# Pap.fr $1💰| URL Search | Keyword Filters | Rich Output (`abotapi/pap-fr-scraper`) Actor

From $1/1k. Extract property listings from pap.fr. Get fully-detailed listings with price, address, rooms, area, photo gallery, description, and arrondissement/department/region geography.

- **URL**: https://apify.com/abotapi/pap-fr-scraper.md
- **Developed by:** [Abot API](https://apify.com/abotapi) (community)
- **Categories:** Real estate, Developer tools, Automation
- **Stats:** 27 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $1.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## PAP.fr Scraper

Extract property listings from pap.fr: *De Particulier à Particulier*, France's largest owner-to-owner real-estate platform. Get fully-detailed listings with price, address, rooms, area, photo gallery, description, and arrondissement/department/region geography.

### Why This Scraper?

- **20+ fields per listing.** Price (numeric + formatted), rooms (pièces), living area, street address, postcode, city, arrondissement, department, region, full photo gallery, description, PAP reference number, and more.
- **Two input modes.** Pick a French city and department code from the form, or paste any pap.fr search URL you already refined in your browser.
- **Rich filter set.** Buy or rent, property type, minimum rooms (pièces), sort order - all passed straight to pap.fr so the results are exactly what the site would show.
- **Auto pagination.** Walks every result page forward to the limit you set.
- **Both Buy (Vente) and Rent (Location).** Apartments, houses, plots, parking, and commercial property.
- **Owner-to-owner exclusive.** PAP forbids agent listings - every record is a private-owner listing you won't find on the agent-heavy aggregators.

### Data You Get

| Field | Example |
|---|---|
| Title | `Vente appartement 3 pièces 57 m² Paris 18E` |
| Price | `590 000` (numeric) + `590.000 €` (formatted) |
| Rooms (pièces) | `3` |
| Living area | `57 m²` |
| Street address | `Rue Muller, 75018 Paris` |
| Postcode | `75018` |
| City | `Paris 18e` |
| Arrondissement | `Paris 18e` |
| Department | `Paris` |
| Region | `Île-de-France` |
| Reference | `G17/2664` (PAP internal reference) |
| Latitude / Longitude | `48.8358`, `2.2899` (when `fetchDetails=true`) |
| Energy class (DPE) | `A`-`G` (when `fetchDetails=true`) |
| GHG class (GES) | `A`-`G` (when `fetchDetails=true`) |
| Active status | `true` live / `false` delisted (when `fetchDetails=true`) |
| Images | Full gallery, high-res URLs |
| Description | Full seller description (when `fetchDetails=true`) |
| Scraped at | ISO timestamp |

### How to Use

#### Search by Location

Enter a French city and its 2-digit department code. The scraper resolves the pap.fr geo-id automatically.

```json
{
  "mode": "filter",
  "locations": [
    { "city": "Paris", "department": "75" }
  ],
  "listingType": "Buy",
  "propertyType": "Apartment",
  "maxPages": 10
}
```

#### Search with Filters

```json
{
  "mode": "filter",
  "locations": [{ "city": "Lyon", "department": "69" }],
  "listingType": "Rent",
  "propertyType": "Apartment",
  "roomsMin": 3,
  "sortBy": "PriceAsc",
  "maxPages": 10
}
```

#### Multiple Cities

```json
{
  "mode": "filter",
  "locations": [
    { "city": "Paris", "department": "75" },
    { "city": "Lyon", "department": "69" },
    { "city": "Marseille", "department": "13" },
    { "city": "Bordeaux", "department": "33" },
    { "city": "Nice", "department": "06" }
  ],
  "listingType": "Buy",
  "propertyType": "House",
  "maxPages": 5
}
```

#### Direct URLs with auto pagination

Refine a search in your browser (including price / surface filters which aren't exposed in the form here), copy the URL, paste it here. If the URL ends with `-N` (page number), scraping starts from page N and walks forward.

```json
{
  "mode": "url",
  "urls": [
    "https://www.pap.fr/annonce/vente-appartements-paris-75-g439-3-pieces-tri-prix-asc"
  ],
  "maxPages": 20
}
```

### Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `mode` | string | `filter` | `filter` for city + department inputs, or `url` for direct URLs |
| `locations` | array | Paris / 75 | City + 2-digit department pairs (Filter mode only) |
| `urls` | string\[] | example URL | pap.fr search URLs (URL mode only); honors trailing `-N` as start page |
| `listingType` | string | `Buy` | `Buy` (Vente) or `Rent` (Location) - Filter mode only |
| `propertyType` | string | `Apartment` | `Apartment`, `House`, `Plot`, `Parking`, or `CommercialProperty` (Filter mode only) |
| `roomsMin` | number | no limit | Minimum pièces (1-5, where 5 means 5+) - Filter mode only |
| `sortBy` | string | `Default` | `Default`, `PriceAsc`, `PriceDesc`, `SurfaceAsc`, `SurfaceDesc`, `DateAsc` (Filter mode only) |
| `maxPages` | number | (empty) | Max pages per search. Leave empty to walk every result page until pap.fr has no next page for that search. |
| `maxListings` | number | `20` | Hard cap across the whole run. `0` = unlimited (still bounded by `maxPages`). |
| `fetchDetails` | boolean | `false` | Visit each listing's detail page for full description + street address + reference + high-res photo gallery |
| `resumeFromRunId` | string | (empty) | A previous run ID or dataset ID to continue a full-catalogue walk across separate runs. Listings already collected there (matched by `id`) are skipped, so this run only saves the new ones. |
| `incrementalMode` | boolean | `false` | Turn on for recurring (e.g. daily/weekly) monitoring of the SAME search. Off by default — no existing user's behavior or bill changes until you opt in. |
| `stateKey` | string | (empty) | Optional name for the monitoring campaign. Leave empty to auto-derive a key from every search input (mode, locations/URLs, listing/property type, rooms, sort, `fetchDetails`) — different searches then never mix state. |
| `emitUnchanged` | boolean | `false` | Incremental mode only. Also return listings unchanged since the last run, marked `UNCHANGED`. **Returns and bills extra rows** you already have. |
| `emitExpired` | boolean | `false` | Incremental mode only. Also return listings that disappeared since the last run, marked `EXPIRED`. Only produced after a run fully scans the tracked search (not when `maxPages`/`maxListings` capped it, a block stopped it early, or `resumeFromRunId` was used). **Returns and bills extra synthetic rows.** |
| `proxy` | object | Apify RES + FR | Proxy config, French residential recommended |

#### Resuming a full-catalogue walk

For an unbounded pull (`maxPages` empty, `maxListings: 0`), two things protect a long run:

- **`resumeFromRunId`** lets you continue in a brand-new run: paste the ID of a previous run (or its dataset), and this run skips every listing `id` already saved there, appending only new listings.
- A **checkpoint** is saved automatically as the run progresses. If the run is interrupted by an Apify platform migration or you click **Resurrect** on a failed run, it picks back up from where it left off in the *same* run, without re-saving (or re-charging for) listings it already collected. No input is needed for this; it's automatic.

#### Recurring / incremental monitoring

`resumeFromRunId` continues **one specific interrupted run**. For running the **same search again and again** (e.g. daily/weekly) and getting only what changed, use `incrementalMode` instead:

- Turn on `incrementalMode`. The first run returns everything as `NEW`. Every later run against the same search (same `stateKey`, or the same auto-derived scope) classifies each listing as `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, or `EXPIRED` and — by default — only returns `NEW`/`UPDATED`/`REAPPEARED` rows, so you're billed only for what actually changed.
- Set `stateKey` to name the campaign explicitly (or to deliberately share state across two differently-configured runs). Leave it empty to let the actor derive one automatically from the search itself.
- `emitUnchanged` and `emitExpired` are both off by default because turning them on **bills extra rows** — a full re-snapshot (`emitUnchanged`) or synthetic delisting rows (`emitExpired`) on top of the real changes.
- `emitExpired` only fires after a run proves it scanned the **entire** tracked search with nothing capping it short (no `maxPages`/`maxListings` ceiling reached, no block, no `resumeFromRunId`). Otherwise the run can't tell "this listing is gone" from "I just didn't get to its page" — the log line says why EXPIRED detection was skipped that run.
- Incremental state is kept in Apify's key-value store, separate from `resumeFromRunId`'s checkpoint, and layered over the same listing-id dedup the checkpoint already uses — the two features don't duplicate any tracking.

### Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step **after** the scrape — the Apify dataset is never changed.

**What gets written to the connector:** a condensed, human-readable **summary** of each record — not the full JSON. Each item becomes one entry with a **title** (the listing's name / address) and its key fields flattened to plain text. Nested objects are collapsed to their main value and long lists are trimmed. The **complete record always stays in the Apify dataset**.

