# Optionalpha Strategy Info Parser Spider (`getdataforme/optionalpha-strategy-info-parser-spider`) Actor
The Optionalpha Strategy Info Parser Spider extracts detailed options trading strategy data from Option Alpha. It offers comprehensive, high-quality data extraction, customizable inputs, and structured JSON output for easy integration, making it ideal for traders, analysts, and researchers.
- **URL**: https://apify.com/getdataforme/optionalpha-strategy-info-parser-spider.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** AI, Automation, E-commerce
- **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
## Optionalpha Strategy Info Parser Spider
### Introduction
The Optionalpha Strategy Info Parser Spider is designed to extract detailed information about options trading strategies from Option Alpha. This actor efficiently scrapes data from specified URLs, providing comprehensive insights into various trading strategies, making it an invaluable tool for traders and analysts.
### Features
- **Comprehensive Data Extraction**: Scrapes detailed information about options trading strategies.
- **High Data Quality**: Ensures accurate and up-to-date information from Option Alpha.
- **Efficient Performance**: Quickly processes multiple URLs for fast data retrieval.
- **Customizable Input**: Allows users to specify multiple URLs for targeted scraping.
- **Reliable Output**: Provides structured JSON data for easy integration and analysis.
- **User-Friendly Interface**: Simple configuration and execution through the Apify platform.
- **Versatile Applications**: Suitable for market research, competitive analysis, and more.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|-----------|--------|----------|------------------------------------------|-------------------------------------------------------------------------|
| Urls | Array | No | The URLs for the spider to scrape. | ["https://optionalpha.com/lessons/bull-call-backspread"] |
### Example Usage
#### Example Input
```json
{
"Urls": [
"https://optionalpha.com/lessons/bull-call-backspread",
"https://optionalpha.com/lessons/bull-call-spread"
]
}
````
#### Example Output
```json
[
{
"source_url": "https://optionalpha.com/lessons/bull-call-backspread",
"title": "Bull Call Backspread",
"description": "A bull call backspread is a multi-leg, risk-defined, bullish strategy, with unlimited profit potential...",
"meta_description": "A bull call backspread is a multi-leg, risk-defined, bullish strategy, with unlimited profit potential...",
"breadcrumbs": ["Home", "Education", "Courses", "Bullish Strategies", "Bull Call Backspread"],
"content": "A bull call backspread is similar to a long call option as far as your outlook on the underlying stock...",
"transcript": "The text is the output of AI-based and/or outsourced transcribing from the audio and/or video recording...",
"instructor": {
"name": "Kirk Du Plessis",
"role": "Founder",
"profile_url": "https://optionalpha.com/team/kirk-duplessis"
},
"tags": ["Options", "Strategies"],
"last_updated": "Sep 23, 2022",
"published_date": "Feb 11, 2021",
"scraped_date": "2026-04-24",
"scraped_time": "11:35:27",
"actor_id": "5ibeZnmzvMvs7wrYQ",
"run_id": "IPoPdzEzZAWXu0vh5"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gain insights into trading strategies for better decision-making.
- **Competitive Intelligence**: Monitor and analyze competitor strategies.
- **Price Monitoring**: Track changes in strategy pricing and profitability.
- **Content Aggregation**: Collect and organize educational content on trading strategies.
- **Academic Research**: Use data for studies on financial strategies and market behavior.
- **Business Automation**: Automate data collection for financial analysis and reporting.
### Installation and Usage
1. Search for "Optionalpha Strategy Info Parser Spider" 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 structured JSON array where each object contains:
- `source_url`: The URL of the scraped page.
- `title`: The title of the strategy.
- `description`: A detailed description of the strategy.
- `meta_description`: Meta description for SEO purposes.
- `breadcrumbs`: Navigation path on the website.
- `content`: Full content of the strategy page.
- `transcript`: Transcription of any associated media.
- `instructor`: Information about the instructor.
- `tags`: Relevant tags for categorization.
- `last_updated`, `published_date`, `scraped_date`, `scraped_time`: Date and time metadata.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `Urls` (type: `array`):
The urls for the spider.
## Actor input object example
```json
{
"Urls": [
"https://optionalpha.com/lessons/bull-call-backspread",
"https://optionalpha.com/lessons/bull-call-spread",
"https://optionalpha.com/strategies/bull-call-debit-spread"
]
}
```
# 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("getdataforme/optionalpha-strategy-info-parser-spider").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("getdataforme/optionalpha-strategy-info-parser-spider").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 getdataforme/optionalpha-strategy-info-parser-spider --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/optionalpha-strategy-info-parser-spider",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Optionalpha Strategy Info Parser Spider",
"description": "The Optionalpha Strategy Info Parser Spider extracts detailed options trading strategy data from Option Alpha. It offers comprehensive, high-quality data extraction, customizable inputs, and structured JSON output for easy integration, making it ideal for traders, analysts, and researchers.",
"version": "0.0",
"x-build-id": "OQ7ZRd7fuAbrj82rC"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~optionalpha-strategy-info-parser-spider/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-optionalpha-strategy-info-parser-spider",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~optionalpha-strategy-info-parser-spider/runs": {
"post": {
"operationId": "runs-sync-getdataforme-optionalpha-strategy-info-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~optionalpha-strategy-info-parser-spider/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-optionalpha-strategy-info-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"Urls": {
"title": "Urls",
"minItems": 1,
"type": "array",
"description": "The urls for the spider.",
"default": [
"https://optionalpha.com/lessons/bull-call-backspread",
"https://optionalpha.com/lessons/bull-call-spread",
"https://optionalpha.com/strategies/bull-call-debit-spread"
],
"items": {
"type": "string"
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```