# Ffhoney Search Product Parser Spider (`getdataforme/ffhoney-search-product-parser-spider`) Actor The Ffhoney Search Product Parser Spider efficiently extracts product data from Forest Fresh Honey, capturing titles, prices, and images. Ideal for market research and competitive analysis, it offers customizable item limits, structured JSON output, and user-friendly configuration.... - **URL**: https://apify.com/getdataforme/ffhoney-search-product-parser-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, 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 --- ## Ffhoney Search Product Parser Spider ### Introduction The Ffhoney Search Product Parser Spider is designed to efficiently extract product data from the Forest Fresh Honey website. This Apify Actor simplifies the process of gathering detailed information about honey products, including titles, prices, and images, making it an invaluable tool for market research and competitive analysis. ### Features - **Comprehensive Data Extraction**: Captures essential product details such as title, price, URLs, and images. - **Customizable Item Limits**: Allows users to set a maximum number of items to scrape per run. - **High-Quality Output**: Ensures data reliability with structured JSON output for easy integration. - **User-Friendly Configuration**: Simple setup with intuitive input parameters. - **Versatile Applications**: Suitable for market research, price monitoring, and content aggregation. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|---------| | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "item_limit": 5 } ```` #### Output JSON ```json [ { "title": "3 x 500g Active Honey Value Set", "product_url": "https://www.forestfreshhoney.com.au/products/active-bundle-jarrah-blackbutt-marri?_pos=1&_sid=27feb7b93&_ss=r", "main_image": "//www.forestfreshhoney.com.au/cdn/shop/files/COA_dd7a7ca9-2cb9-4630-91e8-b5ca2db2b627.png?v=1759418568&width=1080", "secondary_image": "//www.forestfreshhoney.com.au/cdn/shop/files/Info_0d681e15-108c-4f95-a2a7-40f24a0e7003.png?v=1759418570&width=1080", "price": "From $68.00", "search_keyword": "honey+fresh", "actor_id": "AkCUGoZiGkGz9nkx0", "run_id": "3Gij8l2wzok5PO8cs" }, { "title": "Honeycomb", "product_url": "https://www.forestfreshhoney.com.au/products/honeycomb?_pos=2&_sid=27feb7b93&_ss=r", "main_image": "//www.forestfreshhoney.com.au/cdn/shop/files/HoneyComb.jpg?v=1759418535&width=1080", "secondary_image": "//www.forestfreshhoney.com.au/cdn/shop/products/image_de96b6b0-5ed1-4d30-afed-dbdf8cfced72.jpg?v=1759418539&width=2936", "price": "From $18.00", "search_keyword": "honey+fresh", "actor_id": "AkCUGoZiGkGz9nkx0", "run_id": "3Gij8l2wzok5PO8cs" }, { "title": "Jarrah Gold TA40+ (MGO 2142+ equiv)", "product_url": "https://www.forestfreshhoney.com.au/products/jarrah-gold-ta40-mgo-2142-equiv?_pos=3&_sid=27feb7b93&_ss=r", "main_image": "//www.forestfreshhoney.com.au/cdn/shop/files/Ta40.jpg?v=1759418458&width=1080", "secondary_image": "//www.forestfreshhoney.com.au/cdn/shop/files/Info_2bd5a3e7-47f3-4f21-9aac-c91cc6f915ec.jpg?v=1759418461&width=1080", "price": "From $19.00", "search_keyword": "honey+fresh", "actor_id": "AkCUGoZiGkGz9nkx0", "run_id": "3Gij8l2wzok5PO8cs" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data for competitive analysis. - **Competitive Intelligence**: Monitor competitor pricing strategies. - **Price Monitoring**: Track price changes over time. - **Content Aggregation**: Compile product information for content creation. - **Academic Research**: Support studies on market trends in honey products. - **Business Automation**: Automate data collection processes. ### Installation and Usage 1. Search for "Ffhoney Search Product Parser Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 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 containing objects with the following fields: - `title`: The product title. - `product_url`: URL of the product page. - `main_image`: URL of the main product image. - `secondary_image`: URL of an additional product image. - `price`: Product price information. - `search_keyword`: Keyword used for search. - `actor_id`: Unique identifier for the actor. - `run_id`: Unique identifier for the run. ### Error Handling The Actor is designed to handle common errors gracefully, such as network issues or changes in website structure. If an error occurs, it will be logged, and you can review the log for details on how to address the issue. ### Rate Limiting and Best Practices To ensure optimal performance and avoid being blocked by the target site, adhere to the following best practices: - Respect the `item_limit` parameter to control data volume. - Monitor logs for any rate-limiting warnings or errors. - Use appropriate delays between requests if necessary. ### Limitations and Considerations - The Actor is tailored specifically for the Forest Fresh Honey website; changes in site structure may affect performance. - Ensure compliance with legal and ethical guidelines when scraping websites. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "item_limit": 10 } ``` # 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/ffhoney-search-product-parser-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/ffhoney-search-product-parser-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/ffhoney-search-product-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/ffhoney-search-product-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Ffhoney Search Product Parser Spider", "description": "The Ffhoney Search Product Parser Spider efficiently extracts product data from Forest Fresh Honey, capturing titles, prices, and images. Ideal for market research and competitive analysis, it offers customizable item limits, structured JSON output, and user-friendly configuration....", "version": "0.0", "x-build-id": "5uPMgOSWXHLWs1OMo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~ffhoney-search-product-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-ffhoney-search-product-parser-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~ffhoney-search-product-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-ffhoney-search-product-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~ffhoney-search-product-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-ffhoney-search-product-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```