# Argenprop Property Details Scraper (`ecomscrape/argenprop-property-details-scraper`) Actor
Discover how the ArgeProp.com Property Details Scraper streamlines real estate data extraction from Argentina's leading property platform. Extract comprehensive property information including prices, locations, features, and seller details with automated precision.
- **URL**: https://apify.com/ecomscrape/argenprop-property-details-scraper.md
- **Developed by:** [ecomscrape](https://apify.com/ecomscrape) (community)
- **Categories:** Real estate, Automation, Developer tools
- **Stats:** 16 total users, 2 monthly users, 100.0% runs succeeded, 0 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
## Contact
If you encounter any issues or need to exchange information, please feel free to contact us through the following link:
[My profile](https://apify.com/ecomscrape)
## **Professional Argenprop.com Real Estate Data Extraction Solution**
ArgeProp.com stands as one of Argentina's most prominent real estate platforms, connecting property seekers with sellers and rental agents across the country. The website hosts thousands of property listings ranging from apartments and houses to commercial spaces, making it a valuable resource for understanding the Argentinian real estate market. However, manually collecting data from individual property listings becomes time-consuming and inefficient when you need to analyze market trends, compare prices across neighborhoods, or build comprehensive property databases.
This is where the ArgeProp.com Property Details Scraper becomes invaluable. Whether you are a real estate agent tracking competitive listings, an investor analyzing market opportunities, a researcher studying housing trends, or a data analyst building predictive models, this scraper automates the entire data collection process. Instead of spending hours copying and pasting information from dozens or hundreds of property pages, you can extract structured data in minutes, allowing you to focus on analysis and decision-making rather than manual data entry.
### What This Scraper Does and Who Benefits From It
The ArgeProp.com Property Details Scraper is designed to extract comprehensive information from property listing pages on ArgeProp.com. When you provide URLs of specific property listings, the scraper visits each page, intelligently identifies and extracts relevant data fields, and returns the information in a clean, structured format that you can immediately use for analysis or integration into your systems.
The scraper's strength lies in its ability to capture not just basic information like price and address, but also detailed property features, complete descriptions, multiple image URLs, location coordinates, and seller contact information. This comprehensive approach ensures you have all the data you need for thorough property evaluation without missing critical details that could influence investment or purchasing decisions.
This tool serves several key audiences effectively. Real estate professionals can monitor competitor listings and track market changes across different neighborhoods. Property investors benefit from rapid data collection for portfolio analysis and opportunity identification. Market researchers gain access to structured data for trend analysis and forecasting. Data scientists can build datasets for machine learning models that predict property values or identify undervalued opportunities. Even individual property buyers who want to systematically compare multiple options will find this scraper useful for making informed decisions.
### Input and Output Specifications
Example url 1: https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563
Example url 2: https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17850004
Example url 3: https://www.argenprop.com/departamento-en-alquiler-en-centro--18031438
Example Screenshot of property information page:
#### Input Format
The scraper accepts JSON configuration with specific parameters to control the extraction process:
```json
{
"max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
"proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
},
"urls": [ // Links to property information pages.
"https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563",
"https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17850004",
"https://www.argenprop.com/departamento-en-alquiler-en-centro--18031438"
]
}
```
**Key Input Parameters:**
- **max_retries_per_url**: Controls the maximum number of retry attempts for each URL, ensuring reliable data extraction even if initial requests fail
- **proxy configuration**: Essential for avoiding bot detection and maintaining consistent access to Argenprop's servers
- **urls array**: Contains the specific Argenprop property detail page URLs you want to scrape
The proxy settings are particularly important as they help maintain access reliability and prevent IP blocking during data collection processes.
#### Output Format and Data Fields
You get the output from the Argenprop.com Property Details Scraper stored in a tab. The following is an example of the Information Fields collected after running the Actor.
