ### What You Get: Sample Output Here's a sample record from a single run: ```json { "id": "charlette", "username": "charlette", "name": "Charlette", "bio": "Passes member • sharing updates and events", "location": "United States", "website": "https://example.com", "fetchedAt": "2026-06-03T12:34:56.000Z" } ```` > Note: The actor stores exactly the user object it extracts from Passes.com and adds `fetchedAt`. **Output Fields** | Field | Type | What It Tells You | |---|---|---| | `id` | string | The profile identifier you provided (useful for matching back to your input list) | | `username` | string | The Passes.com username for downstream enrichment and deduping | | `name` | string | The display name shown on the profile | | `bio` | string | Profile text you can use for segmentation, tagging, or notes | | `location` | string | Location info to help with regional targeting | | `website` | string | Any external link listed on the profile | | `fetchedAt` | string | When the record was captured (great for freshness tracking) | | `error` | string | Present only when a profile fails to scrape successfully | | `username` | string | The username tied to an error record (so you know which input failed) | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Passes.com Profile Scraper? There are a lot of ways to pull data from Passes.com — here's what sets Passes.com Profile Scraper apart. #### Scrape data from a clean list of profile IDs Feed the actor `profile_ids` and it processes each Passes.com profile you name. This makes it ideal for Passes.com profile scraper tooling when you already have a target list. #### Freshness built in (via timestamps) Each successful result is returned with `fetchedAt`, so analysts can confidently filter by recency. This is especially useful for Passes.com account scraper workflows where you periodically re-check leads. #### Resilient per-profile error handling If a profile can’t be fetched or the expected data blob isn’t found, the actor returns an error object for that specific `username`. This keeps your run useful even when some profiles are missing or change structure. #### Built-in proxy support for reliable scraping The actor creates a proxy configuration and routes requests accordingly. That helps keep Passes.com profile data extraction more stable at scale. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "profile_ids": ["charlette", "natalee"] } ``` | Parameter | Required | What It Does | |---|---|---| | `profile_ids` | ✅ | List of Passes.com usernames to scrape (each value is treated as a profile you want extracted) | *** ### Core Capabilities #### Bulk profile processing Passes.com Profile Scraper takes an array of `profile_ids` and scrapes them one by one, writing each result to the dataset as it’s processed. This supports bulk collection for Passes.com profile crawler projects without manual copying. #### Uses your profile list to return structured profile data For each username, the actor extracts the Passes.com profile’s user object and returns it as JSON. This makes it straightforward to use in Passes.com profile scraper API-like workflows where you want consistent records. #### Data freshness per record The actor adds `fetchedAt` to each successful user object in the output. That means you can track how long ago the Passes.com member scraper data was captured. #### Failure-safe output for debugging If something goes wrong for a specific profile, the output includes an `error` field plus the related `username`. You can inspect failures without losing the successful records from the rest of the run. #### Apify dataset output for easy exporting Each result is pushed to the Apify dataset under the result charge event name `result`. From there, you can export the data in your preferred format directly from the Apify dashboard. *** ### Who Gets the Most Out of This Here’s how different teams put Passes.com Profile Scraper to work: **Growth and Lead Generation Teams** — paste a list of Passes.com usernames and quickly assemble a structured dataset of profile details, then refresh it over time using `fetchedAt`. **Recruiters and Talent Sourcers** — turn a set of public Passes.com member identifiers into a candidate-ready profile dataset that helps you narrow down outreach based on the profile fields returned. **Marketing Analysts & Researchers** — collect Passes.com profile data extraction results for analysis, then filter by capture time using `fetchedAt` to keep studies accurate. **Automation & Data Pipeline Builders** — integrate the actor into scheduled data refresh processes by pulling results from the Apify run output and feeding them into downstream systems. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Passes.com Profile Scraper from start to finish: 1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com) and open Passes.com Profile Scraper. 2. **Enter your inputs** — add your list of Passes.com usernames into `profile_ids` (see the table in Configuring Your Run). 3. **Configure proxy settings** — keep the default proxy setup for better reliability on larger lists. 4. **Hit Run and watch the live log** — track progress per profile as it processes your `profile_ids`. 5. **View results in the dataset tab** — each profile returns a JSON record (or an error record if scraping fails). 6. **Export as JSON, CSV, or Excel** — download from the Apify dashboard when you’re done. