astro-mmdc

v0.2.2 safe
3.0
Low Risk

Python SDK for the MMDC astrophysics platform — SED data access and blazar broadband emission modeling

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with a low risk score. It has a clear purpose related to astrophysics and makes expected network calls without any signs of malicious activity.

  • Low network risk as expected for a data-fetching package
  • No evidence of shell execution, obfuscation, or credential harvesting
Per-check LLM notes
  • Network: The network call pattern suggests the package is making HTTP requests, which could be legitimate if it's an astronomy or space-related package that fetches data from remote servers.
  • Shell: No shell execution patterns detected, indicating no immediate risk related to command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository is not found, and the maintainer has only one package which may indicate a new or less active account.

📦 Package Quality Overall: Medium (5.6/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

  • Test runner config found: conftest.py
  • 4 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://mmdc.am
  • Detailed PyPI description (17924 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 41 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • None: self._client = httpx.Client(base_url=base_url, timeout=timeout) def request(
✓ 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 score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ICRANet MMDC Team" 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 astro-mmdc 
Create a Python-based mini-application called 'BlazarExplorer' that leverages the 'astro-mmdc' package to model and analyze the broadband emission of blazars. The application should allow users to input specific parameters such as redshift, luminosity, and other relevant physical properties of a blazar. Based on these inputs, the app should generate a spectral energy distribution (SED) curve, which models the blazar's broadband emission across various wavelengths.

Key Features:
- User-friendly GUI or CLI interface for inputting blazar parameters.
- Real-time plotting of the SED curve based on user inputs.
- Ability to save and export the generated SED curves as image files or data files.
- Optional feature: comparison mode allowing users to input multiple sets of parameters and compare their respective SED curves side-by-side.

Steps to Implement:
1. Set up a Python environment with 'astro-mmdc' installed.
2. Design the user interface (GUI or CLI) for parameter input.
3. Integrate the 'astro-mmdc' package to handle the SED modeling based on user inputs.
4. Implement real-time plotting functionality using a library like matplotlib or seaborn.
5. Add functionality to save and export the plotted SED curves.
6. Optionally, implement a comparison mode for analyzing multiple sets of parameters.
7. Test the application thoroughly with different sets of input parameters to ensure accuracy and reliability of the SED modeling.
8. Document the code and provide usage instructions.

💬 Discussion Feed

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