```json
[ // List of property information
{
"id": "17185563",
"url": "https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563",
"title": "Alquiler en Barrio Industrial, Rosario",
"address": "Rufino Ortega 200, Piso 05",
"details": [
{
"label": "Sup. cubierta",
"value": "47 m² Cubierta"
},
{
"label": "Dormitorios",
"value": "1 dormitorio"
},
{
"label": "Antiguedad",
"value": "54 años"
},
{
"label": "Baños",
"value": "1 baño"
},
{
"label": "Ambientes",
"value": "3 ambientes"
}
],
"price": "$ 300.000",
"description": "\n Departamento en Alquiler
\n Dirección: Rufino Ortega 222 Bis
\n Ofrecemos un departamento de 1 dormitorio, idealmente ubicado para tu comodidad.
\n
\n Características:
\n Living Comedor: Espacioso y luminoso.
\n Cocina Americana: Práctica y funcional.
\n Baño: Completo y en buen estado.
\n Dormitorio con Placard: Amplio y con buen espacio de almacenamiento.
\n Lavadero Independiente: Comodidad adicional.
\n Detalles Adicionales:
\n
\n Este departamento es ideal para quienes buscan una vivienda cómoda y bien ubicada.
\n
\n Actualización trimestral por IPC.
\n \n
",
"location": {
"latitude": "-32,981003",
"longitude": "-60,62751",
"text": "Barrio Industrial, Rosario, Departamento de Rosario, Santa Fe"
},
"features": [
{
"label": "Cant. Ambientes",
"value": "3"
},
{
"label": "Cant. Dormitorios",
"value": "1"
},
{
"label": "Cant. Baños",
"value": "1"
},
{
"label": "Antiguedad",
"value": "54"
}
],
"images": [
"https://www.argenprop.com/static-content/36558171/a6b9b85c-95dc-4a59-af63-3c990a07b99f_u_medium.jpg",
"https://www.argenprop.com/static-content/36558171/e154fd14-e6ed-458d-beb5-26af28308aa7_u_medium.jpg",
"https://www.argenprop.com/static-content/36558171/794fde75-efab-4ab8-b761-f5f5dce012d7_u_medium.jpg"
],
"seller": {
"name": "PABLO ALLEGRI GESTION INMOBILIARIA Mat. 0230",
"phone": "https://wa.me/7929933",
"url": "https://www.argenprop.com/pablo-allegri"
}
}, // ... Many other property details
]
```
The scraper extracts an extensive range of property data fields, each serving specific analytical and business purposes:
**Output Fields Explained:**
1. **ID**: A unique identifier for the property listing on ArgeProp.com. This field is crucial for:
- Tracking specific properties over time
- Avoiding duplicate entries in databases
- Cross-referencing with the original website
2. **URL**: The original property page link. Useful for:
- Verification of extracted data
- Providing direct access to the listing
- Tracking data source for compliance
3. **Title**: The property listing headline, typically containing key information like property type, number of rooms, and location. This helps with:
- Quick property identification
- Search and filtering operations
- Initial property classification
4. **Address**: The complete property location. Critical for:
- Geographic analysis and mapping
- Neighborhood-based searches
- Location-based pricing studies
5. **Details**: Structured property specifications including number of bedrooms, bathrooms, square meters, etc. This data enables:
- Property comparison and filtering
- Size-based price analysis
- Feature-based categorization
6. **Price**: The listing price in Argentine Pesos (ARS) or other currency. Essential for:
- Market price analysis
- Budget-based filtering
- Price trend monitoring
- Investment calculations
7. **Description**: The full property description provided by the seller. Valuable for:
- Understanding property condition and unique features
- Natural language processing for trend analysis
- Marketing content research
8. **Location**: Geographic coordinates or detailed location information. Enables:
- Map visualization
- Distance calculations
- Geographic market segmentation
9. **Features**: Additional amenities like parking, pool, security, etc. Used for:
- Premium feature identification
- Feature-based price correlation
- Property comparison matrices
10. **Images**: URLs to property photographs. Important for:
- Visual property documentation
- Image-based analysis
- Marketing material collection
11. **Seller**: Contact and information about the listing agent or owner. Useful for:
- Direct communication with property representatives
- Identifying major property sellers/agencies
- Building contact databases
Each field serves specific purposes in property analysis, from basic specifications needed for filtering and comparison to advanced features required for comprehensive market research and business intelligence applications.
### How to Use: Step-by-Step Implementation
**Step 1: Prepare Your URLs**
Collect the property detail page URLs you want to scrape. Navigate to ArgeProp.com, find properties of interest, and copy their full URLs. Ensure each URL points to a property detail page, not search results or category pages.
