# Promodescuentos Scraper (`saswave/promodescuentos-scraper`) Actor High-precision data extraction tool designed for promodescuentos.com, Mexico largest social shopping community. It allows you to monitor the latest bargains, track price errors, and analyze consumer trends by capturing the full technical metadata of deals, vouchers, and discussions. - **URL**: https://apify.com/saswave/promodescuentos-scraper.md - **Developed by:** [SASWAVE](https://apify.com/saswave) (community) - **Categories:** E-commerce, News, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.80 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ### Promodescuentos Scraper High-precision data extraction tool designed for promodescuentos.com, Mexico largest social shopping community. It allows you to monitor the latest bargains, track price errors, and analyze consumer trends by capturing the full technical metadata of deals, vouchers, and discussions. ### FEATURES Granular Price Extraction: Capture the current price, nextBestPrice (comparison price), and shipping details for instant ROI calculation. Temperature & Velocity Tracking: Monitor the "heat" of a deal via the temperature and temperatureLevel fields (e.g., Hot, Hot1) to identify viral offers. Coupon & Voucher Capture: Automatically extract voucherCode data and affiliate-related metadata for stackable discounts. Merchant Intelligence: Identify trending retailers in Mexico such as Amazon.com.mx, Walmart, Liverpool, and Bodega Aurrera. User Authority Mapping: Access information on the deal's author (username) and community status. Localized Taxonomy: Full support for Mexican categories such as "Abarrotes y alimentos," "Electrรณnica," and "Moda y accesorios." Advanced Lifecycle Data: Track publishedAt and updatedAt timestamps to ensure you never miss a limited-time flash deal. ### USE CASES Real-Time Deal Alerts: Build a bot that notifies you the moment a specific product (like "Cafรฉ Blason") reaches a "Hot" status or hits a target price. Market Sentiment Analysis: Use commentCount and voting patterns to gauge Mexican consumer sentiment toward brands or retail events like El Buen Fin or Hot Sale. Competitor Benchmarking: Monitor the aggressive discount strategies of major Mexican e-commerce players to optimize your own pricing. Affiliate Content Aggregation: Populate Mexican deal sites, Telegram "Ofertas" channels, or social media bots with the highest-rated community bargains. Price Error Hunting: Identify deals where the gap between price and nextBestPrice suggests an unintentional discount. ### OUTPUT ```json { "threadId": "1156240", "product_link": "https://www.rappi.com.mx/login&product=ppr-mx-588250373", "titleSlug": "99-de-cashback-en-kfc", "title": "Rappi: 99% de Cashback en KFC", "currentUserVoteDirection": null, "commentCount": 3, "status": "Activated", "isExpired": false, "isNew": false, "isPinned": false, "isTrending": null, "bookmarked": false, "isLocal": false, "temperature": 108.66, "temperatureLevel": "Hot2", "type": "Voucher", "nsfw": false, "deletedAt": null, "isAffiliateTrackingDisabled": false, "isAffiliateDescriptionDisabled": false, "isEditLocked": false, "isExpireLocked": false, "contentLockedBy": null, "isSpamLocked": false, "isLocked": false, "isNewsletterPicked": null, "isCommentsModerationOn": null, "isPushed": null, "isCommunityFavorite": false, "isCategoryCommunityFavorite": false, "isTopDeal": false, "isCategoryTopDeal": false, "pinId": null, "bumpedAt": "", "bumpedAndReset": false, "publishedAt": "2026-05-06 06:18:15", "updatedAt": "2026-05-06 06:18:15", "voucherCode": "kfc99cb05", "link": "", "linkHost": "www.rappi.com.mx", "shareableLink": "https://www.promodescuentos.com/share-deal/1156240", "merchant": { "merchantId": 145, "merchantName": "Rappi", "merchantUrlName": "rappi", "isMerchantPageEnabled": true, "avatar": { "path": "merchants/raw/avatar", "name": "145_4", "slotId": "avatar", "width": 0, "height": 0, "version": 4, "unattached": false, "uid": "145_4.raw", "ext": "raw" } }, "mainGroup": { "threadGroupId": 13, "threadGroupName": "Servicios y suscripciones", "threadGroupUrlName": "servicios" }, "mainImage": { "path": "threads/raw/bXbES", "name": "1156240_1", "slotId": "bXbES", "width": 1206, "height": 1394, "version": 1, "unattached": false, "uid": "1156240_1.raw", "ext": "raw" }, "price": 0, "nextBestPrice": 0, "percentage": 99, "discountType": "Percentage", "shipping": { "isFree": null, "price": 0 }, "user": { "userId": 1031346, "username": "Alfredo_SantosSalazar", "title": "", "avatar": { "path": "users/raw/default", "name": "1031346_1", "slotId": "default", "width": 0, "height": 0, "version": 1, "unattached": false, "uid": "1031346_1.raw", "ext": "raw" }, "persona": { "text": null, "type": null }, "isBanned": false, "isDeletedOrPendingDeletion": false, "isUserProfileHidden": false }, "startDate": { "timestamp": "2026-05-05 06:01:00" }, "selectedLocations": { "isNational": false }, "endDate": { "timestamp": "2026-05-08 05:59:00" }, "isExclusive": false, "isVoucherCodeHidden": true, "claimCodeCampaignId": null, "claimCodeCampaign": null, "canVote": false, "scheduledReleaseDate": { "timestamp": "" }, "isHot": true, "pickedAt": 0, "hotDate": "2026-05-06 13:35:33", "isExcludedFromAds": false, "threadUpdates": [], "unread": null, "keywords": null, "keywordNames": null, "isSuperHot": null } ```` ### ๐Ÿ›Ÿ SUPPORT Share your runs with the developer team and create issues on error to help us improve actor quality. You might discover edge case we didn't test yet We stay available anytime # Actor input Schema ## `urls` (type: `array`): Search url to extract results from ## `max_page` (type: `integer`): Maximum page per search ## Actor input object example ```json { "urls": [ "https://www.promodescuentos.com/search?q=amazon" ], "max_page": 1 } ``` # 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 = { "urls": [ "https://www.promodescuentos.com/search?q=amazon" ] }; // Run the Actor and wait for it to finish const run = await client.actor("saswave/promodescuentos-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "urls": ["https://www.promodescuentos.com/search?q=amazon"] } # Run the Actor and wait for it to finish run = client.actor("saswave/promodescuentos-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.promodescuentos.com/search?q=amazon" ] }' | apify call saswave/promodescuentos-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=saswave/promodescuentos-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Promodescuentos Scraper", "description": "High-precision data extraction tool designed for promodescuentos.com, Mexico largest social shopping community. It allows you to monitor the latest bargains, track price errors, and analyze consumer trends by capturing the full technical metadata of deals, vouchers, and discussions.", "version": "0.0", "x-build-id": "wizL9rqejlAH4f42r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/saswave~promodescuentos-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-saswave-promodescuentos-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/saswave~promodescuentos-scraper/runs": { "post": { "operationId": "runs-sync-saswave-promodescuentos-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/saswave~promodescuentos-scraper/run-sync": { "post": { "operationId": "run-sync-saswave-promodescuentos-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "urls" ], "properties": { "urls": { "title": "Search urls", "type": "array", "description": "Search url to extract results from", "items": { "type": "string" } }, "max_page": { "title": "Maximum page", "minimum": 0, "type": "integer", "description": "Maximum page per search", "default": 1 } } }, "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 } } } } } } } } } } ```