# GreatSchools Reviews Scraper - Low-costπŸ’²πŸ”₯⭐🏫 (`delectable_incubator/greatschools-reviews-scraper-low-cost`) Actor Scrape GreatSchools reviews ⭐🏫 with a powerful education review scraper. Extract reviewer types, star ratings, review dates, review text, helpful votes, and school profile data. Ideal for parent sentiment analysis, school reputation monitoring, education research, and K–12 market intelligence πŸ“ŠπŸš€ - **URL**: https://apify.com/delectable\_incubator/greatschools-reviews-scraper-low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Developer tools, Automation, Lead generation - **Stats:** 2 total users, 1 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 and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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

GreatSchools Reviews Scraper

--- ## 🏫⭐ GreatSchools Reviews Scraper πŸ“ŠπŸ’¬ | School Reviews Scraper | Parent & Student Sentiment Analysis ### πŸš€ Extract GreatSchools Reviews Data in Seconds (No Code) The **GreatSchools Reviews Scraper (Apify Actor)** is a powerful, scalable and SEO-optimized review extraction tool designed to collect parent, student, teacher and community feedback directly from GreatSchools school pages. It allows you to **scrape GreatSchools reviews in bulk**, analyze school reputation, monitor education sentiment, build structured review datasets, and export data for research, analytics, reporting, and AI applications. --- ### πŸ”₯ Why This GreatSchools Reviews Scraper? βœ” Best GreatSchools reviews scraper on Apify βœ” Bulk school review extraction βœ” Parent, Student & Teacher review collection βœ” Automatic pagination support βœ” Structured ratings & sentiment data βœ” Export-ready JSON / CSV / Excel datasets βœ” No coding required βœ” Ideal for education researchers, analysts & data teams --- ### 🎯 What This Scraper Does (GreatSchools Review Extraction) This Apify Actor extracts reviews directly from GreatSchools school profile pages. #### πŸ“Œ Core Features: βœ… Scrape GreatSchools parent reviews βœ… Scrape student reviews βœ… Scrape teacher reviews βœ… Community review collection βœ… Automatic pagination handling βœ… URL normalization (/reviews added automatically) βœ… Max reviews per school control βœ… Extract ratings & review metadata βœ… Clean structured output βœ… High-speed extraction engine --- ### ⚑ Input Configuration (Simple & Powerful) #### πŸ”₯ BULK SCHOOL REVIEW MODE (SEO BOOST πŸš€) ```` { "urls": \[ "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School" ], "maxItemsPerUrl": 50 } ``` --- ### πŸ“Š Extracted Review Data (Structured Output) | Field | Description | | -------------- | ----------------------- | | userType | Reviewer type | | starRating | Review rating | | date | Review publication date | | comment | Full review text | | topicalRatings | Category ratings | | wouldRecommend | Recommendation status | | helpfulCount | Helpful votes count | | sourceUrl | School review URL | --- ### πŸ’‘ Use Cases (High Demand SEO Keywords) This GreatSchools scraper is commonly used for: πŸ“Š Parent sentiment analysis 🏫 School reputation monitoring πŸ“ District feedback tracking ⭐ Education review aggregation πŸ“ˆ Public vs charter school comparisons πŸ€– AI training datasets 🧠 Education market research πŸ“‹ School benchmarking projects πŸ” Review intelligence systems ⚑ Bulk review data extraction --- ### πŸš€ Key Features (Apify SEO Optimized) ⚑ Bulk school review scraping πŸ“„ Automatic pagination support 🏫 GreatSchools review extraction ⭐ Rating collection πŸ’¬ Full review text extraction πŸ“Š Structured review datasets πŸ” Stable extraction engine πŸ’Ύ Export-ready results βš™οΈ Scalable cloud execution πŸš€ Fast and reliable scraping --- ### πŸ“€ Output Formats Supported βœ” JSON (structured API-ready) βœ” CSV (spreadsheet analysis) βœ” Excel XLSX (business reporting) βœ” XML (data pipelines) βœ” HTML (dashboards) --- ### πŸ“¦ Example Output ``` { "userType": "Parent", "starRating": "4", "date": "January 12, 2025", "comment": "This school has strong academic programs and very supportive teachers.", "topicalRatings": "Leadership: 4 | Teachers: 5 | Bullying: 4", "wouldRecommend": "Yes", "helpfulCount": "6", "sourceUrl": "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco/" } ```` --- ### πŸ“Š Preconfigured Dataset Views #### πŸ”Ή Overview Clean review table including: β€’ Reviewer Type β€’ Star Rating β€’ Date β€’ Review Text β€’ Recommendation Status β€’ Helpful Votes β€’ School URL Perfect for filtering and export. #### πŸ”Ή Detailed Reviews Extended dataset including: β€’ Full review text β€’ Topical ratings β€’ Recommendation indicators β€’ Helpful votes Ideal for deeper sentiment analysis. #### πŸ”Ή By School URL Group reviews by school profile page. Useful for: β€’ School comparisons β€’ District-level analysis β€’ Reputation benchmarking β€’ Multi-location studies --- ### πŸ”₯ Why This is the BEST GreatSchools Reviews Scraper