Real Estate Insights with Somantic's GraphQL API on RapidAPI

If you’re looking to access extensive real estate data and perform advanced queries without building an extensive backend, somantic.net’s GraphQL API is the perfect solution. Hosted on RapidAPI, the Somantic API is tailored for developers, data scientists, and real estate businesses looking for a streamlined way to access real estate listings across Germany with powerful filtering, sorting, and statistical insights.

Why Use the Somantic Net API?

The API offers:

• Real-time and historical real estate data: Access active property listings, pricing, and rental data.
• Advanced filtering: Filter by region, type, platform, and transaction type (buy or rent).
• Data analytics: Get average prices and other relevant stats for informed decision-making.
• Pagination support: Manage large datasets with ease by specifying pages and limit results per query.
• GraphQL flexibility: Access only the specific data you need, optimizing performance and reducing unnecessary processing.

With this API, users can gain insights into the real estate market in Germany for various cities and states and tailor queries to focus on specific property types, regions, or marketplaces.

Getting Started

You’ll need a RapidAPI account and an API key to start using Somantic Net’s API. After subscribing to the API on RapidAPI, you can include your API key in requests, and you’re ready to explore.

Base URL

The API endpoint is:

https://somantic-net.p.rapidapi.com/graphql

Example Queries

1. Fetching Recent Apartments for Sale in Bavaria

If you want to pull the latest listings for apartments for sale in Bavaria from Kleinanzeigen, sorted by their posting date, you can use this query:

query AppartmentQuery {
  all_appartments(order_by: "-uptime_date", per_page: 10, page: 1, filters: {is_active: true, action: "kaufen", location: "bl-bayern", spider: "kleinanzeigen"}) {
    edges {
      node {
        uptime_date
        url
        square_meter
        price
      }
    }
  }
}

This request retrieves the 10 most recent listings and provides essential details like the listing URL, square meters, and price.

Pagination Example

To view the next page of results, simply increment the page parameter:

query AppartmentQuery {
  all_appartments(order_by: "-uptime_date", per_page:10, page: 2, filters: {is_active: true, action: "kaufen", location: "bl-bayern", spider: "kleinanzeigen"}) {
    edges {
      node {
        uptime_date
        url
        square_meter
        price
      }
    }
  }
}

2. Fetching Top Houses by Price in Baden-Württemberg

If you’re interested in listings for houses for sale in Baden-Württemberg from Immowelt, you can sort by price in descending order:

query HouseQuery {
  all_houses(order_by: "-price", per_page:20, page: 1, filters: {is_active: true, action: "kaufen", location: "bl-baden-wuerttemberg", spider: "immowelt"}) {
    edges {
      node {
        uptime_date
        url
        square_meter
        price
      }
    }
  }
}

This query retrieves the top 20 houses, allowing users to compare prices for large or high-end properties.

3. Calculating Average Price Per Square Meter for Apartments in Baden-Württemberg

To get an average price per square meter for active apartments in Baden-Württemberg, run the following query:

query ActiveApartmentAveragePriceBWQuery {
  avg_appartments(filters: {is_active: true, action: "kaufen", location: "bl-baden-wuerttemberg"}) {
    edges {
      node {
        avg_price_per_square_meter
      }
    }
  }
}

This provides a single aggregated metric to analyze the regional pricing trend.

4. Counting Active Apartments for Rent in Hamburg

If you want to know how many active apartment listings for rent are available in Hamburg, you can run:

query ActiveRentApartmentCountHHQuery {
  total_appartments_count(filters: {is_active: true, action: "mieten", location: "hamburg"})
}

This query gives you a quick count of available rental apartments in Hamburg, making it easier to gauge market availability.

Python Integration

For those looking to integrate these queries into a Python application, here’s a quick example using the requests library:

import requests

url = "https://somantic-net.p.rapidapi.com/graphql"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "somantic-net.p.rapidapi.com"
}
payload = {
    "query": "query AppartmentQuery { all_appartments(order_by: \"-uptime_date\", per_page:10, page: 2, filters: {action: \"kaufen\", location: \"bl-bayern\", spider: \"kleinanzeigen\"}) { edges { node { uptime_date url square_meter price som_model_price som_model_rent } } } }"
}

response = requests.post(url, json=payload, headers=headers)
print(response.json())

Replace "YOUR_RAPIDAPI_KEY" with your actual API key. This code sample demonstrates how to pull data from the API and access detailed information on listings with an emphasis on estimated price and model rent.

Conclusion

The Somantic Net GraphQL API on RapidAPI is a powerful tool for real estate data analytics, offering flexibility, speed, and efficiency. Whether you’re a developer building a real estate app, a data analyst conducting market research, or a real estate business looking for automated insights, this API provides the data needed to make well-informed decisions.

Ready to transform your real estate analysis? Try the Somantic Net API on RapidAPI today!