# Pasnormal Discovery Spider (`getdataforme/pasnormal-discovery-spider`) Actor The Pasnormal Discovery Spider efficiently extracts detailed product information from Pasnormal Studios' site, capturing names, images, prices, and sizes. It offers flexible URL configuration, scalable item limits, and structured JSON output for easy integration.... - **URL**: https://apify.com/getdataforme/pasnormal-discovery-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 --- ## Pasnormal Discovery Spider ### Introduction The Pasnormal Discovery Spider is a powerful web scraping tool designed to extract detailed product information from Pasnormal Studios' website. It efficiently gathers data such as product names, images, prices, and size variations, providing valuable insights for market research and competitive analysis. ### Features - **Comprehensive Data Extraction**: Captures essential product details including name, image, price, and sizes. - **Flexible URL Configuration**: Allows customization of target URLs to scrape specific content. - **Scalable Item Limit**: Configurable item limit per run ensures efficient data collection tailored to user needs. - **High-Quality Output**: Delivers structured JSON output for easy integration with other tools or databases. - **User-Friendly Setup**: Simple configuration and execution process via the Apify Store. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|----------------------------------------------| | Urls | array | Yes | The URLs for the spider to scrape. | `["https://pasnormalstudios.com/int/search?q=long+sleeve"]` | | 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://pasnormalstudios.com/int/search?q=long+sleeve" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "product_name": "Men's Mechanism Long Sleeve Jersey", "product_image": "https://cdn.shopify.com/s/files/1/0837/6565/7875/files/b60faf0cc1d003fab9bab3d007dfcc4e96288012-3000x3750-product-card.jpg?v=1716466177", "num_colors": 10, "price": "215.0", "currency": "EUR", "tags": [], "size_variations": [ "XXS", "XS", "S", "M", "L", "XL", "XXL" ], "actor_id": "rnntLJCOcXZJmO7uX", "run_id": "19BQUOzPdPjCOhUz0" }, { "product_name": "Men's T.K.O. Essential Light Long Sleeve Jersey", "product_image": "https://cdn.shopify.com/s/files/1/0837/6565/7875/files/f56a30956371db1f38923316943454ad786766ba-1920x2400-product-card.jpg?v=1778245449", "num_colors": 1, "price": "235.0", "currency": "EUR", "tags": ["isNewArrival"], "size_variations": [ "XS", "S", "M", "L", "XL", "XXL" ], "actor_id": "rnntLJCOcXZJmO7uX", "run_id": "19BQUOzPdPjCOhUz0" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather competitive product data for strategic insights. - **Competitive Intelligence**: Monitor competitor pricing and offerings. - **Price Monitoring**: Track price changes over time to identify trends. - **Content Aggregation**: Collect and organize product information for marketing purposes. - **Academic Research**: Use structured data for research projects in business or economics. - **Business Automation**: Integrate with CRM systems for automated updates on product availability. ### Installation and Usage 1. Search for "Pasnormal Discovery 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 where each object represents a product with fields such as `product_name`, `product_image`, `num_colors`, `price`, `currency`, `tags`, and `size_variations`. Each entry also includes unique identifiers like `actor_id` and `run_id`. ### Error Handling Information - **Invalid URLs**: Ensure all provided URLs are valid and accessible. - **Exceeding Item Limit**: If the item limit is reached, no further data will be collected in that run. - **Network Issues**: Handle potential connectivity problems by retrying or checking network status. ### Rate Limiting and Best Practices - Respect website rate limits to avoid being blocked. Implement delays between requests if necessary. - Use a reasonable `item_limit` to balance performance with server load. - Regularly update the spider configuration to adapt to changes in the target website's structure. ### Limitations and Considerations - The spider is tailored for Pasnormal Studios' website; modifications may be needed for other sites. - Ensure compliance with legal and ethical guidelines when scraping data. - Performance may vary based on network conditions and server response times. # 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://pasnormalstudios.com/int/search?q=long+sleeve" ], "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/pasnormal-discovery-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/pasnormal-discovery-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/pasnormal-discovery-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/pasnormal-discovery-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Pasnormal Discovery Spider", "description": "The Pasnormal Discovery Spider efficiently extracts detailed product information from Pasnormal Studios' site, capturing names, images, prices, and sizes. It offers flexible URL configuration, scalable item limits, and structured JSON output for easy integration....", "version": "0.0", "x-build-id": "8wunsY3u0asX4BSoB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~pasnormal-discovery-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-pasnormal-discovery-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~pasnormal-discovery-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-pasnormal-discovery-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~pasnormal-discovery-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-pasnormal-discovery-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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://pasnormalstudios.com/int/search?q=long+sleeve" ], "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 } } } } } } } } } } ```