# Litinerant Scraper (`saswave/litinerant-scraper`) Actor Litinerant.fr scraper. Permet d'extraire les annonces legal d'entreprise sur plusieurs critère comme la ville, le type d'annonce et la date. Identifier facilement les créations d'entreprise ou les fermetures par exemple - **URL**: https://apify.com/saswave/litinerant-scraper.md - **Developed by:** [SASWAVE](https://apify.com/saswave) (community) - **Categories:** Social media, News, Lead generation - **Stats:** 1 total users, 1 monthly users, 96.7% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $25.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## 🏢 Litinerant Scraper – French Legal Company Announcements Extraction **Litinerant Scraper** is a powerful web scraping tool designed to extract legal company announcements from [litinerant.fr](https://www.litinerant.fr). It allows you to gather structured information about **company creations, closures, modifications, and other official announcements**. This tool is ideal for **market research, business intelligence, and legal data analysis**. With Litinerant Scraper, you can filter announcements by **city, type of announcement, or date**, enabling you to quickly identify **new company formations, closures, or capital changes**. All extracted data is returned in a clean, structured JSON format, ready for further processing or integration with **databases and analytics pipelines**. ### ✨ Features - Extract **legal company announcements** from Litinerant.fr - Filter by **city, type of announcement, or date** - Identify **new company creations, closures, and capital changes** - Collect key details: company name, address, capital, president, and more - Output is **structured JSON** ready for analytics, reporting, or database integration ### Ouput example ```json { "raw": "Par acte ssp en date de 15/04/2025, il a été constitué une SAS\nDénomination :\nSUSHI BOSQUET\nNom Commercial\n: OKASUSHI\nSiège Social\n: 38 AVENUE BOSQUET 75007 PARIS 07\nCapital\n: 5000 €\nObjet social\n: RESTAURATION TRADITIONNELLE, PLAT A EMPORTER, LIVRAISON A DOMICILE, DEGUSTATION SUR PLACE\nDurée\n: 99 ans\nPrésident\n: M. ZHANG GUORONG 68 RUE DES ECOLES BAT B ESC 3 93300 AUBERVILLIERS\nCession d'actions\n: LIBRE\nImmatriculation au RCS de PARIS\n[322647]", "url": "https://www.litinerant.fr/annonce/264364-sushi-bosquet-constitution-de-societe-par-action", "siège": "38 AVENUE BOSQUET 75007 PARIS 07", "forme": "", "dénomination": "SUSHI BOSQUET", "capital": "5000 €" } ```` ### 💡 Use Cases Business Intelligence: Monitor new company formations or closures Market Research: Track trends in company types, locations, and capital Legal Analytics: Automate collection of official announcements Data Integration: Feed structured JSON into databases, dashboards, or ML models ### 🚀 Getting Started Add the Litinerant Scraper Actor to your Apify account Configure filters such as city, announcement type, or date range Run the Actor and download structured JSON output Integrate the data into your analytics workflow or database ### 🛟 SUPPORT Share your runs with the developer team and create issues on error to help us improve actor quality. You might discover edge case we didn't test yet We stay available anytime # Actor input Schema ## `annonce_type` (type: `string`): Pour indiquer le type d'annonce, basez vous sur la colonne \ du site ## `date_str` (type: `string`): Extract results until this date included ## `city` (type: `string`): Select city ## `latest` (type: `boolean`): Set to true if you always want results ## `proxyConfiguration` (type: `object`): The best option is usually Automatic proxy. But you can also use your own proxies or no proxy ## Actor input object example ```json { "annonce_type": "constitution", "city": "76", "latest": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } } ``` # Actor output Schema ## `results` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "annonce_type": "constitution", "city": "76", "latest": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } }; // Run the Actor and wait for it to finish const run = await client.actor("saswave/litinerant-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "annonce_type": "constitution", "city": "76", "latest": True, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": [], }, } # Run the Actor and wait for it to finish run = client.actor("saswave/litinerant-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "annonce_type": "constitution", "city": "76", "latest": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } }' | apify call saswave/litinerant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=saswave/litinerant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Litinerant Scraper", "description": "Litinerant.fr scraper. Permet d'extraire les annonces legal d'entreprise sur plusieurs critère comme la ville, le type d'annonce et la date.\nIdentifier facilement les créations d'entreprise ou les fermetures par exemple", "version": "0.0", "x-build-id": "NNgJUnbEJbzwPZu82" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/saswave~litinerant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-saswave-litinerant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/saswave~litinerant-scraper/runs": { "post": { "operationId": "runs-sync-saswave-litinerant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/saswave~litinerant-scraper/run-sync": { "post": { "operationId": "run-sync-saswave-litinerant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "annonce_type": { "title": "Type d'annonce", "type": "string", "description": "Pour indiquer le type d'annonce, basez vous sur la colonne du site" }, "date_str": { "title": "Date limit: yyyy-mm-dd", "type": "string", "description": "Extract results until this date included" }, "city": { "title": "City filter", "enum": [ "", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", "69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", "80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", "91", "92", "93", "94", "95", "96", "98", "99", "100", "101", "206" ], "type": "string", "description": "Select city" }, "latest": { "title": "Get latest date if nothing today", "type": "boolean", "description": "Set to true if you always want results" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "The best option is usually Automatic proxy. But you can also use your own proxies or no proxy" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```