autogalaxy

v2026.5.29.4 safe
3.0
Low Risk

Open-Source Multi Wavelength Galaxy Structure & Morphology

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of risk with no network calls, shell executions, or credential harvesting attempts. The only notable concern is the sparse metadata about the author, which suggests potential lack of maintainer activity.

  • Sparse author metadata
  • No detected network calls
  • No shell executions
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell executions detected, indicating no direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No secret harvesting patterns detected, indicating secure handling of credentials.
  • Metadata: The author's details are sparse, indicating a potentially new or less active maintainer, but there are no clear red flags.

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5820 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

  • 196 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in PyAutoLabs/PyAutoGalaxy
  • Small but multi-author team (3–4 contributors)

🔬 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: rghsoftware.co.uk>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository PyAutoLabs/PyAutoGalaxy 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 autogalaxy 
Develop a mini-application called 'Galaxy Explorer' which leverages the 'autogalaxy' package to analyze and visualize galaxy structures from multi-wavelength data. The application should allow users to upload their own galaxy images or select pre-loaded ones, and then apply various analysis tools provided by 'autalgalxy' to extract structural information such as mass distribution, light profiles, and morphological characteristics. Key features of the application include:

1. A user-friendly interface where users can upload or choose from a set of preloaded galaxy images.
2. Utilization of 'autogalaxy' to perform gravitational lensing analysis, calculating the mass distribution around galaxies.
3. Visualization tools to display the results of the analysis, including heatmaps and contour plots of mass distributions, as well as overlays of light profiles on top of the original galaxy images.
4. An option to save the analysis results and visualizations in a downloadable format, such as PDF or PNG.
5. Integration of machine learning models from 'autogalaxy' to predict galaxy types based on the extracted features.

The goal of 'Galaxy Explorer' is to make advanced galaxy structure and morphology analysis accessible to both researchers and astronomy enthusiasts, allowing them to gain insights into the complex structures of galaxies using state-of-the-art computational methods.

💬 Discussion Feed

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