# CONADIS Peru Disability Registry Scraper (`parseforge/conadis-peru-disability-registry-scraper`) Actor Parse CONADIS Peru observatory tables for disability statistics by region, returning region, year, disability\_type, count, age\_group, and gender. Useful for accessibility research, social policy analysis, NGO planning, and demographic studies across Peruvian departments and age groups. - **URL**: https://apify.com/parseforge/conadis-peru-disability-registry-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Automation, Integrations - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.50 / 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## β™Ώ CONADIS Peru Disability Registry Scraper > πŸš€ **Export Peru's CONADIS disability registry statistics in seconds. Regional counts, disability types, age groups, and gender breakdowns.** > πŸ•’ **Last updated:** 2026-05-29 Β· **πŸ“Š 8 fields** per record Β· All 25 Peruvian regions Β· Live CONADIS observatory The CONADIS Peru Disability Registry Scraper turns the public observatory at [conadisperu.gob.pe](https://www.conadisperu.gob.pe/observatorio/) into a structured dataset. It parses the data tables published by CONADIS and returns one row per region, year, and disability category. Coverage spans all 25 Peruvian departments tracked by Peru's National Council for the Integration of People with Disabilities (CONADIS). | 🎯 Target Audience | πŸ’‘ Primary Use Cases | |---|---| | πŸ›οΈ Public health teams | Map disability prevalence by department | | πŸ“Š NGOs and advocates | Quantify regional service gaps | | πŸ“° Journalists | Source authoritative CONADIS figures | | πŸ€– Data engineers | Mirror disability stats into a warehouse | | πŸŽ“ Researchers | Build cohorts for public health studies | | πŸ’Ό Donor organizations | Allocate aid based on official counts | ### πŸ“‹ What the CONADIS Peru Disability Registry Scraper does - Fetches the public CONADIS observatory page. - Parses the published tables generically (region, year, type, count, age, gender). - Optionally filters to a specific Peruvian region. - Surfaces upstream errors as a clean diagnostic record. > πŸ’‘ **Why it matters:** CONADIS publishes the only nationwide registry of people with disabilities in Peru. The numbers are tucked into observatory HTML tables that change layout; this actor wraps the parsing. ### 🎬 Full Demo _🚧 Coming soon._ ### βš™οΈ Input
FieldTypeRequiredDescription
regionenumNoOne of 25 Peruvian regions or empty for all.
maxItemsintegerNoFree 10, paid up to 1,000,000.
**Example 1 - All regions:** ```json { "maxItems": 25 } ```` **Example 2 - Lima only:** ```json { "region": "LIMA", "maxItems": 50 } ``` > ⚠️ **Good to Know:** CONADIS publishes refreshed tables on the observatory landing page. Run on a schedule to keep your copy current. ### πŸ“Š Output | Field | Type | Description | |---|---|---| | πŸ—ΊοΈ `region` | string | Peruvian region. | | πŸ“… `year` | number | Reporting year. | | β™Ώ `disability_type` | string | Type of disability when reported. | | πŸ”’ `count` | number | Number of registered persons. | | πŸ‘₯ `age_group` | string | Age group bucket. | | ⚧ `gender` | string | Gender when reported. | | πŸ•’ `scrapedAt` | string | When this row was fetched. | | ❌ `error` | string | Set if upstream response was an error. | **Sample record:** ```json { "region": "LIMA", "year": 2024, "disability_type": "FISICA", "count": 152340, "age_group": "30-59", "gender": "F", "scrapedAt": "2026-05-29T13:00:00.000Z", "error": null } ``` ### ✨ Why choose this Actor | πŸ†“ | Works with no API key. | | πŸ‡΅πŸ‡ͺ | Covers all 25 Peruvian regions. | | πŸ›‘οΈ | Real browser headers via got-scraping. | | πŸ›Ÿ | Surfaces upstream errors as a clean diagnostic row. | | πŸ’Ύ | Push to dataset and export CSV, Excel, JSON, or XML. | ### πŸ“ˆ How it compares to alternatives | Approach | Setup time | Coverage | Maintained | |---|---|---|---| | Manual CONADIS portal | minutes per query | full | manual | | INEI mirror | partial | partial | varies | | **This Actor** | 5 sec, no install | full | live | ### πŸš€ How to use 1. Click **Try for free**. 2. Pick a region or leave empty. 3. Click **Start**. ### πŸ’Ό Business use cases **πŸ›οΈ Public health planning.** Map disability prevalence per region for service rollout. **πŸ“° Newsroom verification.** Confirm CONADIS counts in social policy stories. **πŸ“Š NGO planning.** Allocate program budgets using authoritative counts. **πŸ€– Research pipelines.