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# lbc-finder
id.json
logs/
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[codz]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
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lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py.cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
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profile_default/
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# For a library or package, you might want to ignore these files since the code is
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
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# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
#uv.lock
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celerybeat-schedule
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*.sage.py
# Environments
.env
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/site
# mypy
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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#.idea/
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# Abstra is an AI-powered process automation framework.
# Ignore directories containing user credentials, local state, and settings.
# Learn more at https://abstra.io/docs
.abstra/
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# Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore
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## v1.0.0
* Initial release

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MIT License
Copyright (c) 2025 Étienne Hodé
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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# lbc-finder
[![GitHub license](https://img.shields.io/github/license/etienne-hd/lbc?style=for-the-badge)](https://github.com/etienne-hd/lbc/blob/master/LICENSE)
**Stay notified when new ads appear on Leboncoin**
```python
from models import Search, Parameters
import lbc
def handle(ad: lbc.Ad, search_name: str):
print(f"[{search_name}] New ads!")
print(f"Title : {ad.subject}")
print(f"Price : {ad.price} €")
print(f"URL : {ad.url}")
print("-" * 40)
location = lbc.City(
lat=48.85994982004764,
lng=2.33801967847424,
radius=10_000, # 10 km
city="Paris"
)
CONFIG = [
Search(
name="Location Paris",
parameters=Parameters(
text="maison",
locations=[location],
category=lbc.Category.IMMOBILIER,
square=[200, 400],
price=[300_000, 700_000]
),
delay=60 * 5, # Check every 5 minutes
handler=handle
),
... # More
]
```
*lbc-finder is not affiliated with, endorsed by, or in any way associated with Leboncoin or its services. Use at your own risk.*
This project uses [lbc](https://github.com/etienne-hd/lbc), an unofficial library to interact with Leboncoin API.
## Features
* Advanced Search (text, category, price, location, square, etc.)
* Proxy Support for anonymity and bypassing rate limits
* Custom Logger with log file
* Configurable search interval (delay)
* Handler function triggered on new ads for full customization
* Multiple simultaneous searches with threading
* Easy integration with notifications (Discord, Telegram, email…) via handler
## Installation
Docker support will be added soon.
Required **Python 3.9+**
1. **Clone the repository**
```bash
git clone https://github.com/etienne-hd/lbc-finder.git
cd lbc-finder
```
2. **Install dependencies**
```bash
pip install -r requirements.txt
```
## Configuration
A [config.py](config.py) file is provided by default in the project, it contains a basic configuration.
Inside this file, you must define a `CONFIG` variable, which is an list of `Search` objects.
Each `Search` object should be configured with the rules for the ads you want to track.
For example, if you want to track ads for a **Porsche 944** priced between 0€ and 25,000€ anywhere in France:
```python
from models import Search, Parameters
Search(
name="Porsche 944",
parameters=Parameters(
text="Porsche 944",
category=lbc.Category.VEHICULES_VOITURES,
price=[0, 25_000]
),
delay=60 * 5, # Every 5 minutes
handler=handle,
proxy=None
)
```
### Name
A descriptive label for the Search.
It has no impact on the actual query, it’s only used to identify the search.
### Parameters
All available parameters are documented in the [lbc](https://github.com/etienne-hd/lbc) repository.
### Delay
The time interval between each search.
### Handler
This function is called whenever a new ad appears.
It must accept two parameters:
* the `Ad` object
* the name (label) of the search (e.g. **"Porsche 944"**)
```python
def handle(ad: lbc.Ad, search_name: str) -> None:
...
```
You can find example handlers in the [examples](examples/) folder.
### Proxy
You can configure a proxy, here is an example:
```python
from lbc import Proxy
from models import Search
proxy = Proxy(
host="127.0.0.1",
port=9444,
username="etienne",
password="123456"
)
Search(
name=...,
parameters=...,
delay=...,
handler=...,
proxy=proxy
)
```
## Usage
To run **lbc-finder**, simply start the `main.py` file:
```bash
python main.py
```
## 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](https://t.me/etienne_hd) or [Discord](https://discord.com/users/1153975318990827552) if you need help with scraping services or want to write a library.

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from models import Search, Parameters
import lbc
def handle(ad: lbc.Ad, search_name: str):
print(f"[{search_name}] New ads!")
print(f"Title : {ad.subject}")
print(f"Price : {ad.price} €")
print(f"URL : {ad.url}")
print("-" * 40)
location = lbc.City(
lat=48.85994982004764,
lng=2.33801967847424,
radius=10_000, # 10 km
city="Paris"
)
CONFIG = [
Search(
name="Location Paris",
parameters=Parameters(
text="maison",
locations=[location],
category=lbc.Category.IMMOBILIER,
square=[200, 400],
price=[300_000, 700_000]
),
delay=60 * 5, # Check every 5 minutes
handler=handle
),
]

