AI Analysis
The package has minimal risks associated with network calls, shell executions, obfuscations, and credential harvesting. However, the metadata risk score is elevated due to the potential inactivity or newness of the maintainer and lack of community engagement.
- No network calls detected
- No shell execution patterns
- No obfuscation patterns
- No credential harvesting patterns
- Maintainer may be new or inactive
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.
Package Quality Overall: Medium (6.6/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Documentation URL: "Documentation" -> https://manager.materials.docs.pyansys.comDetailed PyPI description (5603 chars)
Some contribution signals present
Separate author ("ANSYS, Inc.") and maintainer ("PyAnsys developers") listedDevelopment Status classifier >= Beta
Partial type annotation coverage
114 type-annotated function signatures detected in source
Active multi-contributor project
4 unique contributor(s) across 100 commits in ansys/pymaterials-managerSmall but multi-author team (3–4 contributors)
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: ansys.com
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
1 maintainer concern(s) found
Author "ANSYS, Inc." appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a comprehensive material management tool using the 'ansys-materials-manager' Python package. This tool will serve as a bridge between various ANSYS applications, allowing users to efficiently manage materials across different simulations. Here are the key steps and features of your project: 1. **Setup Environment**: Ensure you have the 'ansys-materials-manager' package installed. If not, install it via pip. 2. **User Interface**: Develop a simple but intuitive GUI using Tkinter or any other preferred library. The interface should allow users to add, edit, and delete material data easily. 3. **Material Database Integration**: Utilize 'ansys-materials-manager' to integrate with existing material databases within ANSYS applications. Allow users to import material data from these sources directly into your tool. 4. **Material Data Management**: Implement functionalities to store and retrieve material data locally. Users should be able to add new materials, modify existing ones, and delete materials from the database. 5. **Export Capabilities**: Enable users to export material data in formats compatible with ANSYS applications, ensuring seamless integration with simulation tools. 6. **Visualization**: Incorporate basic visualization capabilities to display material properties graphically. This could include plotting stress-strain curves or other relevant graphs based on user selection. 7. **Documentation**: Provide clear documentation explaining how to use the tool effectively, including setup instructions and examples. Your goal is to create a versatile tool that simplifies the process of managing material data across multiple ANSYS applications, enhancing productivity and accuracy in engineering simulations.
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