# Tatd Reviews Spider (`getdataforme/tatd-reviews-spider`) Actor The Tatd Reviews Spider is an Apify Actor that scrapes comprehensive customer reviews from TATD websites, capturing names, locations, dates, ratings, and text.... - **URL**: https://apify.com/getdataforme/tatd-reviews-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ### Description The Tatd Reviews Spider is an Apify Actor that scrapes comprehensive customer reviews from TATD websites, capturing names, locations, dates, ratings, and text.... --- ## Tatd Reviews Spider ### Introduction The Tatd Reviews Spider is a powerful Apify Actor designed to scrape and extract customer reviews from TATD (The Association of Travel Agents of Delhi) websites. It efficiently collects detailed review data, including reviewer names, locations, dates, ratings, and review text, enabling businesses and researchers to gain valuable insights into customer sentiments. This tool streamlines data collection for market analysis, reputation management, and competitive intelligence, saving time and effort compared to manual scraping. ### Features - **Comprehensive Review Extraction**: Captures full review details such as names, locations, dates, ratings (1-5 scale), and review text from TATD pages. - **High Reliability and Accuracy**: Built with robust error handling to ensure data integrity and minimize missing information. - **Scalable Performance**: Handles multiple URLs efficiently, supporting batch processing for large-scale data collection. - **Flexible Output Formats**: Exports data in JSON, CSV, or Excel, ready for integration into analytics tools or databases. - **User-Friendly Configuration**: Simple input setup with URL lists, requiring no coding expertise. - **Real-Time Monitoring**: Provides logs and progress tracking during runs for transparency and debugging. - **Ethical Scraping**: Adheres to website terms and includes built-in delays to respect rate limits and avoid overloading servers. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | Urls | array | No | A list of URLs to scrape reviews from. Must include at least one valid HTTP/HTTPS URL pointing to TATD review pages. | `["https://www.tatd.in/rating-and-review.php"]` | ### Example Usage To run the Tatd Reviews Spider, provide the input in JSON format: ```json { "Urls": [ "https://www.tatd.in/rating-and-review.php" ] } ```` Example output in JSON format: ```json [ { "name": "V C Tripathy", "location": "Noida", "date": "17 Apr, 2026", "rating": 5, "review": "Excellent and very disciplined", "actor_id": "fUKRfWzVBjtrqozPl", "run_id": "dmNGXRCFbtuRQRuM7" }, { "name": "Navdeep Chopra", "location": "South Delhi", "date": "17 Apr, 2026", "rating": 3, "review": "Wanted cash, was complaining about payment not been received on time from tatd", "actor_id": "fUKRfWzVBjtrqozPl", "run_id": "dmNGXRCFbtuRQRuM7" }, { "name": "Aparna G", "location": "Hyderabad", "date": "15 Apr, 2026", "rating": 5, "review": "He is good.", "actor_id": "fUKRfWzVBjtrqozPl", "run_id": "dmNGXRCFbtuRQRuM7" } ] ``` ### Use Cases - **Market Research and Analysis**: Analyze customer feedback to identify trends in travel agent services and improve offerings. - **Competitive Intelligence**: Monitor reviews of competitors to benchmark performance and uncover strengths/weaknesses. - **Reputation Management**: Track online sentiment for TATD members to respond to negative reviews promptly. - **Content Aggregation**: Collect and aggregate reviews for content creation, such as blog posts or reports on travel industry insights. - **Academic Research**: Gather data for studies on consumer behavior in the travel sector. - **Business Automation**: Automate review monitoring for dashboards or alerts on new feedback. ### Installation and Usage 1. Search for "Tatd 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 Actor outputs data as a JSON array of objects, each representing a single review. Key fields include: - `name`: Reviewer's name (string). - `location`: Reviewer's location (string). - `date`: Review date in "DD MMM, YYYY" format (string). - `rating`: Numerical rating from 1 to 5 (integer). - `review`: Full review text (string). - `actor_id`: Unique identifier for the Actor run (string). - `run_id`: Unique identifier for the specific run (string). This structured format ensures easy parsing and integration into downstream applications. ### 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 { "Urls": [ "https://www.tatd.in/rating-and-review.php" ] } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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/tatd-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/tatd-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/tatd-reviews-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/tatd-reviews-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tatd Reviews Spider", "description": "The Tatd Reviews Spider is an Apify Actor that scrapes comprehensive customer reviews from TATD websites, capturing names, locations, dates, ratings, and text....", "version": "0.0", "x-build-id": "OqloVEc1IIpIz1xMy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~tatd-reviews-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-tatd-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~tatd-reviews-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-tatd-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~tatd-reviews-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-tatd-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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.", "default": [ "https://www.tatd.in/rating-and-review.php" ], "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 } } } } } } } } } } ```