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import lbc
import requests
from datetime import datetime
from typing import Final
WEBHOOK_URL: Final[str] = ...
def handle(ad: lbc.Ad, search_name: str) -> None:
timestamp = datetime.strptime(ad.index_date, "%Y-%m-%d %H:%M:%S").timestamp()
payload = {
"content": None,
"embeds": [
{
"title": ad.title,
"description": f"```{ad.body}```",
"url": ad.url,
"color": 14381568,
"author": {
"name": ad.user.name,
"icon_url": ad.user.profile_picture
},
"image": {
"url": ad.images[0] if ad.images else None
},
"fields": [
{
"name": "🕒 Publication",
"value": f"<t:{int(timestamp)}:R>",
"inline": True
},
{
"name": "💰 Price",
"value": f"`{ad.price}€`",
"inline": True
},
{
"name": "📍 Location",
"value": f"`{ad.location.city_label}`",
"inline": True
}
],
}
],
"username": search_name,
"attachments": []
}
requests.post(WEBHOOK_URL, json=payload)

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from searcher import Searcher
from config import CONFIG
def main() -> None:
searcher = Searcher(searches=CONFIG)
searcher.start()
if __name__ == "__main__":
main()

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from .search import Search
from .parameters import Parameters

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from typing import Optional, Union, List
from lbc import Category, Region, Department, City, OwnerType
from typing import overload
class Parameters:
@overload
def __init__(
self,
url: Optional[str] = None,
text: Optional[str] = None,
category: Category = Category.TOUTES_CATEGORIES,
locations: Optional[Union[List[Union[Region, Department, City]], Union[Region, Department, City]]] = None,
limit: int = 35,
limit_alu: int = 3,
page: int = 1,
owner_type: Optional[OwnerType] = None,
shippable: Optional[bool] = None,
search_in_title_only: bool = False,
**kwargs
): ...
def __init__(self, **kwargs):
self._kwargs = kwargs

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from lbc import Proxy, Ad
from .parameters import Parameters
from dataclasses import dataclass
from typing import Callable
@dataclass
class Search:
name: str
parameters: Parameters
delay: float
handler: Callable[[Ad, str], None]
proxy: Proxy = None

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lbc==1.0.9

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from .searcher import Searcher
from .logger import logger

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from .logger import logger
from typing import List, Final
import os
import json
MAX_ID: Final[int] = 10_000
class ID:
def __init__(self):
self._ids: List[str] = self._get_ids()
@property
def ids(self) -> List[str]:
return self._ids
def _get_ids(self) -> List[str]:
ids: List[str] = []
if os.path.exists("id.json"):
with open("id.json", "r") as f:
try:
ids = json.load(f)
except json.JSONDecodeError:
os.remove("id.json")
except:
logger.exception("An error occurred while attempting to open the id.json file.")
return ids
def add(self, id: str) -> bool:
if not id in self._ids:
self._ids.append(id)
with open("id.json", "w") as f:
json.dump(self._ids[-MAX_ID:], f, indent=3)
self._ids = self._ids[-MAX_ID:]
return True
return False

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import logging
import os
from datetime import datetime
# File management
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
file_path: str = os.path.join("logs", f"log_{timestamp}.log")
os.makedirs("logs", exist_ok=True)
# Config logging
logger = logging.getLogger("lbc-finder")
formatter = logging.Formatter('[%(asctime)s] [%(levelname)s] [%(threadName)s] %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(formatter)
logger.addHandler(stream_handler)
logger.setLevel(logging.INFO)
# Log File
file_handler = logging.FileHandler(file_path, mode='w', encoding='utf-8')
file_handler.setLevel(logging.WARNING)
file_handler.setFormatter(formatter)
logger.addHandler(file_handler)

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from models import Search
from lbc import Client, Sort
from .id import ID
from .logger import logger
import time
import threading
from typing import List, Union
class Searcher:
def __init__(self, searches: Union[List[Search], Search], request_verify: bool = True):
self._searches: List[Search] = searches if isinstance(searches, list) else [searches]
self._request_verify = request_verify
self._id = ID()
def _search(self, search: Search) -> None:
client = Client(proxy=search.proxy, request_verify=self._request_verify)
while True:
before = time.time()
try:
response = client.search(**search.parameters._kwargs, sort=Sort.NEWEST)
logger.debug(f"Successfully found {response.total} ad{'s' if response.total > 1 else ''}.")
ads = [ad for ad in response.ads if self._id.add(ad.id)]
if len(ads):
logger.info(f"Successfully found {len(ads)} new ad{'s' if len(ads) > 1 else ''}!")
for ad in ads:
search.handler(ad, search.name)
except:
logger.exception(f"An error occured.")
time.sleep(search.delay - (time.time() - before) if search.delay - (time.time() - before) > 0 else 0)
def start(self) -> bool:
if not len(self._searches):
logger.warning("No search rules have been set. Please create search rules in config.py (see example in README.md).")
return False
for search in self._searches:
threading.Thread(target=self._search, args=(search,), name=search.name).start()
time.sleep(5) # Add latency between each thread to prevent spam
return True