# Thisisl Reviews Spider (`getdataforme/thisisl-reviews-spider`) Actor Thisisl Reviews Spider scrapes customer reviews from multiple URLs, extracting ratings, comments, and dates into structured JSON. Perfect for market research and sentiment analysis, it delivers high accuracy, scalability, and seamless Apify integration with robust error handling. - **URL**: https://apify.com/getdataforme/thisisl-reviews-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Agents, E-commerce - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## Thisisl Reviews Spider Thisisl Reviews Spider is a powerful Apify Actor designed to scrape customer reviews from specified URLs, extracting valuable insights such as ratings, comments, and dates. It transforms unstructured web data into structured JSON format, enabling easy analysis and integration into your workflows. Whether you're conducting market research or monitoring brand sentiment, this tool delivers reliable, high-quality data with minimal setup. ### Features - **Comprehensive Review Extraction**: Captures key details like review text, ratings, reviewer names, and timestamps from product or service pages. - **Multi-URL Support**: Processes multiple URLs in a single run, allowing batch scraping for efficiency. - **High Data Accuracy**: Employs robust parsing to minimize errors and ensure clean, actionable data. - **Fast and Scalable**: Optimized for performance, handling large volumes of reviews quickly without compromising reliability. - **Structured JSON Output**: Delivers results in a consistent, machine-readable format for seamless integration with analytics tools. - **Error-Resilient**: Includes built-in handling for common web scraping challenges like dynamic content or rate limits. - **Apify Integration**: Fully compatible with Apify's ecosystem for easy deployment, monitoring, and data export. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | Urls | array | Yes | A list of URLs from which to scrape reviews. Each URL should point to a page containing reviews (e.g., product review sections). The spider will extract reviews from these pages. | ["https://example.com/product-reviews", "https://anotherexample.com/reviews"] | ### Example Usage To run the Thisisl Reviews Spider, provide an input JSON with the required URLs. Here's an example: **Input JSON:** ```json { "Urls": [ "https://example.com/product-reviews", "https://anotherexample.com/reviews" ] } ```` **Example Output JSON:** ```json [ { "url": "https://example.com/product-reviews", "reviews": [ { "reviewer": "John Doe", "rating": 5, "text": "Excellent product, highly recommend!", "date": "2023-10-01" }, { "reviewer": "Jane Smith", "rating": 4, "text": "Good value for money, but could be improved.", "date": "2023-09-15" } ] }, { "url": "https://anotherexample.com/reviews", "reviews": [ { "reviewer": "Alice Johnson", "rating": 3, "text": "Average experience, nothing special.", "date": "2023-08-20" } ] } ] ``` ### Use Cases - **Market Research and Analysis**: Gather customer feedback to identify trends, preferences, and pain points in your industry. - **Competitive Intelligence**: Compare reviews across competitors' products to benchmark performance and pricing. - **Price Monitoring**: Analyze review sentiments alongside pricing data to optimize your own offerings. - **Content Aggregation**: Collect reviews for content creation, such as blog posts or social media campaigns. - **Academic Research**: Extract data for studies on consumer behavior, sentiment analysis, or product lifecycle. - **Business Automation**: Integrate review data into dashboards for real-time monitoring of brand reputation. ### Installation and Usage 1. Search for "Thisisl Reviews Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The output is a JSON array of objects, where each object corresponds to a scraped URL. Each URL object contains a "url" field and a "reviews" array. The "reviews" array consists of objects with fields like "reviewer" (string), "rating" (number, e.g., 1-5), "text" (string), and "date" (string in YYYY-MM-DD format). This structure ensures easy parsing and analysis, with each review providing comprehensive details for insights. ### Error Handling The Actor includes robust error handling for common issues such as invalid URLs, network timeouts, or CAPTCHA blocks. If a URL fails to load or parse, it will be logged with an error message, and the run will continue with other URLs. Check the Apify console for detailed logs. For persistent issues, ensure URLs are accessible and review-based. ### Rate Limiting and Best Practices Apify enforces rate limits to prevent overloading target websites; respect these to avoid IP bans. Best practices include limiting runs to 10-20 URLs per execution, using proxies if needed, and scheduling runs during off-peak hours. Avoid scraping excessively to maintain ethical standards and comply with website terms of service. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json {} ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/thisisl-reviews-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/thisisl-reviews-spider").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 '{}' | apify call getdataforme/thisisl-reviews-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/thisisl-reviews-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Thisisl Reviews Spider", "description": "Thisisl Reviews Spider scrapes customer reviews from multiple URLs, extracting ratings, comments, and dates into structured JSON. Perfect for market research and sentiment analysis, it delivers high accuracy, scalability, and seamless Apify integration with robust error handling.", "version": "0.0", "x-build-id": "yucQIcFsB1ikU3Pr9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~thisisl-reviews-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-thisisl-reviews-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~thisisl-reviews-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-thisisl-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~thisisl-reviews-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-thisisl-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```