aiowiserbyfeller

v1.1.0 safe
3.0
Low Risk

Wiser by Feller µGateway API

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories with no network calls, shell executions, obfuscations, or credential harvesting activities detected. The metadata risk score is slightly elevated due to incomplete maintainer information.

  • No network calls detected
  • Incomplete maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is typical for many packages and does not indicate risk unless the package's functionality requires external communication.
  • Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package has no associated GitHub repository and the maintainer's author information is incomplete, indicating potential low activity or newness.

📦 Package Quality Overall: Low (4.8/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • 7 test file(s) detected (e.g. test_api_account.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4891 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 183 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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: syonix.ch>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 aiowiserbyfeller 
Create a fully-functional mini-app that serves as a home automation dashboard using the 'aiowiserbyfeller' Python package. This application will allow users to control their smart home devices connected to the Wiser by Feller µGateway, including lights, thermostats, and other IoT-enabled devices. Your goal is to develop an intuitive UI where users can monitor and adjust settings in real-time.

### Core Features:
- **Device Control**: Allow users to turn lights on/off, set thermostat temperatures, and control other connected devices.
- **Real-Time Monitoring**: Display current status of all connected devices, such as temperature readings, light brightness levels, etc.
- **Historical Data**: Provide graphs or charts showing past data for temperature, energy consumption, etc.
- **User Authentication**: Implement basic user authentication to secure access to the dashboard.
- **Mobile Responsiveness**: Ensure the dashboard is mobile-friendly and accessible via smartphones.

### Utilization of 'aiowiserbyfeller':
- Use 'aiowiserbyfeller' to establish a connection to the Wiser by Feller µGateway and retrieve device statuses.
- Leverage the package's functionalities to send commands to devices, such as turning lights on/off or adjusting thermostat settings.
- Integrate with the package's event listeners to update the UI in real-time when changes occur on the µGateway.

### Development Steps:
1. **Setup Environment**: Install necessary packages, including 'aiowiserbyfeller', and any frontend frameworks/libraries you choose.
2. **Connect to µGateway**: Write code to connect to the Wiser by Feller µGateway using 'aiowiserbyfeller'.
3. **Fetch Device Data**: Retrieve and display device statuses and historical data on your dashboard.
4. **Implement Controls**: Create interactive controls for users to manage their devices.
5. **Add Real-Time Updates**: Ensure the dashboard updates automatically based on events from the µGateway.
6. **Security Measures**: Implement user authentication to protect sensitive information.
7. **Responsive Design**: Optimize the UI for different screen sizes.
8. **Testing & Deployment**: Thoroughly test the application and deploy it to a web server or cloud service.

This project aims to showcase the capabilities of 'aiowiserbyfeller' while providing a practical solution for managing smart homes.