A powerful tool for extracting legal announcements from Figaro’s public listings. It helps uncover newly registered companies, understand their legal context, and gather structured business intelligence data. Ideal for sales prospecting, compliance checks, and market analysis.
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This scraper automates the extraction of legal announcements published on Le Figaro’s announcement portal. It gathers detailed company information, legal structures, capital data, and announcement content. It is designed for analysts, business developers, and anyone needing structured insights into new or updated company registrations.
- Capture rich legal announcement details including denomination, legal form, capital, and headquarters.
- Filter results by city, announcement type, or date for targeted insights.
- Retrieve full raw text plus PDF justification files when available.
- Identify newly registered companies to prioritize outreach.
- Output data is structured and ready for CRM or analytics workflows.
| Feature | Description |
|---|---|
| Targeted Legal Notice Extraction | Retrieves detailed attributes from company announcements such as name, legal form, capital, and registered address. |
| Multi-Criteria Filtering | Narrow results by date, announcement type, or city for precision targeting. |
| Full Raw Announcement Text | Provides the complete legal notice for verification and deeper analysis. |
| PDF Retrieval | Fetches downloadable PDF documents when available. |
| Optimized Prospecting | Quickly identify newly created or high-capital companies for B2B outreach. |
| Field Name | Field Description |
|---|---|
| url | Source URL of the legal announcement. |
| title | Official title of the announcement. |
| siège | The company’s registered headquarters address. |
| forme | Legal structure of the entity (e.g., SAS, SARL). |
| dénomination | Official company name or denomination. |
| capital | Reported registered capital amount. |
| raw | Full raw legal announcement text. |
| Direct link to the PDF justification file (if available). | |
| date | Announcement publication date. |
| city | City associated with the announcement. |
| annonce_type | Type of legal announcement such as constitution, modification, adjudication, etc. |
{
"url": "https://annonces-legales.lefigaro.fr/annonces-legales/careit-p-treffiagat-immatriculation-constitution/",
"title": "CAREIT P TREFFIAGAT – Immatriculation – Constitution",
"siège": "78 Avenue Raymond Poincaré 75116 Paris",
"forme": "Société par actions simplifiée unipersonnelle",
"dénomination": "CAREIT P TREFFIAGAT",
"capital": "1 000 euros",
"raw": "Suivant acte sous seing privé du 17/04/2025, a été constituée la société présentant les caractéristiques suivantes : ...",
"pdf": "Télécharger le justificatif PDF"
}
Annonce Legal Figaro Scraper/
├── src/
│ ├── runner.py
│ ├── extractors/
│ │ ├── figaro_parser.py
│ │ └── utils_format.py
│ ├── outputs/
│ │ └── exporters.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.txt
│ └── sample.json
├── requirements.txt
└── README.md
- Sales teams use it to identify newly created companies so they can prioritize outreach to high-value prospects.
- Market analysts use it to monitor legal announcements and detect industry trends or emerging business activities.
- Compliance teams use it to verify company status, legal form, and registration details for due-diligence workflows.
- Real estate or financial firms use it to track capital amounts and pinpoint investment-worthy entities.
Q: Can I filter results by announcement type or city? Yes, you can apply filters such as city, date, and announcement type to refine your search results.
Q: Do all announcements include a downloadable PDF? No, only some listings provide PDF justification files. When available, the scraper retrieves the link.
Q: What format is the output data in? Output is delivered as structured JSON, making it easy to import into analytics dashboards or CRM systems.
Q: Does it handle large volumes of announcements? Yes, the workflow is optimized to handle bulk extraction efficiently with stable performance.
Primary Metric: Average extraction time per record is optimized to deliver results within seconds, even when parsing detailed announcement text.
Reliability Metric: Consistently achieves a high success rate across diverse announcement types and cities due to robust parsing logic.
Efficiency Metric: Handles batch queries with minimal resource consumption through streamlined data extraction routines.
Quality Metric: Produces highly complete and precise datasets, capturing nuanced legal data such as capital amounts, legal forms, and raw announcement details.
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