1. Authorize a connector once under **Apify → Settings → Integrations** (Notion, Linear, Airtable, or Apify).
2. Select it in the **"Pipe results into your apps"** input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For **Notion**, also set `notionParentPageUrl` to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

### Output Example

```json
{
  "id": "<listing-id>",
  "url": "<listing-url>",
  "listingType": "Buy",
  "propertyType": "Apartment",
  "title": "<listing-title>",
  "priceValue": 590000,
  "priceCurrency": "EUR",
  "priceDisplay": "590.000 €",
  "rooms": 3,
  "livingSpace": 57,
  "description": "<full seller description>",
  "streetAddress": "<street, postcode city>",
  "city": "<city>",
  "postcode": "<zip>",
  "arrondissement": "<arrondissement>",
  "department": "<department>",
  "region": "<region>",
  "latitude": 48.84,
  "longitude": 2.29,
  "energyClass": "D",
  "ghgClass": "D",
  "isActive": true,
  "reference": "<PAP reference>",
  "imageCount": 18,
  "images": ["<image-url-1>", "<image-url-2>"],
  "additionalProperties": {
    "Type de bien": "Appartement",
    "Ascenseur": "Oui"
  },
  "scrapedAt": "2026-04-22T10:00:00.000Z"
}
```

With `incrementalMode` on, each row also carries:

```json
{
  "changeType": "UPDATED",
  "changedFields": ["priceValue", "priceDisplay"],
  "firstSeenAt": "2026-04-01T09:00:00.000Z",
  "lastSeenAt": "2026-04-22T10:00:00.000Z"
}
```

These four fields are absent entirely when `incrementalMode` is off — the default output shape is unchanged.

### Plan requirement

This actor needs a residential proxy. Two options:

- **Paid Apify plan** (Starter and above). Keep the default. EU residential is preferred; FR may have issues, so the default pins IT.
- **Bring your own proxy** (any plan, including Free). Uncheck "Use Apify proxy" and paste your own residential URLs (Bright Data, Oxylabs, SmartProxy, IPRoyal, etc.).

If the primary proxy is unavailable, the scraper auto-falls back to a managed backup pool.

### Common Department Codes

| Code | Name | Biggest city |
|---|---|---|
| 75 | Paris | Paris |
| 69 | Rhône | Lyon |
| 13 | Bouches-du-Rhône | Marseille |
| 33 | Gironde | Bordeaux |
| 06 | Alpes-Maritimes | Nice |
| 31 | Haute-Garonne | Toulouse |
| 59 | Nord | Lille |
| 44 | Loire-Atlantique | Nantes |
| 67 | Bas-Rhin | Strasbourg |
| 34 | Hérault | Montpellier |
| 35 | Ille-et-Vilaine | Rennes |
| 38 | Isère | Grenoble |

### About

Built and maintained for reliable, cost-effective scraping of PAP.fr. Report any issues or ideas in the Apify Store listing.

# Actor input Schema

## `mode` (type: `string`):

Filter mode = pick property type + city + department. URL mode = paste any pap.fr search URL already refined in a browser (recommended for price/surface filters since pap.fr encodes those only after you've interacted with the search form).

## `locations` (type: `array`):

Enter a French city name. The 2-digit department code is auto-derived from the city and is only required to disambiguate names shared by multiple communes (e.g. Saint-Denis exists in both 93 and 974).

## `listingType` (type: `string`):

Pick Vente (Buy) or Location (Rent). Filter mode only.

## `propertyType` (type: `string`):

What kind of property to search for. Filter mode only.

## `roomsMin` (type: `integer`):

Minimum number of rooms (pièces). PAP encodes rooms as a URL path segment, so this is applied to the generated URL. Filter mode only.

## `sortBy` (type: `string`):

How to order results. Filter mode only — in URL mode the sort is taken from your pasted URL. Default = most recent first (PAP's own default).

## `urls` (type: `array`):

One or more full pap.fr search URLs. Tip: open pap.fr in your browser, pick property type + location + any price/surface filters, then paste the resulting URL here. If the URL ends with `-N` (page number), scraping starts at page N and walks forward.

## `maxPages` (type: `integer`):

How many result pages to walk per location / URL. PAP returns 20 listings per page. Leave empty to walk every result page.

## `maxListings` (type: `integer`):

Hard cap across the whole run. 0 = unlimited (bounded only by Max pages).

