astropydantic

v0.1.0 safe
2.0
Low Risk

(No description)

🤖 AI Analysis

Final verdict: SAFE

The package appears safe with no detected risks such as network calls, shell executions, obfuscations, or credential harvesting. The metadata risk is slightly elevated due to a new maintainer account and lack of PyPI classifiers, but this does not indicate a supply-chain attack.

  • No network calls detected
  • Maintainer has a new or low activity account
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate risk of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or low activity account and lacks PyPI classifiers, indicating potential low effort or poor metadata quality.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • 5 test file(s) detected (e.g. test_fastapi.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5553 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

  • 14 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: joshborrow.com>

✓ 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 "Maximilian Linhoff" 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 astropydantic 
Create a fully-functional mini-application called 'AstroDataAnalyzer' using Python, which leverages the 'astropydantic' package to handle astronomical data with units and quantities seamlessly. The application should allow users to input various astronomical measurements with their respective units (e.g., distance in parsecs, temperature in Kelvin), perform basic calculations like addition, subtraction, multiplication, division, and conversion between different units, and display the results with appropriate units. Additionally, the app should be able to serialize these measurements into a JSON format and deserialize them back into usable objects for further analysis. Here are the steps and features your application should include:

1. **Setup**: Begin by setting up a virtual environment for your project and installing necessary packages including 'astropy', 'pydantic', and 'astropydantic'.
2. **Input Handling**: Design a user-friendly interface where users can enter values along with their units (e.g., '300 m/s'). Utilize 'astropydantic' to validate and convert these inputs into Astropy Quantity objects.
3. **Calculation Module**: Implement a module that supports basic arithmetic operations on these quantities, ensuring that operations respect the physical dimensions of the quantities involved (e.g., you cannot add velocity to temperature).
4. **Unit Conversion**: Allow users to specify a target unit for their result, and implement functionality to convert the final result to this unit if possible.
5. **Serialization/Deserialization**: Use 'astropydantic' to serialize the entered data and calculation results into a JSON format, and provide a way to deserialize this JSON back into Astropy Quantity objects for further use.
6. **Output Display**: Ensure that all outputs are displayed in a human-readable format, showing both the numerical value and its corresponding unit.
7. **Documentation**: Write comprehensive documentation for your application, explaining how each feature works and how 'astropydantic' is utilized throughout the codebase.
8. **Testing**: Develop test cases to verify that your application functions correctly, especially focusing on edge cases and error handling.

Your goal is to demonstrate the power and flexibility of 'astropydantic' in managing complex astronomical data while keeping the user interface intuitive and the underlying code robust.

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