# Avis Vérifiés Reviews (`avistor_dev/avis-verifies-reviews`) Actor Avis Vérifiés Review Scraper extracts customer reviews from Avis Vérifiés for any brand. Input a review page URL and number of pages to scrape, and get structured data with reviewer names, ratings, dates, review texts, and brand responses. Ideal for reputation monitoring and analysis! 🚀 - **URL**: https://apify.com/avistor\_dev/avis-verifies-reviews.md - **Developed by:** [Avistor dev](https://apify.com/avistor_dev) (community) - **Categories:** E-commerce, Integrations, Other - **Stats:** 21 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $10.00/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 ## **Avis Vérifiés Review Scraper** 🚀 **Extract Verified Customer Reviews from Avis Vérifiés** This **Apify Actor** allows you to scrape **customer reviews from Avis Vérifiés** for any brand. Provide a brand’s review page URL (e.g., `https://www.avis-verifies.com/avis-clients/carglass.fr`) and the number of pages to scrape. The Actor then extracts structured data, including reviewer names, ratings, dates, review texts, and brand responses. --- ### **✨ Features** - **Scrape customer reviews** 📝 – Extract verified reviews with details like reviewer name, rating, review text, and date. - **Capture brand responses** 💬 – Get official replies from brands, if available. - **Handle pagination** 🔄 – Navigate multiple pages automatically until the specified limit is reached or no more reviews are available. - **Structured data output** 📊 – Store results in Apify datasets for easy export and analysis. --- ### **🛠 How It Works** 1. **Actor receives input** – You provide: - `url` → The Avis Vérifiés review page URL. - `numberOfPages` → Number of review pages to scrape. 2. **Fetch and parse reviews** – The Actor: - Loads the page content using **Axios**. - Extracts review data with **Cheerio**. - Handles pagination until the given limit or when no more reviews are available. 3. **Save results** – The extracted data is stored in an Apify dataset for easy access. #### **📌 Example Output** ```json [ { "reviewer": "John D.", "rating": 5, "date": "04/03/2025", "reviewText": "Great service and fast intervention!", "responseText": "Thank you for your feedback! - Carglass Team" } ] ```` #### **📜 Legal Disclaimer** - This scraper is intended for ethical and legal use only. The user is solely responsible for ensuring compliance with all applicable laws, including GDPR and website terms of service. - We do not store, process, or distribute any scraped data—users are responsible for handling the data they collect. - Avis Vérifiés and any brand names mentioned are trademarks of their respective owners. This Actor is not affiliated with or endorsed by Avis Vérifiés. - Misuse of this tool for unauthorized scraping or data harvesting may result in legal consequences. Please consult a legal expert before use. - By using this Actor, you agree to these terms and acknowledge that you are responsible for how you use the data. 🚀 # Actor input Schema ## `url` (type: `string`): The URL of the Avis Vérifiés review page you want to scrape. ## `numberOfPages` (type: `integer`): Number of review pages to scrape. ## Actor input object example ```json { "url": "https://www.avis-verifies.com/avis-clients/carglass.fr", "numberOfPages": 1 } ``` # 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 = { "url": "https://www.avis-verifies.com/avis-clients/carglass.fr", "numberOfPages": 1 }; // Run the Actor and wait for it to finish const run = await client.actor("avistor_dev/avis-verifies-reviews").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 = { "url": "https://www.avis-verifies.com/avis-clients/carglass.fr", "numberOfPages": 1, } # Run the Actor and wait for it to finish run = client.actor("avistor_dev/avis-verifies-reviews").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 '{ "url": "https://www.avis-verifies.com/avis-clients/carglass.fr", "numberOfPages": 1 }' | apify call avistor_dev/avis-verifies-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=avistor_dev/avis-verifies-reviews", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Avis Vérifiés Reviews", "description": "Avis Vérifiés Review Scraper extracts customer reviews from Avis Vérifiés for any brand. Input a review page URL and number of pages to scrape, and get structured data with reviewer names, ratings, dates, review texts, and brand responses. Ideal for reputation monitoring and analysis! 🚀", "version": "0.0", "x-build-id": "msTsGzmN0riSILxRZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/avistor_dev~avis-verifies-reviews/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-avistor_dev-avis-verifies-reviews", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/avistor_dev~avis-verifies-reviews/runs": { "post": { "operationId": "runs-sync-avistor_dev-avis-verifies-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/avistor_dev~avis-verifies-reviews/run-sync": { "post": { "operationId": "run-sync-avistor_dev-avis-verifies-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "url", "numberOfPages" ], "properties": { "url": { "title": "URL of the Avis Vérifiés brand review page", "type": "string", "description": "The URL of the Avis Vérifiés review page you want to scrape." }, "numberOfPages": { "title": "Number of review pages", "type": "integer", "description": "Number of review pages to scrape." } } }, "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 } } } } } } } } } } ```