lbc

Unofficial client for Leboncoin API

import lbc

client = lbc.Client()

location = lbc.City( 
    lat=48.85994982004764,
    lng=2.33801967847424,
    radius=10_000, # 10 km
    city="Paris"
)

result = client.search(
    text="maison",
    locations=[location],
    page=1,
    limit=35,
    sort=lbc.Sort.NEWEST,
    ad_type=lbc.AdType.OFFER,
    category=lbc.Category.IMMOBILIER,
    square=[200, 400],
    price=[300_000, 700_000]
)

for ad in result.ads:
    print(ad.url, ad.subject, ad.price)

lbc is not affiliated with, endorsed by, or in any way associated with Leboncoin or its services. Use at your own risk.

Installation

Required Python 3.9+

pip install lbc

Usage

Start with the examples to quickly understand how to use the library in real-world scenarios.

Client

To create client you need to use lbc.Client class

import lbc

client = lbc.Client()

Proxy

You can also configure the client to use a proxy by providing a Proxy object:

# Setup proxy1
proxy1 = lbc.Proxy(
	host="127.0.0.1",
	port=12345,
	username="username",
	password="password",
	scheme="http"
)

# Initialize client with proxy1
client = lbc.Client(proxy=proxy1)

# Setup proxy2
proxy2 = lbc.Proxy(
	host="127.0.0.1",
	port=23456,
)

# Change client proxy to proxy2
client.proxy = proxy2

# Remove proxy
client.proxy = None

Search

To perform a search, use the client.search method.

This function accepts keyword arguments (**kwargs) to customize your query. For example, if you're looking for houses that include both land and parking, you can specify:

real_estate_type=["3", "4"]

These values correspond to what you’d find in a typical Leboncoin URL, like:

https://www.leboncoin.fr/recherche?category=9&text=maison&...&real_estate_type=3,4

Here's a complete example of a search query:

client.search(
    text="maison",
    locations=[location],
    page=1,
    limit=35,
    limit_alu=0,
    sort=lbc.Sort.NEWEST,
    ad_type=lbc.AdType.OFFER,
    category=lbc.Category.IMMOBILIER,
    owner_type=lbc.OwnerType.ALL,
    search_in_title_only=True,
    square=[200, 400],
    price=[300_000, 700_000],
)

Alternatively

You can also perform search using a full Leboncoin URL:

client.search(
    url="https://www.leboncoin.fr/recherche?category=9&text=maison&locations=Paris__48.86023250788424_2.339006433295173_9256&square=100-200price=500000-1000000&rooms=1-6&bedrooms=3-6&outside_access=garden,terrace&orientation=south_west&owner_type=private",
    page=1,
    limit=35
)

If url is provided, it overrides other keyword parameters such as text, category, locations, etc. However, pagination parameters like page, limit, and limit_alu are still applied.

Location

The locations parameter accepts a list of one or more location objects. You can use one of the following:

• lbc.Region(...)
• lbc.Department(...)
• lbc.City(...)

Each one corresponds to a different level of geographic granularity.

City example

location = lbc.City(
    lat=48.85994982004764,
    lng=2.33801967847424,
    radius=10_000,  # in meters
    city="Paris"
)

Region / Department example

from lbc import Region, Department

region = Region.ILE_DE_FRANCE
department = Department.PARIS

403 Error

If you encounter a 403 Forbidden error, it usually means your requests are being blocked by Datadome. To resolve this:

• Try reducing the request frequency (add delays between requests).
• If you're using a proxy, make sure it is clean and preferably located in France.

Using residential or mobile proxies can also help avoid detection.

License

This project is licensed under the MIT License.

Support

<a href="https://www.buymeacoffee.com/etienneh" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>

You can contact me via Telegram or Discord if you need help with scraping services or want to write a library.