AI Analysis
The package shows very low risks across all categories except metadata, where incomplete maintainer information raises a slight concern. However, there is no evidence of malicious activity.
- Low risk scores in network, shell, and obfuscation categories.
- Incomplete maintainer information in metadata.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution patterns detected, indicating no immediate risk of command injection or unauthorized system access.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer's author information is incomplete, suggesting a potentially less experienced or inactive developer.
Package Quality Overall: Low (3.0/10)
Partial test coverage signals detected
1 test file(s) detected (e.g. test_basic.py)
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Limited contributor diversity
1 unique contributor(s) across 41 commits in ImFeH2/arisSingle author but highly active (41 commits)
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: feh2.im>
All external links appear legitimate
Repository ImFeH2/aris 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 educational tool called 'MathMaster' using the 'aris-lib' package, which is a comprehensive mathematical computing library. This tool aims to help students and enthusiasts practice and understand various mathematical concepts through interactive problem-solving sessions. Hereβs a detailed plan on how to develop MathMaster: 1. **Project Setup**: Initialize your project with a virtual environment and install the 'aris-lib' package. 2. **Core Features**: - **Problem Generator**: Develop a module that generates math problems based on user-defined parameters such as difficulty level, topic (e.g., algebra, calculus), and specific concepts (e.g., quadratic equations, integrals). - **Solution Provider**: Implement a feature that provides step-by-step solutions to the generated problems, utilizing 'aris-lib' for complex calculations and symbolic manipulations. - **Practice Mode**: Allow users to solve problems in a timed session, with options to review their answers and see detailed explanations. - **Learning Resources**: Integrate external resources like video tutorials or articles related to the solved problems, enhancing the learning experience. 3. **User Interface**: Design a simple yet intuitive GUI using libraries like Tkinter or PyQt, making it accessible for both beginners and advanced users. 4. **Testing and Validation**: Ensure the accuracy of the problem solutions and the robustness of the application through thorough testing, leveraging 'aris-lib' for automated verification. 5. **Deployment**: Package the application for distribution, possibly as a standalone executable, ensuring itβs easily accessible to users without requiring them to install 'aris-lib'. By following these steps, you will create a valuable educational tool that leverages the powerful computational capabilities of 'aris-lib' to enhance mathematical understanding and skills.
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