# EDX Discovery Scraper (`getdataforme/edx-discovery-scraper`) Actor
The EDX Discovery Scraper extracts detailed course data from EDX, including descriptions, pricing, and organization info, aiding market research and competitive analysis....
- **URL**: https://apify.com/getdataforme/edx-discovery-scraper.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** Lead generation, Other, Agents
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $9.00 / 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.
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
## EDX Discovery Scraper
### Introduction
The EDX Discovery Scraper is a powerful tool designed to extract detailed course information from the EDX platform. It enables users to gather comprehensive data on courses, including descriptions, pricing, and organizational details, facilitating market research, competitive analysis, and content aggregation.
### Features
- **Comprehensive Data Extraction**: Scrapes detailed course information including descriptions, pricing, and organizational details.
- **High Data Quality**: Ensures accurate and up-to-date information directly from EDX.
- **Customizable Searches**: Allows users to specify search queries for targeted data extraction.
- **Efficient Performance**: Capable of handling large volumes of data with a high degree of reliability.
- **Proxy Support**: Utilizes Apify's residential proxy network to ensure anonymity and avoid IP bans.
- **Scalable**: Easily handles varying data loads, from small to large-scale scraping tasks.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|---------------------|----------|----------|-----------------------------------------------------------------------------|----------------|
| `searchQuery` | String | Yes | Enter the Search Keywords | "data" |
| `maxItems` | Integer | No | Maximum number of items to scrape. | 100 |
| `proxyConfiguration`| Object | No | Specifies proxy servers to be used by the scraper to hide its origin. | See below |
#### Proxy Configuration Example
```json
{
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US"
}
````
### Example Usage
#### Example Input
```json
{
"searchQuery": "data science",
"maxItems": 50,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US"
}
}
```
#### Example Output
```json
[
{
"id": "91f52ef3-fa3f-4934-9d19-8d5a32635cd4",
"name": "Data Science: R Basics",
"source": "edx",
"type": "course",
"subType": "Course",
"slug": "learn/r-programming/harvard-university-data-science-r-basics",
"description": "The first in our Professional Certificate Program in Data Science...
",
"shortDescription": "Build a foundation in R and learn how to wrangle, analyze, and visualize data.
",
"imageUrl": "https://prod-discovery.edx-cdn.org/cdn-cgi/image/width=auto,height=auto,quality=75,format=webp/media/course/image/91f52ef3-fa3f-4934-9d19-8d5a32635cd4-d99e27f09d19.jpg",
"destinationUrl": "https://www.edx.org/learn/r-programming/harvard-university-data-science-r-basics",
"organization": {
"name": "Harvard University",
"logoUrl": "https://prod-discovery.edx-cdn.org/organization/logos/44022f13-20df-4666-9111-cede3e5dc5b6-2cc39992c67a.png"
},
"meta": {
"productType": "Course",
"completionTimeText": "8 weeks",
"flexibilityLabel": "Self-paced",
"highestLevel": "Introductory",
"learningOutcome": "1 certificate",
"listPriceFormatted": "$219",
"strikethroughPriceFormatted": ""
},
"subjects": [
"Data Analysis & Statistics",
"Computer Science"
],
"skills": [
"Data Science",
"Git (Version Control System)",
"Data Wrangling",
"RStudio",
"Document Preparations",
"Sorting",
"Data Visualization",
"Machine Learning",
"R (Programming Language)",
"Data Analysis",
"Ggplot2",
"Unix",
"Dplyr",
"Version Control",
"Github",
"Probability",
"Linux",
"File Organization"
],
"level": "Introductory",
"flexibility": "self_paced",
"weeksToComplete": 8,
"minHoursEffortPerWeek": 1,
"courseCount": 0,
"language": [
"English"
],
"listPrice": 219,
"strikethroughPrice": 0,
"currencyCode": "USD",
"availability": [
"Current"
],
"partner": [
"Harvard University"
],
"sortPosition": 0,
"scrapedAt": "2026-05-29T09:42:21.183Z"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather insights on educational trends and course offerings.
- **Competitive Intelligence**: Monitor competitor course offerings and pricing strategies.
- **Price Monitoring**: Track changes in course pricing and availability.
- **Content Aggregation**: Compile comprehensive course data for educational platforms.
- **Academic Research**: Analyze educational content and trends for research purposes.
- **Business Automation**: Automate data collection for educational service providers.
### Installation and Usage
1. Search for "EDX Discovery Scraper" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).
### Output Format
The output is a JSON array where each object contains detailed information about a course, including fields like `id`, `name`, `description`, `organization`, `subjects`, `skills`, and more. This structured format allows for easy integration into various applications and analysis tools.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form: [Contact Us](https://getdataforme.com/contact/)
We're here to help you get the most out of this Actor!
# Actor input Schema
## `searchQuery` (type: `string`):
Enter the Search Keywords
## `maxItems` (type: `integer`):
Maximum number of items to scrape.
## `proxyConfiguration` (type: `object`):
Specifies proxy servers that will be used by the scraper in order to hide its origin.
## Actor input object example
```json
{
"searchQuery": "data",
"maxItems": 100,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}
```
# 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 = {
"searchQuery": "data",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/edx-discovery-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 = {
"searchQuery": "data",
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US",
},
}
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/edx-discovery-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 '{
"searchQuery": "data",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}' |
apify call getdataforme/edx-discovery-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/edx-discovery-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "EDX Discovery Scraper",
"description": "The EDX Discovery Scraper extracts detailed course data from EDX, including descriptions, pricing, and organization info, aiding market research and competitive analysis....",
"version": "0.0",
"x-build-id": "dheax25D3YnOvjOsr"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~edx-discovery-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-edx-discovery-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~edx-discovery-scraper/runs": {
"post": {
"operationId": "runs-sync-getdataforme-edx-discovery-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~edx-discovery-scraper/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-edx-discovery-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"searchQuery"
],
"properties": {
"searchQuery": {
"title": "Search Query",
"type": "string",
"description": "Enter the Search Keywords",
"default": "data"
},
"maxItems": {
"title": "Max Items",
"type": "integer",
"description": "Maximum number of items to scrape.",
"default": 100
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```