AI Analysis
The package shows a moderate risk due to the potential misuse of subprocess.run for executing shell commands, despite no clear evidence of malicious activity or obfuscation.
- Shell risk due to subprocess.run usage
- No network calls or credentials handling detected
Per-check LLM notes
- Network: No network calls detected, which is not necessarily suspicious.
- Shell: The use of subprocess.run to execute shell commands could indicate legitimate functionality but requires further investigation to ensure it's not being used for malicious purposes.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
Package Quality Overall: Low (4.4/10)
Test suite present — 8 test file(s) found
8 test file(s) detected (e.g. _fakes.py)
Some documentation present
Detailed PyPI description (6012 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
45 type-annotated function signatures detected in source
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
Found 1 shell execution pattern(s)
aryFile() as tmpfile: subprocess.run( ["uv", "export", "--frozen", "--no-header", "--
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: grayvines.com>
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor 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
Your task is to create a Python-based utility named 'DependChecker' that leverages the 'amigpl' package to analyze Python projects and identify any copyleft dependencies within them. This tool will be particularly useful for developers who want to ensure their projects comply with open-source licenses. ### Core Functionality: - **Project Analysis:** Users should be able to input the path of a Python project directory. The tool will then scan the project's requirements.txt file (or similar dependency files) and use the 'amigpl' package to check each listed dependency for copyleft licensing. - **Dependency Reporting:** The utility should generate a report listing all dependencies found in the project along with their license types. Specifically, it should highlight any dependencies that have copyleft licenses. - **User Interface:** Implement a simple command-line interface (CLI) where users can specify the project directory path as an argument when running the utility. ### Additional Features: - **Automated Scanning:** Extend the utility to automatically detect and include any additional dependency files (e.g., setup.py, Pipfile) if present in the project directory. - **License Compliance Check:** For each identified copyleft dependency, provide a brief explanation of what copyleft means and suggest actions developers might take to comply with these licenses. - **Interactive Mode:** Offer an interactive mode where users can enter dependency names directly into the CLI to check individual packages. ### How to Use 'amigpl': - Integrate 'amigpl' into your utility to perform the checks on each dependency. This package will likely provide functions or methods that you can call to determine the licensing type of a given package. - Ensure you handle any exceptions or errors gracefully, providing meaningful feedback to the user if something goes wrong during the analysis process.
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