🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with network, shell, obfuscation, and credential handling. However, the metadata risk score is slightly elevated due to incomplete author details and a potentially new or inactive account.

Low risk scores across major categories
Elevated metadata risk due to incomplete author details

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating secure handling of secrets.
Metadata: The author's details are incomplete and the account seems new or inactive, which raises some concern but not enough to strongly indicate malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: outlook.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository BolunHan/PyEventEngine appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with PyEventEngine

Your task is to create a real-time stock price monitoring application using Python and the PyEventEngine package. This application will allow users to track multiple stocks in real-time and receive notifications when certain price thresholds are met. Here’s a step-by-step guide on how to build this application:

1. **Setup Environment**: Ensure you have Python installed and create a virtual environment for your project. Install the necessary packages including PyEventEngine and any required libraries for web scraping or API integration (such as requests or pandas).

2. **Define Core Components**: Use PyEventEngine to define event listeners and handlers for stock price updates. Each stock will have its own event listener that triggers based on price changes.

3. **Data Retrieval**: Implement a function to fetch real-time stock prices. This could involve scraping data from financial websites or using APIs provided by financial services like Alpha Vantage or Yahoo Finance.

4. **Threshold Notifications**: Configure the application to monitor specific stocks and set up threshold alerts. When a stock’s price crosses a predefined threshold, the user should be notified via email, SMS, or a simple alert within the application.

5. **User Interface**: Develop a basic GUI using Tkinter or a web interface using Flask or Django where users can input the stock symbols they wish to monitor and view real-time price updates.

6. **Testing and Validation**: Test the application thoroughly to ensure it accurately retrieves stock prices and sends notifications correctly. Validate that the event engine functions as expected, handling multiple events efficiently without performance issues.

7. **Deployment**: Once testing is complete, consider deploying the application either locally or online, depending on your requirements.

Suggested Features:
- Support for multiple stock symbols to be monitored simultaneously.
- Adjustable price thresholds for different stocks.
- Historical data analysis and charting capabilities.
- User authentication and personalization options.
- Integration with external services for more comprehensive financial data.

By following these steps and utilizing PyEventEngine effectively, you’ll develop a powerful tool for real-time stock price monitoring that can provide valuable insights to investors.