** Pipe registry stats into a public health warehouse. ### πŸ”Œ Automating CONADIS Peru Disability Registry Scraper - **Make / Zapier**: trigger and push to Airtable. - **Cron schedule**: monthly refreshes. - **Webhooks**: POST to your endpoint after each run. - **Pipe to BigQuery / Snowflake / Postgres**: native integrations. ### 🌟 Beyond business use cases **πŸŽ“ Education.** Teach disability studies with authoritative Peruvian data. **πŸ§ͺ Personal research.** Map disability counts in your home region. **🀝 Non-profit.** Power advocacy campaigns. **🧰 Prototyping.** Mock up a public health dashboard. ### πŸ€– Ask an AI assistant about this scraper Paste this README into ChatGPT or Claude. ### ❓ Frequently Asked Questions **❓ Do I need an API key?** No. **❓ Which years are covered?** Every year CONADIS has published on the observatory. **❓ Can I filter by region?** Yes, set `region` to a department name. **❓ Are counts cast to numbers?** Yes. **❓ Can I schedule runs?** Yes via the Apify scheduler. **❓ Is this scraping or API?** HTML parsing of the public CONADIS observatory. **❓ What format can I download?** CSV, Excel, JSON, JSONL, XML, RSS, or HTML. **❓ What if the table is empty?** A diagnostic record with `error` is pushed. **❓ Does it follow robots.txt?** Only public pages are fetched. **❓ Will the schema change?** Stable. ### πŸ”Œ Integrate with any app Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST API or webhook. ### πŸ”— Recommended Actors | Actor | What it does | |---|---| | [ParseForge ONPE Peru Elections Scraper](https://apify.com/parseforge/onpe-peru-elections-scraper) | Peru election results. | | [ParseForge DANE Colombia Scraper](https://apify.com/parseforge/dane-colombia-statistics-scraper) | Colombia statistics. | | [ParseForge collection](https://apify.com/parseforge) | 900+ production scrapers. | > πŸ’‘ **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for 900+ production-grade scrapers across business intelligence, real estate, e-commerce, sports, finance, and public records. *** **Disclaimer:** This actor scrapes only publicly available data. ParseForge is not affiliated with, endorsed by, or sponsored by any of the third-party services referenced. Users are responsible for complying with the target site's terms of service and applicable law. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp). # Actor input Schema ## `region` (type: `string`): Department name (e.g. LIMA, AREQUIPA). Leave empty for nationwide. ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## Actor input object example ```json { "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/conadis-peru-disability-registry-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "maxItems": 10 } # Run the Actor and wait for it to finish run = client.actor("parseforge/conadis-peru-disability-registry-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10 }' | apify call parseforge/conadis-peru-disability-registry-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/conadis-peru-disability-registry-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CONADIS Peru Disability Registry Scraper", "description": "Parse CONADIS Peru observatory tables for disability statistics by region, returning region, year, disability_type, count, age_group, and gender. Useful for accessibility research, social policy analysis, NGO planning, and demographic studies across Peruvian departments and age groups.", "version": "0.1", "x-build-id": "w5HctNpX8z5Dqdlmc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~conadis-peru-disability-registry-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-conadis-peru-disability-registry-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~conadis-peru-disability-registry-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-conadis-peru-disability-registry-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~conadis-peru-disability-registry-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-conadis-peru-disability-registry-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "region": { "title": "Peruvian region", "enum": [ "", "AMAZONAS", "ANCASH", "APURIMAC", "AREQUIPA", "AYACUCHO", "CAJAMARCA", "CALLAO", "CUSCO", "HUANCAVELICA", "HUANUCO", "ICA", "JUNIN", "LA LIBERTAD", "LAMBAYEQUE", "LIMA", "LORETO", "MADRE DE DIOS", "MOQUEGUA", "PASCO", "PIURA", "PUNO", "SAN MARTIN", "TACNA", "TUMBES", "UCAYALI" ], "type": "string", "description": "Department name (e.g. LIMA, AREQUIPA). Leave empty for nationwide." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" } } }, "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 } } } } } } } } } } ```