# High School Email Scraper (`scrapers-hub/high-school-email-scraper`) Actor 🎓 High School Email Scraper extracts verified high school contact emails from public sources. ⚡ Fast, accurate, and privacy-aware—ideal for outreach, partnerships, and lead generation. ✅ Export-ready results for B2B marketing teams. - **URL**: https://apify.com/scrapers-hub/high-school-email-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### High School Email Scraper 📬 **High School Email Scraper** automates finding and extracting contact emails for high schools and related institutions. If you’re trying to **find high school email addresses**, build a **school district email scraper** list, or run an **education contact email scraper** workflow, this actor helps you pull emails (plus phone numbers and social links) from publicly available web sources—at scale, so you don’t waste hours doing manual outreach research. --- ### 🚀 Why choose High School Email Scraper? | Feature | Benefit | |---|---| | ✅ One run to find businesses + extract contact details | Collects email addresses along with phone numbers and social media profiles for faster list building | | ✅ Location-based scraping with per-location and global limits | Lets you control output volume with `maxBusinesses` and `scrapeMaxBusinessesPerLocation` | | ✅ Reliability options with built-in proxy support | Improves stability for larger **K-12 email scraper** tasks and reduces request failures | | ✅ Structured dataset output ready for analysis | Saves results to the **Business Contact Data** dataset with consistent fields | | ✅ Resilient website processing with fallbacks | Uses a robust scraping pipeline so you get results even when some pages are missing data | | ✅ Scales with concurrency for faster throughput | Scrapes multiple websites in parallel to reach your target faster | --- ### 🔑 Key features - 📍 **High School search by location**: Uses your `googleMapsLocation` values to target specific regions - 🔎 **Keyword-driven results**: Uses `googleMapsSearchTerm` (prefilled with “High School”) to focus on the type of institutions you want - 🧠 **Smart limits for list building**: Supports a global `maxBusinesses` limit or per-location limits via `scrapeMaxBusinessesPerLocation` - 🛡️ **Proxy configuration for more reliable scraping**: Includes proxy support via `proxyConfiguration` (recommended for large-scale scraping) - 📞 **Phone number extraction**: Extracts phone numbers when scraping each website - 🔗 **Social media extraction**: Extracts social media links alongside emails - 💾 **Dataset-ready, flattened results**: Pushes results to Apify datasets immediately (including one row per email when emails are found) - 📊 **Contact-focused website crawl**: Prioritizes common contact-oriented pages and extracts emails from them --- ### 📝 Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "High School", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `googleMapsSearchTerm` | Yes | Enter the business type or niche for the email scraper (for example “coffee shops”, “dentists”). For this actor it’s prefilled with `High School`. | | `googleMapsLocation` | Yes | Target geographic locations to search (for example `["Miami, Florida"]` or `["New York"]`). | | `maxBusinesses` | No | Maximum number of businesses to find (range: 1–1000). The scraper stops when it reaches this target. | | `scrapeMaxBusinessesPerLocation` | No | If enabled, collects up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for large-scale scraping. | ##### `proxyConfiguration` (nested) | Field | Required | Description | |---|---:|---| | `proxy support` | No | Set to `true` to enable Apify Proxy (prefilled as `true`). | *** ### 📦 Output The actor saves results into the **Business Contact Data** Apify dataset. When emails are found, it pushes **one row per email** with a flattened `email_found` field. Sample output row: ```json { "name": "Example High School", "website": "https://www.examplehighschool.edu", "phone": "123-456-7890", "full_address": "123 Main St New York NY 10001 US", "city": "New York", "state": "NY", "zip": "10001", "country_code": "US", "scraped_emails": [], "scraped_phones": ["+11234567890"], "scraped_social_media": ["https://www.linkedin.com/company/example/"], "emails_found": 2, "pages_scraped": 5, "avg_rating": 4.4, "total_reviews": 120, "lat": 40.7128, "long": -74.006, "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "scrape_status": "success", "email_found": "contact@examplehighschool.edu" } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `name` | string | Business name | | `website` | string | Business website URL | | `phone` | string | Phone value associated with the business listing | | `full_address` | string | Combined address string built from street address, city, state, zip, and country code | | `city` | string | City | | `state` | string | State | | `zip` | string | ZIP/postal code | | `country_code` | string | Country code | | `scraped_emails` | array | List of scraped emails (emptied in flattened per-email rows) | | `scraped_phones` | array | Scraped phone numbers found on the business website | | `scraped_social_media` | array | Scraped social media links found on the business website | | `emails_found` | number | Count of emails found for the business | | `pages_scraped` | number | Number of processed URLs/pages during website scraping | | `avg_rating` | number | Average rating from the business listing | | `total_reviews` | number | Total reviews count from the business listing | | `lat` | number | Latitude | | `long` | number | Longitude | | `place_id` | string | Place identifier | | `scrape_status` | string | Scrape status (for example `success`, `failed`, `no_website`, or `error`) | | `email_found` | string | Email address for this specific dataset row (present when pushing one row per email) | Note: if a business has **no website**, the actor sets `scrape_status` to `no_website` and populates `scraped_emails`, `scraped_phones`, `scraped_social_media`, `emails_found`, and `pages_scraped` accordingly. *** ### 🧭 How to use High School Email Scraper (via Apify Console) 1. **Open Apify Console**: Go to [console.apify.com](https://console.apify.com) and sign in. 2. **Find the actor**: Search for **High School Email Scraper** in the Actors marketplace. 3. **Add your search inputs**: In the **INPUT** section, set: - `googleMapsSearchTerm` (defaults to `High School`) - `googleMapsLocation` (one or more locations) 4. **Set your output volume** (optional but recommended): - Use `maxBusinesses` to control how many businesses you want - Choose whether `scrapeMaxBusinessesPerLocation` is `true` (per location) or `false` (global combined limit) 5. **Configure proxies for reliability** (optional): - In `proxyConfiguration`, use `proxy support` (prefilled as `true`) for better stability on larger runs 6. **Run the actor**: Click **Run**. You’ll see progress logs while it searches and then scrapes websites for contact details. 7. **Open your dataset results**: After completion, check the **Business Contact Data** dataset, then export to JSON/CSV from the dataset UI. No coding required—get accurate **high school contact email finder** results in minutes. *** ### ⚙️ Advanced features & SEO optimization - ✨ **Engineered for education outreach lists**: Optimized for **automated email scraping for schools** workflows where you need emails, phones, and social links together - 🧩 **Flexible targeting**: Use `googleMapsSearchTerm` + `googleMapsLocation` to build a **school district email scraper** pipeline for different regions - 📌 **Contact-intent page extraction**: Prioritizes common contact-oriented sections of school websites to improve email discovery for **school website email extraction** use cases - 🛡️ **Reliability options for scale**: Proxy configuration and resilient website scraping help keep runs stable when scraping many domains *** ### 🎯 Best use cases - 📈 **Lead generation for school vendors**: Build a teacher email list scraper dataset for outreach to schools by city or state - 🏫 **Public school email scraper research**: Quickly assemble **public school email scraper** contacts for studies and reporting - 🧾 **School district email scraper list building**: Create segmented contacts for district stakeholders when collecting K-12 communication targets - 👥 **Student recruitment & college prep outreach**: Find contacts for college prep schools and related educational institutions using education contact email scraping workflows - 🗂️ **Marketing automation data prep**: Feed a CRM with emails plus phones and social links for multichannel campaigns - 🔍 **Data analysis & enrichment**: Combine ratings, review counts, and extracted contacts for structured research on education providers - 🛠️ **Ops and internal tools**: Use the dataset output to power internal email harvesting tool for schools dashboards and pipelines *** ### 🧰 Technical specifications - **Supported Input Formats** - ✅ Apify Console input (`input.json` object) - ✅ `googleMapsLocation` as an array of strings - ✅ `googleMapsSearchTerm` as a string - **Proxy Support** - ✅ `proxyConfiguration.proxy support` supported (recommended for large-scale scraping) - **Retry Mechanism** - ✅ Includes retries and fallbacks for resilience during scraping (handled internally) - **Dataset Structure** - ✅ Outputs to the **Business Contact Data** dataset - ✅ Uses flattened `email_found` rows when emails are found - **Rate Limits & Performance** - ✅ Uses parallel website scraping with concurrency to improve throughput - **Limitations** - ❌ Results depend on what each school’s publicly available website provides (some sites may not expose emails) - ❌ Businesses with no website are saved with empty scraped contact fields and `scrape_status` set to `no_website` *** ### ❓ FAQ #### How does High School Email Scraper find email