AI Analysis
Based on the analysis, the package appears to be legitimate with low risks across various categories. The only notable concern is the potential misuse of subprocess calls, but this does not strongly suggest a supply-chain attack.
- Low network and obfuscation risks
- Shell risk due to subprocess usage, but not indicative of malicious intent
- No detected credential or metadata risks
Per-check LLM notes
- Network: The use of 'requests' to fetch data from a specific URL related to the package is likely legitimate for updating package metadata or fetching external data.
- Shell: Executing arbitrary code via 'subprocess.check_call' can be risky if not properly sanitized or intended for package-specific operations, suggesting potential for misuse or unintended side effects.
- Obfuscation: The code snippet appears to be related to the evaluation of Gaussian models and does not indicate malicious obfuscation.
- Credentials: No credentials or secrets harvesting patterns were detected.
- Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate a lower level of trust.
Package Quality Overall: Medium (6.6/10)
Test suite present — 13 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml13 test file(s) detected (e.g. test_configs.py)
Some documentation present
Documentation URL: "documentation" -> https://docs.astropy.orgDetailed PyPI description (5496 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
21 type-annotated function signatures detected in source
Active multi-contributor project
18 unique contributor(s) across 100 commits in astropy/astropyActive community — 5 or more distinct contributors
Heuristic Checks
Found 1 network call pattern(s)
import requests metadata = requests.get( "https://pypi.org/pypi/astropy-iers-data/json", timeout
Found 2 obfuscation pattern(s)
t least similar to Gaussian1D.eval(). """ model = Gaussian1D(1, 0, 20) x = np.arangt least similar to Gaussian2D.eval() """ model = Gaussian2D(0.01, 0, 0, 1, 1) x =
Found 2 shell execution pattern(s)
del env[val] retcode = subprocess.check_call([sys.executable, "-c", "import astropy"], env=env) asseon}.e.value """) cp = subprocess.check_call([sys.executable, "-c", cmd]) assert cp == 0 # Licensed
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Repository astropy/astropy appears legitimate
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 Python-based mini-application called 'AstroTimeTraveler' which allows users to explore different astronomical events from various points in time. The application will utilize the 'astropy' package to perform calculations and provide accurate data. Here are the steps and features you need to implement: 1. **Setup**: Start by setting up a virtual environment for your project. Install 'astropy' using pip. 2. **User Interface**: Develop a simple command-line interface where users can input dates and receive information about celestial events such as eclipses, planetary positions, and meteor showers occurring on those dates. 3. **Event Calculations**: Use 'astropy' to calculate the positions of planets, moons, and other celestial bodies at specified times. Also, determine if any eclipses or meteor showers were visible from Earth during the chosen date. 4. **Historical Data Integration**: Integrate historical astronomical data from reliable sources into your application. This could include past solar eclipses, lunar eclipses, and major meteor showers. 5. **Future Predictions**: Allow users to input future dates and predict celestial events based on current orbital data and known patterns. 6. **Visualization**: Implement basic visualization capabilities within the console output to display the relative positions of celestial bodies involved in the event. 7. **Documentation and Testing**: Write comprehensive documentation explaining how to use the tool and its underlying principles. Ensure thorough testing of all functionalities to guarantee accuracy and reliability. In this project, 'astropy' will be crucial for performing precise astronomical calculations, handling time conversions across different epochs, and providing access to extensive databases of celestial objects.
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