AI Analysis
The package archaeo has minimal risks associated with it as there are no network or shell execution activities detected. However, due to its recent release and limited activity, caution should still be exercised.
- Low network and shell risk
- New package with limited activity
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating the package does not execute commands on the host system.
- Metadata: The package is new with limited activity, but no immediate signs of malicious intent.
Package Quality Overall: Low (1.4/10)
No test suite detected
No test files or test-runner configuration detected
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
Single-author or unverifiable project
1 unique contributor(s) across 6 commits in anderscui/archaeoSingle author with few commits — possibly a personal or throwaway project
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
No author email provided
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "Anders Cui" 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 develop a simple yet powerful utility application using the 'archaeo' Python package. This application will serve as a tool for managing and analyzing data from archaeological sites. It will include features such as data import/export, basic statistical analysis, and visualization of findings. 1. **Project Setup**: Begin by setting up your Python environment and installing the 'archaeo' package. Ensure you have all necessary dependencies installed. 2. **Data Management**: Utilize 'archeo' to create functions for importing data from various sources (e.g., CSV files, SQLite databases). Also, implement functionality to export data into different formats, ensuring flexibility in handling and sharing data. 3. **Statistical Analysis**: With 'archeo', develop modules that perform basic statistical analyses on the imported data. These could include mean, median, mode calculations, frequency distributions, and other relevant metrics pertinent to archaeological data. 4. **Visualization**: Use 'archeo' to integrate visualization capabilities. Create visual representations of your statistical findings, such as histograms, scatter plots, and line graphs, to help interpret the data more effectively. 5. **User Interface**: Optionally, consider building a simple command-line interface or a graphical user interface (GUI) using 'archeo'. This will make the application more accessible and user-friendly. 6. **Documentation**: Finally, ensure thorough documentation of your application, explaining how each feature works and how users can interact with it. Include examples and tutorials to assist new users in getting started quickly. Throughout the development process, leverage the core functionalities provided by 'archeo' to streamline your workflow and enhance the reliability and efficiency of your application.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue