# Letsmakeaplan Blog Detail Opp Spider (`getdataforme/letsmakeaplan-blog-detail-opp-spider`) Actor Automate data extraction from Letsmakeaplan blogs with high-quality, customizable scraping. Tailor inputs and export in JSON, CSV, or Excel. Ideal for market research, content aggregation, and more.... - **URL**: https://apify.com/getdataforme/letsmakeaplan-blog-detail-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 --- ## README.md ### Letsmakeaplan Blog Detail Opp Spider #### Introduction The Letsmakeaplan Blog Detail Opp Spider is a powerful web scraping tool designed to extract detailed information from specific blog articles on the Letsmakeaplan website. This actor automates data collection, ensuring high-quality and reliable data for various analytical purposes. #### Features - **Automated Data Extraction**: Seamlessly scrape blog details with minimal setup. - **High-Quality Data**: Ensures accurate and comprehensive extraction of article content. - **Customizable Input Parameters**: Tailor the scraping process to specific needs. - **Efficient Performance**: Optimized for speed and reliability in data collection. - **Flexible Output Formats**: Export results in JSON, CSV, or Excel formats. #### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------| | `Urls` | array | Yes | The URLs for the spider to scrape. | `[ "https://www.letsmakeaplan.org/financial-topics/articles/family-finances/how-to-manage-the-effects-of-inflation-on-your-family" ]` | | `item_limit`| integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | #### Example Usage ##### Input JSON ```json { "Urls": [ "https://www.letsmakeaplan.org/financial-topics/articles/family-finances/how-to-manage-the-effects-of-inflation-on-your-family" ], "item_limit": 10 } ```` ##### Output JSON ```json [ { "url": "https://www.letsmakeaplan.org/financial-topics/articles/family-finances/how-to-manage-the-effects-of-inflation-on-your-family", "post_title": "How to Manage the Effects of Inflation on Your Family", "post_image": "https://www.letsmakeaplan.org/-/media/images/lmap/w64-images/how-to-manage-the-effects-of-inflation-on-your-family-and-money.jpg?cx=0&cy=0&cw=1920&ch=800&hash=5C10F04618EF69ADB25AC68D828D6402", "description": "Are you worried about how inflation will impact your family finances? Inflation is a general increase in the level of prices over a given period of time...", "actor_id": "EzzEbXytgK6SdaMuK", "run_id": "XLRJroySAjJwIolof" } ] ``` #### Use Cases - **Market Research and Analysis**: Extract insights from financial articles for market trends. - **Competitive Intelligence**: Monitor competitor content strategies and topics. - **Price Monitoring**: Track changes in product pricing mentioned in blog posts. - **Content Aggregation**: Compile information from multiple articles into a single dataset. - **Academic Research**: Gather data for studies on financial literacy and consumer behavior. - **Business Automation**: Automate the collection of relevant industry news. #### Installation and Usage 1. Search for "Letsmakeaplan Blog Detail 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 containing objects with the following fields: - `url`: The URL of the scraped article. - `post_title`: Title of the blog post. - `post_image`: Image URL associated with the post. - `description`: Detailed content description from the article. - `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 ## `Urls` (type: `array`): The urls 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 { "Urls": [ "https://www.letsmakeaplan.org/financial-topics/articles/family-finances/how-to-manage-the-effects-of-inflation-on-your-family" ], "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/letsmakeaplan-blog-detail-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/letsmakeaplan-blog-detail-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/letsmakeaplan-blog-detail-opp-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/letsmakeaplan-blog-detail-opp-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Letsmakeaplan Blog Detail Opp Spider", "description": "Automate data extraction from Letsmakeaplan blogs with high-quality, customizable scraping. Tailor inputs and export in JSON, CSV, or Excel. Ideal for market research, content aggregation, and more....", "version": "0.0", "x-build-id": "Z29BslznkMcvOzN7a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~letsmakeaplan-blog-detail-opp-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-letsmakeaplan-blog-detail-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~letsmakeaplan-blog-detail-opp-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-letsmakeaplan-blog-detail-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~letsmakeaplan-blog-detail-opp-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-letsmakeaplan-blog-detail-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.letsmakeaplan.org/financial-topics/articles/family-finances/how-to-manage-the-effects-of-inflation-on-your-family" ], "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 } } } } } } } } } } ```