ansys-optislang-core

v1.5.0 suspicious
4.0
Medium Risk

A Python wrapper for Ansys optiSLang application.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some potential red flags, particularly concerning shell execution and incomplete author metadata, which raises suspicion despite the lack of direct threats like network calls or credential harvesting.

  • Shell execution present
  • Incomplete author metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal and expected.
  • Shell: Shell execution is present but without context it's hard to determine intent; however, it could potentially be used for legitimate purposes such as running system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's details are incomplete and the author has only one package, which could indicate a less experienced or potentially suspicious account.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://optislang.docs.pyansys.com
  • Detailed PyPI description (7644 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

  • 543 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 7 unique contributor(s) across 100 commits in ansys/pyoptislang
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • # Process can be either subprocess.Popen (Python) or System.Diagnostics.Process (IronPython) s
  • tion self.__process = subprocess.Popen( # nosec B603 args, env=env_vars,
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: ansys.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository ansys/pyoptislang 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 ansys-optislang-core 
Your task is to develop a mini-application that leverages the 'ansys-optislang-core' Python package to create a user-friendly interface for performing robust design optimization on engineering components. This application will allow users to input various parameters related to their component design, such as material properties, dimensions, and loads, and then use optiSLang to perform sensitivity analysis and optimization studies.

### Step-by-Step Instructions:
1. **Setup Environment**: Ensure your development environment is set up with Python and the 'ansys-optislang-core' package installed. If not already installed, you can install it via pip.
2. **User Input Form**: Design a simple form where users can input details about their component, including materials, dimensions, and applied loads. This could be a command-line interface or a GUI using a library like Tkinter or PyQt.
3. **optiSLang Integration**: Use the 'ansys-optislang-core' package to integrate with optiSLang. Your application should be able to take the user inputs and convert them into a format that optiSLang can understand and process.
4. **Sensitivity Analysis**: Implement functionality to perform sensitivity analysis on the given parameters. This involves identifying which parameters have the most significant impact on the performance of the component.
5. **Optimization Studies**: Enable users to run optimization studies based on their input data. The application should be able to suggest optimal values for the parameters to maximize or minimize specific performance metrics.
6. **Results Presentation**: After processing, present the results back to the user in an understandable format. This could include graphs, tables, or detailed reports.
7. **Documentation & Testing**: Write comprehensive documentation explaining how to use the application and its functionalities. Additionally, ensure thorough testing of all features to guarantee reliability.

### Suggested Features:
- Support for multiple types of engineering components (e.g., beams, plates, shafts).
- Ability to define custom performance metrics for optimization.
- Option to visualize the sensitivity analysis results graphically.
- Export results to common file formats like CSV or PDF for further analysis.
- Provide examples and templates for different types of components to help new users get started.

By following these steps and incorporating the suggested features, you'll create a powerful yet accessible tool for engineers looking to optimize their designs using the capabilities of optiSLang.