on Apify? βœ” Optimized for Apify marketplace ranking βœ” Fast review extraction engine βœ” Automatic pagination handling βœ” Parent, student & teacher review support βœ” Clean structured output βœ” Enterprise-ready scalability βœ” Education intelligence ready --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $4.89 / 1000 results --- ### ❓ FAQ (SEO BOOST SECTION) #### Can I scrape multiple schools at once? Yes β€” bulk URL mode is fully supported. #### Does the scraper handle pagination? Yes β€” pagination is automatically processed. #### Can I limit the number of reviews? Yes β€” use maxItemsPerUrl. #### Are parent and student reviews included? Yes β€” parent, student, teacher and community reviews are collected when available. #### Is coding required? No β€” 100% no-code Apify Actor. #### Can I export the data? Yes β€” JSON, CSV, Excel, XML and HTML are supported. --- ### ⚠️ Disclaimer This scraper is an independent automation tool and is not affiliated with, endorsed by, or sponsored by GreatSchools. All trademarks belong to their respective owners. --- ### πŸ”— Related Actors (PrimeScrape Ecosystem) We are building a complete PrimeScrape Education & Reviews Intelligence Suite. πŸ‘‰ More actors coming soon πŸš€ --- ### 🌍 PrimeScrape Ecosystem Built for data scraping, automation, AI training datasets, lead generation, reputation monitoring and market intelligence at scale. πŸ“Š Review extraction 🏫 Education intelligence πŸ“ˆ Sentiment analysis πŸ€– AI datasets βš™οΈ Automation pipelines πŸ” Reputation monitoring --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a review if you like this scraper πŸ“© Contact us for custom scraping solutions and enterprise requests πŸŒͺ️ PrimeScrape https://apify.com/primescrape # Actor input Schema ## `urls` (type: `array`): One or more GreatSchools school URLs to scrape reviews from. You can provide the base school URL or the /reviews URL β€” the scraper will normalize them. Do NOT include ?page= β€” pagination is handled automatically. ## `maxItemsPerUrl` (type: `integer`): Maximum number of reviews to collect per school URL. ## Actor input object example ```json { "urls": [ "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School" ], "maxItemsPerUrl": 20 } ```` # Actor output Schema ## `overview` (type: `string`): No description ## `detailed` (type: `string`): No description ## `by_source` (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.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School" ], "maxItemsPerUrl": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/greatschools-reviews-scraper-low-cost").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 = { "urls": [ "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School", ], "maxItemsPerUrl": 20, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/greatschools-reviews-scraper-low-cost").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 '{ "urls": [ "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School" ], "maxItemsPerUrl": 20 }' | apify call delectable_incubator/greatschools-reviews-scraper-low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/greatschools-reviews-scraper-low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GreatSchools Reviews Scraper - Low-costπŸ’²πŸ”₯⭐🏫", "description": "Scrape GreatSchools reviews ⭐🏫 with a powerful education review scraper. Extract reviewer types, star ratings, review dates, review text, helpful votes, and school profile data. Ideal for parent sentiment analysis, school reputation monitoring, education research, and K–12 market intelligence πŸ“ŠπŸš€", "version": "0.0", "x-build-id": "w2JOV8WawcS4ualV5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~greatschools-reviews-scraper-low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-greatschools-reviews-scraper-low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~greatschools-reviews-scraper-low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-greatschools-reviews-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~greatschools-reviews-scraper-low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-greatschools-reviews-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "School Profile URLs", "type": "array", "description": "One or more GreatSchools school URLs to scrape reviews from. You can provide the base school URL or the /reviews URL β€” the scraper will normalize them. Do NOT include ?page= β€” pagination is handled automatically.", "items": { "type": "string" }, "default": [ "https://www.greatschools.org/california/san-francisco/31959-The-New-School-Of-San-Francisco", "https://www.greatschools.org/california/san-francisco/16863-Feinstein-Dianne-Elementary-School" ] }, "maxItemsPerUrl": { "title": "Max Reviews per URL", "type": "integer", "description": "Maximum number of reviews to collect per school URL. ", "default": 20 } } }, "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 } } } } } } } } } } ```