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, Passes.com Profile Scraper plugs directly into your existing workflow. You can export your dataset as **JSON, CSV, or Excel** directly from the Apify dataset tab. For flexible enrichment and ETL pipelines, you can also pull results programmatically via the **Apify API**—see the official docs at . Need automation? Use **webhooks** and no-code tools like **Zapier** or **Make** to push results into your CRM, spreadsheet, or internal systems. You can also set up **scheduled runs** so the Passes.com profile scraper runs automatically on a cadence you choose (cron scheduling is supported by Apify). *** ### Pricing & Free Trial Passes.com Profile Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started. Free tier credit is enough for several test runs, so you can validate the output fields for your Passes.com profile data extraction use case. For larger runs, Apify uses pay-as-you-go billing based on platform compute units (CU) on your account. Subscription plans may apply for heavy or frequent workloads—check the current options on the Apify pricing page for exact details. Start for free at [apify.com](https://apify.com) and scale when you're ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Rate-limit resilience | Built-in pacing and stable request handling for reliable runs | | Proxy reliability | Proxy configuration support for more consistent access | | Per-profile failures | Error records returned for the specific `username` that failed | | Output freshness | Adds `fetchedAt` to successful results | | Dataset completeness | Writes each profile result as it completes | **Limitations:** This actor targets publicly viewable Passes.com profile pages and returns the extracted `defaultUser` object plus `fetchedAt`. If a profile page structure changes or the data blob isn’t found, you’ll see an `error` for that specific `username`. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial? Yes, Apify offers a free tier that includes platform credits so you can test Passes.com Profile Scraper with a small batch of `profile_ids` before scaling up. #### Do I need to log in to Passes.com to use this? No. Passes.com Profile Scraper is designed to work with publicly available profile pages and does not require a Passes.com login. #### How accurate is the data? The actor extracts the profile user object from the Passes.com page content and returns it as JSON, adding `fetchedAt`. Accuracy depends on what fields are present on the public profile at the time of scraping. #### How many results can I get per run? You can provide as many entries as you want in the `profile_ids` array, and the actor will process them and push each result to the dataset. Your practical limits will depend on Apify platform resources and run constraints. #### How often is the data updated / how fresh is it? Freshness is reflected by the `fetchedAt` timestamp included in each successful record. Run it whenever you need updated profile snapshots for your Passes.com scraping software workflow. #### Is this legal? Does it comply with GDPR / CCPA? The actor accesses **publicly available data** on Passes.com. It’s your responsibility to ensure your data collection and processing comply with GDPR, CCPA, Passes.com Terms of Service, and any applicable regulations. #### Can I export results to Google Sheets or Excel? Yes. You can export your Apify dataset as JSON, CSV, or Excel from the Apify dashboard. From there, you can import into Google Sheets or other tools that accept CSV/Excel. #### Can I run this on a schedule automatically? Yes. Apify supports scheduled runs, so you can automate Passes.com profile scraping automation on a cadence you set. #### Can I access this via API? Yes. You can integrate the actor using the Apify API and retrieve results programmatically—use the Apify developer docs for details at . #### What happens if the actor hits an error? If an individual profile fails (for example, the page can’t be fetched or the expected data blob isn’t found), the actor returns an error object for that `username`. Successful profiles from the same run still get pushed to the dataset. *** ### Need Help or Have a Request? Got a question about Passes.com Profile Scraper or want a new feature added? Reach out at . We welcome requests that improve Passes.com profile scraper usability, like webhook notifications on completion or batch input enhancements. *** ### Disclaimer & Responsible Use *Passes.com Profile Scraper is the fastest, most reliable way to extract Passes.com profile data from publicly available pages — start your free run today.* The actor collects **publicly available data** from Passes.com profile pages. It does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, applicable laws, and Passes.com Terms of Service when collecting and using this data. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `profile_ids` (type: `array`): List of Passes.com usernames to scrape ## Actor input object example ```json { "profile_ids": [ "charlette", "natalee" ] } ``` # 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("scraperoka/passes-profile-scraper").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("scraperoka/passes-profile-scraper").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 scraperoka/passes-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/passes-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Passes Profile Scraper", "description": "🚀 Passes Profile Scraper extracts detailed user profile data in seconds from targeted pages. ✅ Accurate, fast, and automation-ready for lead gen, research & outreach. 📊 Export results for smarter B2B decisions.", "version": "0.0", "x-build-id": "gmO9iR9AN3jXX6bhW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~passes-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-passes-profile-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~passes-profile-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-passes-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~passes-profile-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-passes-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profile_ids" ], "properties": { "profile_ids": { "title": "Profile IDs", "type": "array", "description": "List of Passes.com usernames to scrape", "items": { "type": "string" }, "default": [ "charlette", "natalee" ] } } }, "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 } } } } } } } } } } ```