# Northface Profile Scraper (`getdataforme/northface-profile-scraper`) Actor
Project Cheerio Crawler Typescript is a web scraping tool using Cheerio and TypeScript for efficient data extraction. It offers scalable performance, customizable start URLs, and detailed output, making it ideal for market research, competitive analysis, and more. Easy setup via Apify.
- **URL**: https://apify.com/getdataforme/northface-profile-scraper.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
## Project Cheerio Crawler Typescript
### Introduction
Project Cheerio Crawler Typescript is a robust web scraping tool designed to extract structured data from web pages using Cheerio and TypeScript. This actor is ideal for users who need reliable and efficient data extraction for various applications, such as market research, competitive analysis, and more.
### Features
- **Efficient Web Crawling**: Utilizes Cheerio for fast and efficient HTML parsing.
- **TypeScript Integration**: Ensures type safety and improved code quality.
- **Customizable Start URLs**: Easily configure the starting point of your crawl.
- **Data Reliability**: Extracts high-quality, structured data consistently.
- **Scalable Performance**: Handles large-scale data extraction tasks with ease.
- **Detailed Output**: Provides comprehensive data including product details, availability, and more.
- **User-Friendly Interface**: Simple setup and configuration through the Apify platform.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|------------|--------|----------|------------------------|-------------------------------------------------------------------------|
| startUrls | array | Yes | URLs to start with. | `[{ "url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702" }]` |
### Example Usage
#### Example Input
```json
{
"startUrls": [
{
"url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702"
}
]
}
````
#### Example Output
```json
[
{
"url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702",
"title": "Men's Jackets and Coats | The North Face",
"description": "From frigid mountainsides to autumn trails to nighttime bonfires, stay warm with The North Face men's jackets and coats for all weather. Adventure in comfort.",
"price": null,
"sku": null,
"color": {
"selected": null,
"available": [
{
"name": "TNF Black",
"colorCode": "#262527",
"available": true
},
// Additional colors...
],
"count": 44
},
"sizes": {
"available": [],
"all": [],
"count": 0,
"availableCount": 0
},
"availability": {
"inStock": false,
"status": "out_of_stock",
"message": "Out of Stock",
"availableSizes": 0
},
"features": [],
"details": {},
"materials": null,
"fit": null,
"images": [],
"categories": {
"all": [
{
"name": "Men's",
"url": "https://www.northface.com/en-us/c/mens-211701",
"level": 1
}
],
"primary": {
"name": "Men's",
"url": "https://www.northface.com/en-us/c/mens-211701",
"level": 1
},
"secondary": null,
"tertiary": null
},
"rating": {
"average": null,
"count": 0,
"hasReviews": false
},
"scrapedAt": "2026-03-30T10:49:51.459Z"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather data on product offerings and trends.
- **Competitive Intelligence**: Monitor competitor pricing and product availability.
- **Price Monitoring**: Track price changes over time for strategic pricing decisions.
- **Content Aggregation**: Compile data from various sources for content creation.
- **Academic Research**: Collect data for research projects and studies.
- **Business Automation**: Automate data collection processes to save time and resources.
### Installation and Usage
1. Search for "Project Cheerio Crawler Typescript" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
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 detailed information about the scraped web page, including URL, title, description, color options, availability, and more. This structured format allows for easy integration into various data processing workflows.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `startUrls` (type: `array`):
URLs to start with.
## Actor input object example
```json
{
"startUrls": [
{
"url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702"
}
]
}
```
# Actor output Schema
## `results` (type: `string`):
No description
# 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://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/northface-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 = { "startUrls": [{ "url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702" }] }
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/northface-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 '{
"startUrls": [
{
"url": "https://www.thenorthface.com/en-us/c/mens/mens-jackets-and-vests-211702"
}
]
}' |
apify call getdataforme/northface-profile-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/northface-profile-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Northface Profile Scraper",
"description": "Project Cheerio Crawler Typescript is a web scraping tool using Cheerio and TypeScript for efficient data extraction. It offers scalable performance, customizable start URLs, and detailed output, making it ideal for market research, competitive analysis, and more. Easy setup via Apify.",
"version": "0.0",
"x-build-id": "AXqiSPV0U3ZWaTahB"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~northface-profile-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-northface-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~northface-profile-scraper/runs": {
"post": {
"operationId": "runs-sync-getdataforme-northface-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~northface-profile-scraper/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-northface-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"startUrls": {
"title": "Start URLs",
"type": "array",
"description": "URLs to start with.",
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```