# Fommy Blog Discovery Opp Spider (`getdataforme/fommy-blog-discovery-opp-spider`) Actor The Fommy Blog Discovery Opp Spider is a web scraping tool for extracting product data from the Fommy blog, ideal for market research and competitive analysis. It offers keyword-based searches, high-quality data extraction, configurable item limits, and flexible output formats (JSON, CSV, Excel).... - **URL**: https://apify.com/getdataforme/fommy-blog-discovery-opp-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 --- ## Fommy Blog Discovery Opp Spider ### Introduction The Fommy Blog Discovery Opp Spider is a powerful web scraping tool designed to extract product data from the Fommy blog. It allows users to efficiently gather information on products related to specified keywords, making it an invaluable resource for market research and competitive analysis. ### Features - **Keyword-Based Scraping**: Customize searches with specific keywords. - **High Data Quality**: Reliable extraction of product details. - **Configurable Limits**: Set item limits to control data volume. - **Flexible Output Formats**: Export results in JSON, CSV, or Excel. - **User-Friendly Interface**: Easy setup and execution on the Apify platform. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|------------------------| | Keywords | array | No | The keywords for the spider. | `["tablet"]` | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Keywords": ["tablet"], "item_limit": 10 } ```` #### Output JSON ```json [ { "product_name": "AMZER TUFFEN Multilayer Case with 360 Degree Rotating Kickstand with Shoulder Strap, Hand Grip for Samsung Galaxy Tab A11+ (Wi-Fi/5G)/ A9+ 11 inch", "post_image": "//fommy.com/cdn/shop/files/208979-1_95x95@2x.jpg?v=1769098852", "posted_date": null, "description": null, "pagination": "page=1", "discounted_price": "30.98", "actual_price": "59.95", "currency": "USD", "actor_id": "sRATtHaaHM2v5BtxX", "run_id": "vDLKOtMYwC95Jitzp" }, { "product_name": "AMZER TUFFEN Multilayer Case with Rotating Kickstand/Handle Grip, Shoulder Strap, Pencil Holder For Lenovo Tab M11/Xiaoxin Pad 11 2024", "post_image": "//fommy.com/cdn/shop/files/209141-1_95x95@2x.jpg?v=1767889841", "posted_date": null, "description": null, "pagination": "page=1", "discounted_price": "27.95", "actual_price": "49.95", "currency": "USD", "actor_id": "sRATtHaaHM2v5BtxX", "run_id": "vDLKOtMYwC95Jitzp" }, { "product_name": "Huawei MediaPad T3 10 9.6 inch Black 3-fold Flip Case", "post_image": "//fommy.com/cdn/shop/products/204530-1_95x95@2x.jpg?v=1548550933", "posted_date": null, "description": null, "pagination": "page=1", "discounted_price": "19.95", "actual_price": "27.95", "currency": "USD", "actor_id": "sRATtHaaHM2v5BtxX", "run_id": "vDLKOtMYwC95Jitzp" } ] ``` ### Use Cases - **Market Research and Analysis**: Identify trends and opportunities. - **Competitive Intelligence**: Monitor competitor pricing and offerings. - **Price Monitoring**: Track price changes over time. - **Content Aggregation**: Compile product information for analysis. - **Academic Research**: Gather data for studies on e-commerce behavior. - **Business Automation**: Integrate with systems for automated reporting. ### Installation and Usage 1. Search for "Fommy Blog Discovery Opp 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 of product objects, each containing: - `product_name`: Name of the product. - `post_image`: URL of the product image. - `posted_date`: Date when the post was made (if available). - `description`: Product description (if available). - `pagination`: Pagination information for the page. - `discounted_price`: Price after any discounts. - `actual_price`: Original price before discounts. - `currency`: Currency of the prices. - `actor_id`: Unique identifier for the actor run. - `run_id`: Unique identifier for the specific run. ### 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 ## `Keywords` (type: `array`): The keywords for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "Keywords": [ "tablet" ], "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/fommy-blog-discovery-opp-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/fommy-blog-discovery-opp-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/fommy-blog-discovery-opp-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/fommy-blog-discovery-opp-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fommy Blog Discovery Opp Spider", "description": "The Fommy Blog Discovery Opp Spider is a web scraping tool for extracting product data from the Fommy blog, ideal for market research and competitive analysis. It offers keyword-based searches, high-quality data extraction, configurable item limits, and flexible output formats (JSON, CSV, Excel)....", "version": "0.0", "x-build-id": "jTiEn6NtOWv03kurk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~fommy-blog-discovery-opp-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-fommy-blog-discovery-opp-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~fommy-blog-discovery-opp-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-fommy-blog-discovery-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~fommy-blog-discovery-opp-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-fommy-blog-discovery-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Keywords": { "title": "Keywords", "type": "array", "description": "The keywords for the spider.", "default": [ "tablet" ], "items": { "type": "string" } }, "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 } } } } } } } } } } ```