**Step 2: Configure Your Input**
Create your JSON configuration file with appropriate settings. For ArgeProp.com, consider using Argentine proxies (AR) for better results. Set max_retries_per_url to 2-3 for optimal reliability without excessive delays.
**Step 3: Run the Scraper**
Execute the scraper with your configuration. The tool will process each URL sequentially, extracting all available data fields.
**Step 4: Review and Process Output**
Once complete, review the extracted data for completeness. The structured output can be directly imported into databases, spreadsheets, or analysis tools.
**Best Practices:**
- Test with a small URL set first to verify configuration
- Use residential proxies for better success rates
- Avoid scraping too many URLs simultaneously to prevent rate limiting
- Regularly update your URL list to track new properties
- Store outputs with timestamps for historical tracking
**Common Issues and Solutions:**
- **Missing data fields**: Some properties may not have all information available; the scraper handles this gracefully
- **Timeout errors**: Increase max_retries_per_url or check proxy configuration
- **Invalid URLs**: Verify URLs point to property detail pages, not search results
### Benefits and Real-World Applications
**Time Efficiency:**
Manual data collection from even 50 properties could take 3-4 hours. This scraper completes the same task in minutes, allowing you to focus on analysis rather than data entry.
**Practical Applications:**
*Market Analysis*: Real estate agencies can monitor competitor pricing, identify market trends, and adjust their strategies based on comprehensive market data.
*Investment Research*: Property investors can quickly build databases of available properties, analyze price-per-square-meter ratios, and identify undervalued opportunities.
*Trend Monitoring*: Data analysts can track how property features correlate with pricing, monitor neighborhood appreciation, and forecast market movements.
*Portfolio Management*: Property management companies can maintain updated databases of available rentals, benchmark their pricing, and optimize vacancy rates.
**Business Value:**
The structured data enables advanced analytics, supports data-driven decision-making, and provides competitive intelligence that would be nearly impossible to gather manually. The consistent format allows for seamless integration with existing business intelligence tools and CRM systems.
### Conclusion: Empower Your Real Estate Operations
The ArgeProp.com Property Details Scraper transforms the time-consuming process of property data collection into an efficient, automated workflow. By providing comprehensive, structured data from Argentina's leading real estate platform, it enables professionals to make faster, more informed decisions based on complete market intelligence.
Whether you're analyzing market trends, building property databases, or conducting competitive research, this scraper provides the data foundation you need. Start automating your property data collection today and gain the competitive advantage that comes from having complete, current market information at your fingertips.
## Related Actors
- [**Argenprop.com Property Search Scraper**](https://apify.com/ecomscrape/argenprop-property-search-scraper): A specialized data extraction tool engineered to harvest detailed property information from Argenprop's dominant Dutch real estate marketplace.
## Your feedback
We are always working to improve Actors' performance. So, if you have any technical feedback about Argenprop.com Property Details Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.
# Actor input Schema
## `urls` (type: `array`):
Add the URLs of the Specific property urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
## `max_retries_per_url` (type: `integer`):
Limit the number of retries for each URL if the scrape is detected as a bot or the page fails to load
## `proxy` (type: `object`):
Select proxies to be used by your scraper.
## Actor input object example
```json
{
"urls": [
"https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563"
],
"max_retries_per_url": 2,
"proxy": {
"useApifyProxy": false
}
}
```
# 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 = {
"urls": [
"https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563"
],
"max_retries_per_url": 2,
"proxy": {
"useApifyProxy": false
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("ecomscrape/argenprop-property-details-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 = {
"urls": ["https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563"],
"max_retries_per_url": 2,
"proxy": { "useApifyProxy": False },
}
# Run the Actor and wait for it to finish
run = client.actor("ecomscrape/argenprop-property-details-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 '{
"urls": [
"https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563"
],
"max_retries_per_url": 2,
"proxy": {
"useApifyProxy": false
}
}' |
apify call ecomscrape/argenprop-property-details-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,ecomscrape/argenprop-property-details-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 ` 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/fBSvbyQ5dHGq5efbX/builds/uPL7jYBMJB4aS14LM/openapi.json