## `fetchDetails` (type: `boolean`):

Adds lat/lng, DPE/GES energy classes, street address, full seller description, reference number, bedrooms, floor, HOA charges, property tax, heating type, and the full high-res photo gallery. Turn off for a faster run with just the SERP-level fields (price, rooms, m², city, primary photo).

## `resumeFromRunId` (type: `string`):

Paste a previous run ID or dataset ID to continue a full-catalogue walk across separate runs. Listings already collected there (matched by listing id) are skipped, so this run only saves the new ones. Leave empty for a normal fresh run. For recurring monitoring of the same search instead, use Incremental mode below.

## `incrementalMode` (type: `boolean`):

Turn this on for daily/weekly recurring monitoring of the same search. The first run returns all matching listings as NEW. Later runs return only NEW, UPDATED, and REAPPEARED listings by default. Turn on "Emit unchanged listings" or "Emit expired listings" only when you also want those rows returned (and billed). State is kept separately per search (location/URL, listing/property type, rooms, sort, and detail-fetch setting) — use State key below to name or deliberately share a monitoring campaign. To continue one specific interrupted run instead, use Resume from a previous run above.

## `stateKey` (type: `string`):

Optional. Name this monitoring campaign to keep its state stable, or to deliberately share state across differently-configured runs. Leave empty to let the actor derive a key automatically from the search inputs above (mode, locations/URLs, listing/property type, rooms, sort, detail-fetch setting) — different searches then never mix state with each other.

## `emitUnchanged` (type: `boolean`):

Off by default. Turn on to also return listings that have not changed since the last run, marked UNCHANGED. This returns — and bills — extra rows you already have, so leave it off unless you specifically want the full snapshot every run.

## `emitExpired` (type: `boolean`):

Off by default. Turn on to also return listings that were present in a previous run but are no longer found, marked EXPIRED. Only produced once a run has fully scanned the tracked search — not when Max pages/Max listings capped it, a block stopped it early, or Resume was used. This returns — and bills — extra synthetic rows, so leave it off unless you need expiry tracking.

## `proxy` (type: `object`):

EU residential proxy is preferred. FR may have issues; default pins IT.

## `mcpConnectors` (type: `array`):

Optionally send the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. Authorize a connector once under Apify → Settings → Integrations, then select it here. The connector receives a condensed, human-readable summary per item (title + key fields), not the full JSON — the complete record stays in the dataset. Leave empty to skip. Supported: Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/sse), Airtable (https://mcp.airtable.com/mcp), Apify (https://mcp.apify.com).

## `notionParentPageUrl` (type: `string`):

URL (or id) of the Notion page under which item pages are created. Required to enable the Notion export; ignored by other connectors.

## `maxNotifyListings` (type: `integer`):

Cap on items written to each connector per run. Does not affect the dataset.

## Actor input object example

```json
{
  "mode": "filter",
  "locations": [
    {
      "city": "Paris"
    }
  ],
  "listingType": "Buy",
  "propertyType": "Apartment",
  "sortBy": "Default",
  "urls": [
    "https://www.pap.fr/annonce/vente-appartements-paris-75-g439"
  ],
  "maxListings": 20,
  "fetchDetails": true,
  "incrementalMode": false,
  "emitUnchanged": false,
  "emitExpired": false,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IT"
  },
  "maxNotifyListings": 50
}
```

# Actor output Schema

## `overview` (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 = {
    "locations": [
        {
            "city": "Paris"
        }
    ],
    "urls": [
        "https://www.pap.fr/annonce/vente-appartements-paris-75-g439"
    ],
    "incrementalMode": false,
    "emitUnchanged": false,
    "emitExpired": false,
    "proxy": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "IT"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("abotapi/pap-fr-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 = {
    "locations": [{ "city": "Paris" }],
    "urls": ["https://www.pap.fr/annonce/vente-appartements-paris-75-g439"],
    "incrementalMode": False,
    "emitUnchanged": False,
    "emitExpired": False,
    "proxy": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "IT",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("abotapi/pap-fr-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 '{
  "locations": [
    {
      "city": "Paris"
    }
  ],
  "urls": [
    "https://www.pap.fr/annonce/vente-appartements-paris-75-g439"
  ],
  "incrementalMode": false,
  "emitUnchanged": false,
  "emitExpired": false,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IT"
  }
}' |
apify call abotapi/pap-fr-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,abotapi/pap-fr-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/XgIbs7Xhlg08vKaLX/builds/MXsXdm6RVXfQqW9pB/openapi.json