# Ademe DPE Properties and Details Scraper (`realestateapi/ademe-dpe-properties-and-details-scraper`) Actor

Ademe DPE Properties and Details Scraper — Read bounded public French energy-performance diagnostics from the official ADEME Data Fair dataset, with DPE/GES classes, address, surface, construction, energy-use, emissions, and geolocation fields.

- **URL**: https://apify.com/realestateapi/ademe-dpe-properties-and-details-scraper.md
- **Developed by:** [Real Estate API](https://apify.com/realestateapi) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.99 / 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/actors/running/actors-in-store.md#pay-per-event

## 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

## Ademe DPE Properties and Details Scraper

This Actor reads bounded rows from the official ADEME Data Fair `dpe03existant` dataset. It exposes public DPE/GES classes, address, city, surface, construction year, energy use, emissions, property type, validity date, and coordinates. Optional filters are applied locally after fetching a bounded public result page.

It uses no credentials, private endpoint, proxy rotation, challenge solving, or remote Apify operation. Source-backed DPE certificates are the Actor's real property records (the French DPE certificate itself is a diagnostic); access and failure diagnostics are never written as dataset records. A source failure before any record is saved ends the run as `status=FAILED`, `runStatus=FAILED`, with a nonzero process exit. Partial source-backed results keep native `status=SUCCEEDED` and exit zero while `runStatus` and `collectionStatus` report `PARTIAL`. A valid empty response reports `status=SUCCEEDED` and `runStatus=COMPLETED` with no dataset rows.

`fieldCoverage` lists only populated ADEME property fields, excluding Actor metadata. `dataQuality.sourceBackedFields` and `dataQuality.emptyFields` are calculated from those fields for each new record. Historical rows retain their original coverage metadata.

### Input

```json
{
  "limit": 5,
  "query": "Paris",
  "city": "Paris",
  "dpeClass": "C",
  "includeRaw": false,
  "requestTimeoutSecs": 30
}
```

Supported filters include city, postal code, department, DPE/GES class, surface bounds, and construction year.

### Offline verification

```bash
npm install
npm test
npm run lint
apify validate-schema
```

#### Dependency security

The locked dependency graph overrides basic-ftp with the patched 6.2.1 release. The SDK’s unpatched HTTP cache policy is replaced with the readable local vendor/noncaching-http-policy adapter, which refuses cache reads and writes and forces fresh network responses. This is an explicit removal of caching, not a claimed upstream security patch. Source transports, permission gates and request limits are unchanged. npm run test:dependencies checks cross-user cache isolation, imported stale policy rejection, FTP integration methods and adversarial listing parsing. Cloud builds run npm audit --omit=dev --audit-level=low against the installed production graph.

# Actor input Schema

## `limit` (type: `integer`):

Maximum diagnostics to emit after public filters.

## `query` (type: `string`):

Optional ADEME full-text query passed to the public Data Fair endpoint.

## `city` (type: `string`):

Optional exact city filter applied to public nom_commune_ban/nom_commune fields.

## `postalCode` (type: `string`):

Optional exact postal-code filter.

## `department` (type: `string`):

Optional French department-code filter.

## `dpeClass` (type: `string`):

Optional DPE energy class filter A-G.

## `gesClass` (type: `string`):

Optional GES class filter A-G.

## `minSurface` (type: `number`):

Optional minimum habitable surface.

## `maxSurface` (type: `number`):

Optional maximum habitable surface.

## `yearBuilt` (type: `integer`):

Optional exact construction-year filter.

## `includeRaw` (type: `boolean`):

Retain the complete public source row for each record.

## `requestTimeoutSecs` (type: `integer`):

Timeout for the public Data Fair request.

## Actor input object example

```json
{
  "limit": 25,
  "includeRaw": false,
  "requestTimeoutSecs": 30
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

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

// Prepare Actor input
const input = {};

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

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("realestateapi/ademe-dpe-properties-and-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 '{}' |
apify call realestateapi/ademe-dpe-properties-and-details-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,realestateapi/ademe-dpe-properties-and-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 <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/HY0jRuWNlJz7hAwHY/builds/G8zZEuhREWTXGxxW8/openapi.json