# HTML Scraper pro (`scrapingxpert/html-scraper-pro`) Actor
The HTML Scraper Pro is a powerful tool designed to extract the HTML source code and metadata from websites. It uses advanced web scraping techniques to retrieve the full HTML content of web pages,page title and HTTP status code.This tool is ideal for data extraction, website analysis, and archiving
- **URL**: https://apify.com/scrapingxpert/html-scraper-pro.md
- **Developed by:** [scrapingxpert](https://apify.com/scrapingxpert) (community)
- **Categories:** SEO tools, Lead generation, Automation
- **Stats:** 309 total users, 9 monthly users, 100.0% runs succeeded, 9 bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $16.00 / 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
## 🧲 HTML Scraper Pro 🧲
##### Welcome to HTML Scraper Pro 🎉
The **HTML Scraper Pro** is a powerful tool designed to extract the **HTML source code** and **metadata** from websites. It uses advanced web scraping techniques to retrieve the full HTML content of web pages, along with the page title and HTTP status code. This tool is ideal for data extraction, website analysis, and archiving.
---
### ✨ Key Features ✨
- **HTML Source Code Extraction**: Retrieves the full HTML source code of web pages.
- **Page Title Extraction**: Extracts the title of the webpage.
- **HTTP Status Code**: Provides the HTTP status code (e.g., 200, 404) for each URL.
- **Customizable Parameters**: Allows you to set scrolling and waiting times for AJAX-loaded pages.
- **Multiple URL Support**: Processes multiple website URLs simultaneously.
- **Error Handling**: Gracefully handles errors and ensures smooth execution.
---
### ✨ How to Use It ✨
#### 📌 Step 1: Prepare Your Input
1. Navigate to the website you want to scrape.
2. Copy the URL of the website from your browser's address bar.
#### 📌 Step 2: Configure the Actor
1. In the input area of the **HTML Scraper Pro**, paste the URL into the "Start URLs" field.
2. Optionally, configure the following parameters:
- **Scroll for one screen (times)**: Number of times to scroll down by one screen (for AJAX-loaded pages).
- **Scroll to the bottom of the webpage (times)**: Number of times to scroll to the bottom of the page (for AJAX-loaded pages).
- **Wait before extraction (seconds)**: Time to wait before extracting the HTML source code (for slow-loading pages).
#### 📌 Step 3: Run the Scraper
1. Run the scraper to start extracting the HTML source code and metadata.
2. Depending on the size of the website and the parameters, the scraper may take a few minutes to complete.
#### 📌 Step 4: Download the Data
1. Once the scraper has finished, you can download the extracted data in various formats, including **JSON**, **CSV**, **Excel**, **HTML**, and more.
2. Use the extracted data for website analysis, archiving, or further processing.
---
### ✨ Output Example ✨
Here is an example of the data output in JSON format:
```json
[
{
"Status_code": 200,
"Original_URL": "https://example.com",
"Page_title": "Example Domain",
"Source_code": "...",
}
]
````
You can choose to download your data in JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.
***
### ✨ Maximize Efficiency: HTML Scraper Pro with Apify API ✨
The Apify API empowers you with programmatic access to the comprehensive Apify platform. With RESTful HTTP endpoints at your disposal, you can effortlessly manage, schedule, and execute Apify actors. Additionally, the API facilitates seamless access to datasets, performance monitoring, result retrieval, version creation, updates, and much more.
Leverage the apify-client NPM package to tap into the API using Node.js, or employ the apify-client PyPI package for Python integration.
For comprehensive information, explore the Apify API reference documentation, or simply click on the API tab to explore insightful code examples.
***
### 🛠️ Integration
Leverage the apify-client NPM package for Node.js or the apify-client PyPI package for Python integration.
***
### 💬 Feedback 💬
If you have any technical feedback or encountered a bug while using the HTML Scraper Pro, please create an issue on the actor's dedicated ["Issues"](https://console.apify.com/actors/7BhF4151OSrcQueku/issues) tab in the Apify Console. We value your input and appreciate your help in improving our services.
***
### 💼 Hire Me for Your Projects 💼
Looking for a freelancer to assist with web scraping, automation, or data extraction? Feel free to hire me on [hire me on Upwork](https://www.upwork.com/freelancers/~01483c7790a543c9bd) for your next project.
***
### 📩 Contact Me 📩
##### Contact me through Apify or email me at \[oabakar@proton.me].
# Actor input Schema
## `start_urls` (type: `array`):
URLs to start with
## `max_depth` (type: `integer`):
Depth to which to scrape to
## Actor input object example
```json
{
"start_urls": [
{
"url": "https://apify.com"
}
],
"max_depth": 1
}
```
# 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 = {
"start_urls": [
{
"url": "https://apify.com"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapingxpert/html-scraper-pro").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 = { "start_urls": [{ "url": "https://apify.com" }] }
# Run the Actor and wait for it to finish
run = client.actor("scrapingxpert/html-scraper-pro").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 '{
"start_urls": [
{
"url": "https://apify.com"
}
]
}' |
apify call scrapingxpert/html-scraper-pro --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapingxpert/html-scraper-pro",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "HTML Scraper pro",
"description": "The HTML Scraper Pro is a powerful tool designed to extract the HTML source code and metadata from websites. It uses advanced web scraping techniques to retrieve the full HTML content of web pages,page title and HTTP status code.This tool is ideal for data extraction, website analysis, and archiving",
"version": "0.2",
"x-build-id": "QgjVHJl3GjIdZCs0F"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapingxpert~html-scraper-pro/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapingxpert-html-scraper-pro",
"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/scrapingxpert~html-scraper-pro/runs": {
"post": {
"operationId": "runs-sync-scrapingxpert-html-scraper-pro",
"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/scrapingxpert~html-scraper-pro/run-sync": {
"post": {
"operationId": "run-sync-scrapingxpert-html-scraper-pro",
"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": [
"start_urls"
],
"properties": {
"start_urls": {
"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"
}
}
}
},
"max_depth": {
"title": "Maximum depth",
"type": "integer",
"description": "Depth to which to scrape to",
"default": 1
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```