astrapeum

v0.1.0 suspicious
4.0
Medium Risk

Geometry and tuning tools for the Astrapeum basin system.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package appears to have low technical risks but exhibits signs of low effort and potential inactivity, raising some suspicion about its legitimacy.

  • Metadata risk at 5 out of 10
  • Low effort or potential inactivity indicators
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution detected, indicating the package likely does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some signs of low effort and could be new or inactive, raising moderate suspicion.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

  • Test runner config found: pyproject.toml
  • 2 test file(s) detected (e.g. test_geometry.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1181 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 24 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "WitchMithras" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with astrapeum 
Create a Python-based mini-application that allows users to design and optimize their own Astrapeum basin systems. This application should leverage the 'astrapeum' package to perform geometry calculations and tuning for optimal performance. Here are the steps and features your app should include:

1. **User Interface**: Develop a simple yet intuitive UI using a library like Tkinter or PyQt. This interface should allow users to input basic parameters of their desired basin system such as dimensions, material types, and environmental conditions.
2. **Geometry Calculation**: Use the 'astrapeum' package to calculate the geometric properties of the basin based on user inputs. Display these results clearly within the UI.
3. **Tuning Optimization**: Implement a feature where the application automatically tunes the basin system for optimal water retention and drainage, based on the user's specifications. Use the 'astrapeum' package's tuning tools to achieve this.
4. **Visualization**: Allow users to visualize their designed basin system through 2D or 3D plots. Utilize libraries like Matplotlib or Plotly for this purpose.
5. **Export Options**: Provide options for users to export their designs in various formats such as PDF, PNG, or even 3D model files like STL.
6. **Help and Documentation**: Include comprehensive help sections and tooltips within the application to guide users through the process and explain the significance of each parameter and calculation.

Ensure that your application is well-documented and includes error handling to provide meaningful feedback to users when incorrect inputs are provided.

💬 Discussion Feed

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