AI Analysis
The package does not pose significant risks, with low scores across all categories except for obfuscation due to the use of pickle for testing equality.
- No network calls detected
- Shell execution is benign
- Potential obfuscation via pickle usage
Per-check LLM notes
- Network: No network calls detected, which is normal for a formatting tool.
- Shell: Shell execution appears to be for running a code formatter, which is benign.
- Obfuscation: The code appears to be using pickle for testing equality, which could be seen as obfuscation but is likely a legitimate test mechanism.
- Credentials: No clear patterns of credential harvesting or secret storage were identified.
- Metadata: The maintainer has only one package, which could indicate a new or less active developer, but no other red flags were found.
Package Quality Overall: Medium (6.2/10)
Test suite present — 7 test file(s) found
7 test file(s) detected (e.g. lro-occultation.py)
Some documentation present
Detailed PyPI description (14235 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
13 type-annotated function signatures detected in source
Active multi-contributor project
9 unique contributor(s) across 100 commits in nyx-space/aniseActive community — 5 or more distinct contributors
Heuristic Checks
No suspicious network call patterns found
Found 4 obfuscation pattern(s)
clipse_val = eclipse_boundary.eval(orbit, almanac) is_in_eclipse = eclipse_val >= 01e-3 # Pickling test pickle.loads(pickle.dumps(eme2k)) == eme2k pickle.loads(pickle.dumps(le.dumps(eme2k)) == eme2k pickle.loads(pickle.dumps(eme2k.shape)) == eme2k.shape # Cannot picklss module boundaries =( # pickle.loads(pickle.dumps(paris)) == paris # Test that we can get th
Found 1 shell execution pattern(s)
_ruff(file: str) -> None: subprocess.check_call(["python", "-m", "ruff", "format", file]) if __name__ == "
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Repository nyx-space/anise appears legitimate
1 maintainer concern(s) found
Author "Christopher Rabotin <[email protected]>" 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 space mission planning tool using the Python package 'anise'. This tool should allow users to input spacecraft parameters, such as initial position, velocity, and orientation, along with mission objectives like target celestial bodies and desired observation times. The application should utilize ANISE's capabilities to generate attitude, navigation, instrument, and ephemeris data to simulate the spacecraft's journey and ensure it meets its mission goals. Step-by-step functionality: 1. User interface for entering spacecraft initial conditions and mission targets. 2. Use ANISE to calculate trajectories and predict spacecraft positions over time. 3. Display a visual representation of the spacecraft's path around the solar system. 4. Provide real-time feedback on whether the spacecraft is on track to meet its mission objectives. 5. Allow users to adjust parameters and see how these changes affect the mission outcome. Suggested Features: - Interactive 3D visualization of the solar system and spacecraft trajectory. - Detailed reports summarizing key mission events and outcomes. - Support for multiple mission scenarios and comparison between them. - Export mission plans and data in standard formats for further analysis or sharing. The 'anise' package will be crucial in providing the necessary tools and data for calculating spacecraft trajectories, predicting positions, and ensuring accurate simulations of the mission.
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