AI Analysis
The package appears to be safe for use with minimal risks identified. It does not engage in network calls, shell executions, or any form of obfuscation that could indicate malicious activity.
- No network calls detected.
- No shell execution patterns detected.
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 direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some red flags, particularly the lack of maintainer information and a single associated package, which may indicate a new or inactive account.
Package Quality Overall: Low (4.8/10)
Test suite present — 8 test file(s) found
Test runner config found: pyproject.toml8 test file(s) detected (e.g. generate_test_vectors.py)
Some documentation present
Detailed PyPI description (10181 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project26 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a small, interactive astronomy project using the 'astrowidget' package in Python. Your project should allow users to visualize and interact with real-time radio astronomy data within a Jupyter Notebook environment. The application should have the following core functionalities: 1. Load and display real-time or pre-recorded radio astronomy data. 2. Implement a user interface where users can select different frequencies to filter the data being visualized. 3. Provide options for adjusting the scale and color map of the displayed data for better analysis. 4. Include a feature to save the current visualization as an image file. 5. Enable users to annotate the visualization with notes or markers. 6. Optionally, add a feature to overlay known celestial objects or paths on the visualization for context. Use the 'astrowidget' package to create the interactive visualization widgets. Ensure your application is well-documented with comments explaining how each part of the code works and any assumptions made during development. Additionally, provide a short tutorial or guide on how to run and use the application.
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