# IIFYM Blog Details Scraper (`getdataforme/iifym-blog-details-opp-scraper`) Actor Extract detailed insights from IIFYM blogs with ease using the IIFYM Blog Details Scraper. Capture comprehensive data like titles, authors, and publication dates to enhance your market research, competitive intelligence, or content aggregation efforts.... - **URL**: https://apify.com/getdataforme/iifym-blog-details-opp-scraper.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 ## README.md ### IIFYM Blog Details Scraper #### Introduction The **IIFYM Blog Details Scraper** is an advanced web scraping tool designed to extract detailed information from IIFYM (If It Fits Your Macros) blogs. This powerful scraper provides users with comprehensive data, enabling them to gain insights into fitness and nutrition trends, optimize their macro tracking strategies, and enhance content creation. #### Features - **Comprehensive Data Extraction**: Captures a wide range of blog details including titles, URLs, publication dates, authors, and more. - **High-Quality Data**: Ensures reliable and accurate data extraction with minimal errors. - **User-Friendly Interface**: Easy to configure and use, even for those without technical expertise. - **Flexible Output Formats**: Supports multiple export formats such as JSON, CSV, and Excel. - **Real-Time Monitoring**: Allows users to track the progress of their scraping tasks in real-time. - **Scalability**: Capable of handling large volumes of data efficiently. #### Input Parameters Table | Parameter | Type | Required | Description | Example | |-----------------|---------|----------|-----------------------------------------------------------------------------|--------------------------| | `url` | String | Yes | The URL of the IIFYM blog to scrape. | `"https://example.com"` | | `maxPages` | Integer | No | Maximum number of pages to scrape from the blog. | `5` | | `delay` | Float | No | Delay between requests in seconds to prevent being blocked by the server. | `2.0` | | `outputFormat` | String | No | Desired output format (e.g., JSON, CSV). | `"JSON"` | #### Example Usage ##### Input JSON ```json { "url": "https://example.com", "maxPages": 5, "delay": 2.0, "outputFormat": "JSON" } ```` ##### Output JSON ```json { "data": [ { "title": "How to Track Macros Effectively", "url": "https://example.com/how-to-track-macros", "datePublished": "2023-10-01", "author": "John Doe" }, // Additional blog entries... ] } ``` #### Use Cases - **Market Research and Analysis**: Gain insights into fitness trends and consumer preferences. - **Competitive Intelligence**: Monitor competitors' content strategies and performance. - **Price Monitoring**: Track pricing changes in nutrition products mentioned in blogs. - **Content Aggregation**: Curate a collection of relevant blog posts for analysis or sharing. - **Academic Research**: Collect data for studies on fitness, nutrition, and lifestyle trends. - **Business Automation**: Automate content discovery and integration into marketing strategies. #### Installation and Usage 1. Search for "IIFYM Blog Details Scraper" 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 section. 6. Export results in your preferred format (JSON, CSV, Excel). #### Output Format The output data is structured with key fields such as `title`, `url`, `datePublished`, and `author`. Each entry represents a blog post extracted from the specified IIFYM blog. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Get Data For Me](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! *** ## Description **Maximize your fitness insights with the IIFYM Blog Details Scraper!** Extract comprehensive blog data effortlessly, including titles, authors, and publication dates. Ideal for market research, competitive intelligence, and content aggregation. Start scraping today and unlock valuable trends in nutrition and fitness! 🚀 # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## Actor input object example ```json { "startUrls": [ { "url": "https://iifym.com/blog/macro-tracking-app/" } ] } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "startUrls": [ { "url": "https://iifym.com/blog/macro-tracking-app/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/iifym-blog-details-opp-scraper").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 = { "startUrls": [{ "url": "https://iifym.com/blog/macro-tracking-app/" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/iifym-blog-details-opp-scraper").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 '{ "startUrls": [ { "url": "https://iifym.com/blog/macro-tracking-app/" } ] }' | apify call getdataforme/iifym-blog-details-opp-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/iifym-blog-details-opp-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "IIFYM Blog Details Scraper", "description": "Extract detailed insights from IIFYM blogs with ease using the IIFYM Blog Details Scraper. Capture comprehensive data like titles, authors, and publication dates to enhance your market research, competitive intelligence, or content aggregation efforts....", "version": "0.0", "x-build-id": "Uu5UY8EpQFe9K8LpS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~iifym-blog-details-opp-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-iifym-blog-details-opp-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~iifym-blog-details-opp-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-iifym-blog-details-opp-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~iifym-blog-details-opp-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-iifym-blog-details-opp-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```