# Necc Egg Price Scraper (`akash9078/necc-egg-price-scraper`) Actor NECC Egg Price Scraper is a tool that automatically extracts real-time egg prices published by the National Egg Coordination Committee (NECC). It enables users to track daily price fluctuations across different regions, ensuring accurate, up-to-date market data for analysis, trading, or business. - **URL**: https://apify.com/akash9078/necc-egg-price-scraper.md - **Developed by:** [Akash Kumar Naik](https://apify.com/akash9078) (community) - **Categories:** AI, Developer tools, E-commerce - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start 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 ## NECC Egg Price Scraper Scrape daily egg prices from the National Egg Co-ordination Committee (NECC) website for any date range and district. Extract date-wise egg prices across 35+ Indian production and consumption centres — perfect for market analysis, price tracking, and agricultural research. ### Features - **Scrape NECC egg prices** for any custom date range with datepicker inputs - **Select specific districts** or scrape all 35+ available centres across India - **Date-wise daily price extraction** from NECC's official suggested prices - **Export to Excel (.xlsx)** with organized columns per district - **JSON dataset output** for API integration and programmatic access - **Handle ASP.NET form postbacks** reliably with headless browser automation - **No proxy required** — NECC website has no anti-bot protection ### Use Cases - **Egg price trend analysis** — Track daily egg price fluctuations across Indian markets for commodities research - **Agricultural market monitoring** — Monitor NECC suggested prices for production centres (Namakkal, Warangal, Pune) and consumption centres (Mumbai, Delhi, Chennai) - **Supply chain planning** — Use historical egg price data to optimize procurement and logistics for poultry businesses - **Academic research** — Access structured NECC egg price datasets for economic studies on food inflation - **Competitor intelligence** — Compare prevailing prices across regions for trading decisions - **Automated data pipelines** — Integrate NECC egg price data into dashboards, spreadsheets, or analytics platforms via Apify API ### How It Works This Actor uses Playwright headless browser to automate the NECC egg price portal at [e2necc.com](https://www.e2necc.com/home/eggprice). It: 1. Fetches all available district names from the current month's data table 2. Iterates through each month in the specified date range 3. Submits the ASP.NET form with month/year parameters to retrieve daily rates 4. Parses the price table, matching district names to daily values (days 1–31) 5. Filters results to the exact date range provided 6. Exports structured data to both Apify Dataset (JSON) and an Excel file stored in Key-Value Store ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `startDate` | Date (YYYY-MM-DD) | Yes | Today | Start date for scraping egg prices | | `endDate` | Date (YYYY-MM-DD) | Yes | Today | End date for scraping egg prices | | `districts` | Array of strings | No | All districts | Select specific districts to scrape. Leave empty for all 35+ centres | #### Available Districts **Production Centres:** Namakkal, Warangal, Vijayawada, Chittoor, E.Godavari, W.Godavari, Vizag, Pune, Surat, Ludhiana, Barwala, Hospet, Mysuru, Jabalpur, Raipur, Nagpur, Bhopal, Ajmer, Ahmedabad, Hyderabad **Consumption Centres:** Mumbai (CC), Delhi (CC), Chennai (CC), Bengaluru (CC), Kolkata (WB), Kanpur (CC), Luknow (CC), Allahabad (CC), Varanasi (CC), Ranchi (CC), Muzaffurpur (CC), Indore (CC), Brahmapur (OD), Berhampur (OD) ### Output #### Dataset (JSON) Each item represents one date with prices for all selected districts: ```json { "date": "2026-04-01", "Berhampur (OD)": "455", "Raipur": "425", "Namakkal": "405", "Mumbai (CC)": "470", "Delhi (CC)": "460" } ```` #### Excel File (Key-Value Store) A formatted `.xlsx` file with columns: `Date`, followed by one column per selected district. Downloadable from the run's Key-Value Store. #### Run Statistics ```json { "totalRows": 367, "totalDistricts": 35, "districts": ["Namakkal", "Raipur", "Mumbai (CC)", "..."], "startDate": "2025-04-01", "endDate": "2026-04-02", "monthsScraped": 13 } ``` ### Usage Examples #### Apify API (JavaScript) ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('your-username/necc-egg-price-scraper').call({ startDate: '2025-04-01', endDate: '2026-04-02', districts: ['Namakkal', 'Raipur', 'Mumbai (CC)', 'Delhi (CC)'], }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Scraped ${items.length} days of egg prices`); ``` #### Apify API (Python) ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("your-username/necc-egg-price-scraper").call( start_date="2025-04-01", end_date="2026-04-02", districts=["Namakkal", "Raipur", "Mumbai (CC)"], ) items = client.dataset(run["defaultDatasetId"]).list_items().items print(f"Scraped {len(items)} days of NECC egg prices") ``` #### cURL ```bash curl --request POST \ --url "https://api.apify.com/v2/acts/your-username~necc-egg-price-scraper/runs" \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer