asteroid_spinprops

v1.5.0 safe
3.0
Low Risk

Collection of tools used for fitting sHG1G2 and SOCCA photometric models to sparse asteroid photometry

🤖 AI Analysis

Final verdict: SAFE

The package appears safe with very low risks across all assessed categories, suggesting it is unlikely to pose a direct threat. However, the metadata risk score is slightly elevated due to the maintainer's single package, which warrants monitoring for future updates.

  • Low network and shell execution risks
  • No obfuscation or credential harvesting attempts
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls suggest normal behavior for a library focused on local computation.
  • Shell: No shell executions indicate the package does not attempt to execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, indicating potential newness or inactivity, but no other red flags were raised.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5111 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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: proton.me

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Odysseas" 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 asteroid_spinprops 
Develop a web-based application using Python's Flask framework that allows astronomers to upload sparse asteroid photometry data and receive fitted parameters from the sHG1G2 and SOCCA photometric models provided by the 'asteroid_spinprops' package. The application should have the following features:

1. User Authentication: Users should be able to register, log in, and manage their accounts.
2. Data Upload: A feature allowing users to upload CSV files containing their asteroid photometry data.
3. Model Fitting: Utilize the 'asteroid_spinprops' package to fit the uploaded data against both the sHG1G2 and SOCCA models. The results should include key parameters such as shape, orientation, and rotation period.
4. Visualization: Display the fitted model over the original data points in an interactive plot. This plot should allow users to zoom in/out, pan, and toggle between the two models.
5. Results Export: Provide an option for users to download the fitted parameters in a downloadable CSV file.
6. Documentation: Include a user-friendly guide explaining how to use the app, including details on the expected format of the input data and explanations of the output parameters.

The application should be deployed on a cloud platform like Heroku or AWS, ensuring it is accessible to the global astronomy community. The goal is to provide a tool that simplifies the complex process of analyzing asteroid photometry data, making advanced modeling techniques more accessible to researchers.

💬 Discussion Feed

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