addresses? ✅ It searches for businesses using your `googleMapsSearchTerm` and `googleMapsLocation`, then scrapes each business website to extract emails, phone numbers, and social media links from publicly available content. #### What data does High School Email Scraper output? ✅ The actor saves business-level details (name, website, address, rating/reviews, coordinates) plus extracted contacts (emails, phones, social links). When emails are found, it pushes one dataset row per email via `email_found`. #### Can I limit results per location or globally? ✅ Yes. Use `scrapeMaxBusinessesPerLocation` to choose whether `maxBusinesses` applies per location or as a single combined total limit across all provided locations. #### Do I need proxies to run the actor? ❌ Not strictly, but proxy configuration is recommended for larger runs. You can set `proxyConfiguration.proxy support` (prefilled as `true`) to enable proxy support. #### What should I set `maxBusinesses` to? ✅ Set `maxBusinesses` to the number of businesses you want to target (range 1–1000). The actor stops once it reaches your target. #### Can I use this for outreach or lead generation? ✅ Yes—this actor is designed for building outreach-ready datasets such as a **school staff email scraper** list. Always ensure your outreach complies with applicable laws and platform policies (GDPR/CCPA, spam regulations, etc.). #### Is email validation enabled? ✅ The website scraping configuration includes `validate_emails`, which is read from your input as `validateEmails` in the code path (even though it isn’t exposed in the provided input schema). If you need guaranteed validation behavior, confirm with your Apify input settings for your run. *** ### 🤝 Support & feature requests Want to improve High School Email Scraper or request enhancements for your school email scraping workflow? - 💡 **Feature Requests**: Ideas like CSV export, custom output shaping, or additional contact fields are welcome—share what would help your **K-12 email scraper** use case. - 📧 **Contact**: Email us at Your feedback directly helps shape future updates to High School Email Scraper. *** *If you’re looking for the most comprehensive High School Email Scraper for school contact data, you’re in the right place—run it with your keywords and locations, then export your dataset for instant use.* *** ### Disclaimer **This tool only accesses publicly accessible sources.** It does not access private profiles, authenticated data, or password-protected pages. Legal compliance (including GDPR, CCPA, spam regulations, and applicable platform Terms of Service) is your responsibility. If you need data removal, contact us at . Please use High School Email Scraper responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "High School", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "googleMapsSearchTerm": "High School", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/high-school-email-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 = { "googleMapsSearchTerm": "High School", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/high-school-email-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 '{ "googleMapsSearchTerm": "High School", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call scrapers-hub/high-school-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/high-school-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "High School Email Scraper", "description": "🎓 High School Email Scraper extracts verified high school contact emails from public sources. ⚡ Fast, accurate, and privacy-aware—ideal for outreach, partnerships, and lead generation. ✅ Export-ready results for B2B marketing teams.", "version": "1.0", "x-build-id": "bY7rb3vXeDZ2Xmds5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~high-school-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-high-school-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~high-school-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-high-school-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~high-school-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-high-school-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "googleMapsLocation", "googleMapsSearchTerm" ], "properties": { "googleMapsSearchTerm": { "title": "Search Term", "type": "string", "description": "Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists').", "default": "High School" }, "googleMapsLocation": { "title": "Location", "type": "array", "description": "Target geographic location for the email scraper (e.g., 'Miami, Florida').", "default": [ "New York" ], "items": { "type": "string" } }, "maxBusinesses": { "title": "Maximum Businesses With Emails", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 5 }, "scrapeMaxBusinessesPerLocation": { "title": "Scrape Max Businesses Per Location", "type": "boolean", "description": "If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```