YOUR_API_TOKEN' \ --data '{ "startDate": "2025-04-01", "endDate": "2026-04-02", "districts": ["Namakkal", "Raipur"] }' ``` ### Pricing This Actor is available under Apify's [Pay Per Event (PPE)](https://docs.apify.com/platform/pricing/pay-per-event) pricing model. You are charged based on compute units consumed during execution. Scraping 13 months of data across all districts typically consumes minimal compute units. ### Limitations - NECC publishes data month-by-month; each month requires a separate form submission - Historical data availability depends on what NECC has published on their website (from 2009 onwards) - Prices shown are NECC suggested prices, which are advisory and not mandatory - The website may occasionally return 500 errors during peak hours; retries are handled automatically ### FAQ **What are NECC egg prices?** NECC (National Egg Co-ordination Committee) publishes daily suggested egg prices for major production and consumption centres across India. These prices serve as a benchmark for the poultry industry. **How many districts are available?** The scraper auto-detects all available districts from the NECC website. Currently there are 35+ centres including Namakkal, Warangal, Mumbai, Delhi, Chennai, Kolkata, and more. **Can I scrape only specific districts?** Yes. Use the `districts` input field to select specific centres. Leave it empty to scrape all available districts. **What date range can I scrape?** Any range from 2009 (earliest available on NECC) to the current date. The default is set to today's date for single-day lookups. **Is the data updated daily?** NECC updates their website with new prices regularly. Run this Actor whenever you need the latest data. **Do I need a proxy?** No. The NECC website does not employ anti-bot measures, so proxy is not required. **What format is the output?** Data is available as JSON via Apify Dataset and as a formatted Excel (.xlsx) file in the Key-Value Store. *** *Data sourced from NECC (National Egg Co-ordination Committee). Prices are suggestive only and not mandatory. This Actor is not affiliated with NECC.* # Actor input Schema ## `startDate` (type: `string`): Start date for scraping egg prices ## `endDate` (type: `string`): End date for scraping egg prices ## `places` (type: `array`): Select places to scrape egg prices. Leave empty to scrape all available places. ## Actor input object example ```json { "startDate": "2026-04-02", "endDate": "2026-04-02" } ``` # Actor output Schema ## `dataset` (type: `string`): Date-wise egg prices for all selected places in JSON format # 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("akash9078/necc-egg-price-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 = {} # Run the Actor and wait for it to finish run = client.actor("akash9078/necc-egg-price-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 '{}' | apify call akash9078/necc-egg-price-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=akash9078/necc-egg-price-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Necc Egg Price Scraper", "description": "NECC Egg Price Scraper is a tool that automatically extracts real-time egg prices published by the National Egg Coordination Committee (NECC). It enables users to track daily price fluctuations across different regions, ensuring accurate, up-to-date market data for analysis, trading, or business.", "version": "0.1", "x-build-id": "ZeoR9ttppbFhFtnIA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/akash9078~necc-egg-price-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-akash9078-necc-egg-price-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/akash9078~necc-egg-price-scraper/runs": { "post": { "operationId": "runs-sync-akash9078-necc-egg-price-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/akash9078~necc-egg-price-scraper/run-sync": { "post": { "operationId": "run-sync-akash9078-necc-egg-price-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startDate", "endDate" ], "properties": { "startDate": { "title": "Start Date", "pattern": "^(\\d{4})-(0[1-9]|1[0-2])-(0[1-9]|[12]\\d|3[01])$", "type": "string", "description": "Start date for scraping egg prices", "default": "2026-04-02" }, "endDate": { "title": "End Date", "pattern": "^(\\d{4})-(0[1-9]|1[0-2])-(0[1-9]|[12]\\d|3[01])$", "type": "string", "description": "End date for scraping egg prices", "default": "2026-04-02" }, "places": { "title": "Places", "type": "array", "description": "Select places to scrape egg prices. Leave empty to scrape all available places.", "items": { "type": "string", "enum": [ "Ahmedabad", "Ajmer", "Allahabad (CC)", "Barwala", "Bengaluru (CC)", "Brahmapur (OD)", "Bhopal", "Chennai (CC)", "Chittoor", "Delhi (CC)", "E.Godavari", "Hospet", "Hyderabad", "Indore (CC)", "Jabalpur", "Kanpur (CC)", "Kolkata (WB)", "Ludhiana", "Luknow (CC)", "Mumbai (CC)", "Muzaffurpur (CC)", "Mysuru", "Nagpur", "Namakkal", "Patna", "Pune", "Raipur", "Ranchi (CC)", "Surat", "Varanasi (CC)", "Vijayawada", "Vizag", "W.Godavari", "Warangal" ] } } } }, "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 } } } } } } } } } } ```