# Arcteryx Profile Scraper (`getdataforme/arcteryx-profile-scraper`) Actor
The Arcteryx Profile Scraper efficiently extracts detailed product data from the Arcteryx website, including descriptions, variants, and pricing....
- **URL**: https://apify.com/getdataforme/arcteryx-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, 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
## Arcteryx Profile Scraper
### Introduction
The Arcteryx Profile Scraper is designed to efficiently extract detailed product information from the Arcteryx website. This actor provides a reliable solution for gathering data on product descriptions, variants, pricing, and availability, making it invaluable for market research and competitive analysis.
### Features
- **Comprehensive Data Extraction**: Captures detailed product information including descriptions, variants, and pricing.
- **High Data Quality**: Ensures accurate and up-to-date information from the Arcteryx website.
- **Efficient Performance**: Quickly processes multiple URLs to deliver results in a timely manner.
- **Scalable Solution**: Handles large volumes of data without compromising on speed or accuracy.
- **User-Friendly Interface**: Easy setup and configuration through the Apify platform.
- **Customizable Outputs**: Export data in various formats such as JSON, CSV, and Excel.
- **Robust Error Handling**: Provides clear error messages and recovery options.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|------------|--------|----------|----------------------------|-------------------------------------------------------------------------|
| startUrls | array | Yes | URLs to start with. | `[{"url": "https://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"}]` |
### Example Usage
#### Example Input JSON
```json
{
"startUrls": [
{
"url": "https://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"
}
]
}
````
#### Example Output JSON
```json
[
{
"id": "X000009533",
"name": "Kragg SL Cotton Shirt SS Men's",
"description": "Regular-fit premium cotton climbing tee for breathability and durability.",
"brand": "Arc'teryx",
"category": "Shirts and Tops",
"material": "Body: SUPIMA® premium long-staple Cotton Jersey, 160 gsm - 100% SUPIMA® Cotton, Contrast: SUPIMA® premium long-staple Cotton, 1x1 Rib, 225gsm - 100% SUPIMA® Cotton, Origin of fabric: COLOMBIA, Origin of dyeing: COLOMBIA, Origin of Manufacture: COLOMBIA",
"url": "https://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533",
"variants": [
{
"name": "Kragg SL Cotton Shirt SS Men's, Black, Size XXL",
"sku": "X000009533007",
"color": "Black",
"size": "XXL",
"image": "https://images.arcteryx.com/details/1350x1710/F25-X000009533-Kragg-SL-Cotton-Shirt-SS-Black-Front-View.jpg",
"inStock": false,
"price": 80,
"currency": "CAD",
"url": "https://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"
}
]
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather comprehensive product data for industry insights.
- **Competitive Intelligence**: Monitor competitor offerings and pricing strategies.
- **Price Monitoring**: Track price changes and availability of products.
- **Content Aggregation**: Compile product information for ecommerce platforms.
- **Academic Research**: Analyze consumer trends and product specifications.
- **Business Automation**: Automate data collection for inventory management.
### Installation and Usage
```
1. Search for "Arcteryx Profile Scraper" 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 structured as a JSON array containing detailed product information. Key fields include `id`, `name`, `description`, `brand`, `category`, `material`, `url`, and `variants`. Each variant includes `name`, `sku`, `color`, `size`, `image`, `inStock`, `price`, and `currency`.
### 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://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"
}
]
}
```
# 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://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/arcteryx-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://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533" }] }
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/arcteryx-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://arcteryx.com/ca/en/shop/mens/kragg-sl-cotton-shirt-ss-9533"
}
]
}' |
apify call getdataforme/arcteryx-profile-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/arcteryx-profile-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Arcteryx Profile Scraper",
"description": "The Arcteryx Profile Scraper efficiently extracts detailed product data from the Arcteryx website, including descriptions, variants, and pricing....",
"version": "0.0",
"x-build-id": "sVQUGgDQ3WI0dWh1t"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~arcteryx-profile-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-arcteryx-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~arcteryx-profile-scraper/runs": {
"post": {
"operationId": "runs-sync-getdataforme-arcteryx-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~arcteryx-profile-scraper/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-arcteryx-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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
}
}
}
}
}
}
}
}
}
}
```