# KR Brandi Scraper (`styleindexamerica/kr-brandi-scraper`) Actor

This actor is intended to extract data from brandi.co.kr

- **URL**: https://apify.com/styleindexamerica/kr-brandi-scraper.md
- **Developed by:** [PopinBorder Castnet](https://apify.com/styleindexamerica) (community)
- **Categories:** E-commerce
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### TypeScript Crawlee & CheerioCrawler template

A template example built with [Crawlee](https://crawlee.dev/) to scrape data from a website using [Cheerio](https://cheerio.js.org/) wrapped into [CheerioCrawler](https://crawlee.dev/api/cheerio-crawler/class/CheerioCrawler).

### Included features

- **[Apify SDK](https://docs.apify.com/sdk/js)** - toolkit for building [Actors](https://apify.com/actors)
- **[Crawlee](https://crawlee.dev/)** - web scraping and browser automation library
- **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input
- **[Dataset](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-datasets)** - store structured data where each object stored has the same attributes
- **[Cheerio](https://cheerio.js.org/)** - a fast, flexible & elegant library for parsing and manipulating HTML and XML

### How it works

This code is a TypeScript script that uses [Crawlee CheerioCralwer](https://crawlee.dev/api/cheerio-crawler/class/CheerioCrawler) framework to crawl a website and extract the data from the crawled URLs with Cheerio. It then stores the website titles in a dataset.

- The crawler starts with URLs provided from the input `startUrls` field defined by the input schema. Number of scraped pages is limited by `maxPagesPerCrawl` field from input schema.
- The crawler uses `requestHandler` for each URL to extract the data from the page with the Cheerio library and to save the title and URL of each page to the dataset. It also logs out each result that is being saved.

### Resources

- [Video tutorial](https://www.youtube.com/watch?v=yTRHomGg9uQ) on building a scraper using CheerioCrawler
- [Written tutorial](https://docs.apify.com/academy/web-scraping-for-beginners/challenge) on building a scraper using CheerioCrawler
- [Web scraping with Cheerio in 2023](https://blog.apify.com/web-scraping-with-cheerio/)
- How to [scrape a dynamic page](https://blog.apify.com/what-is-a-dynamic-page/) using Cheerio
- [TypeScript vs. JavaScript: which to use for web scraping?](https://blog.apify.com/typescript-vs-javascript-crawler/)
- [Integration with Zapier](https://apify.com/integrations), Make, Google Drive and others
- [Video guide on getting scraped data using Apify API](https://www.youtube.com/watch?v=ViYYDHSBAKM)
- A short guide on how to build web scrapers using code templates:

[web scraper template](https://www.youtube.com/watch?v=u-i-Korzf8w)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the actor use the following command:

```bash
apify run
```

### Deploy to Apify

#### Connect Git repository to Apify

If you've created a Git repository for the project, you can easily connect to Apify:

1. Go to [Actor creation page](https://console.apify.com/actors/new)
2. Click on **Link Git Repository** button

#### Push project on your local machine to Apify

You can also deploy the project on your local machine to Apify without the need for the Git repository.

1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action.

   ```bash
   apify login
   ```

2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my).

   ```bash
   apify push
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## `productUrls` (type: `array`):

This is a list of product URLs.

## `listingUrls` (type: `array`):

This is a list of category or brand URLs

## `keywords` (type: `array`):

This is a list of keyword to search products based on.

## `startPageNumber` (type: `integer`):

Page number to start scraping products.

## `finalPageNumber` (type: `integer`):

Page number to start scraping products.

## `minPrice` (type: `integer`):

Minimum price of scrapped products.

## `maxPrice` (type: `integer`):

Maximum price of scrapped products.

## Actor input object example

```json
{}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startPageNumber": 0,
    "finalPageNumber": 0,
    "minPrice": 0,
    "maxPrice": 0
};

// Run the Actor and wait for it to finish
const run = await client.actor("styleindexamerica/kr-brandi-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "startPageNumber": 0,
    "finalPageNumber": 0,
    "minPrice": 0,
    "maxPrice": 0,
}

# Run the Actor and wait for it to finish
run = client.actor("styleindexamerica/kr-brandi-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "startPageNumber": 0,
  "finalPageNumber": 0,
  "minPrice": 0,
  "maxPrice": 0
}' |
apify call styleindexamerica/kr-brandi-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,styleindexamerica/kr-brandi-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/OVfg4nVqj39ioJlNm/builds/Zi7i17vFKAEXzImjh/openapi.json