ashwelness-utils

v0.7.1 safe
3.0
Low Risk

Python library containing common utilities used across various ASH projects.

🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risk across multiple categories including network, shell, obfuscation, and credential risks. While there is some concern about metadata quality and maintainer history, these do not indicate any malicious intent.

  • Low network and shell execution risk
  • No obfuscation or credential harvesting detected
  • Metadata and maintainer history show low effort but no malicious signs
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low effort in metadata and maintainer history, but lacks clear malicious indicators.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (11749 chars)
◈ Medium Contributing Guide 7.0

Some contribution signals present

  • Governance file: security.py
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 87 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ashwelness-utils 
Create a personal wellness tracker application named 'WellnessPulse' using Python, which leverages the 'ashwelness-utils' package to manage common tasks efficiently. This application will allow users to log their daily activities related to wellness such as diet, exercise, sleep quality, and mood. The goal is to provide insights into how these factors interrelate and impact overall health over time.

Steps to complete this project:
1. Set up the basic structure of the application including initialization files and directories.
2. Use 'ashwelness-utils' to handle data validation and sanitization for user inputs.
3. Implement a feature where users can add entries about their daily activities. These entries should include timestamps, activity type (e.g., diet, exercise), duration, and qualitative feedback (e.g., how did it make you feel).
4. Utilize 'ashwelness-utils' to store these entries in a structured format (such as SQLite or JSON files).
5. Develop a reporting module that generates weekly summaries based on the logged activities. This report should highlight trends, suggest improvements, and provide personalized advice.
6. Integrate 'ashwelness-utils' to perform statistical analysis on the collected data to identify correlations between different activities and overall well-being.
7. Ensure the application has a simple and intuitive command-line interface for ease of use.
8. Test the application thoroughly to ensure all functionalities work as expected and fix any bugs.
9. Document the codebase and write usage instructions for new users.

Suggested Features:
- Option to categorize activities further (e.g., specific types of exercises).
- Graphical representation of trends over time.
- Integration with external fitness trackers for automatic data import.
- Notifications提醒用户定期记录活动。

如何利用'ashwelness-utils'包：
- 数据验证和清理：使用该库提供的工具确保输入数据的准确性和一致性。
- 数据存储：利用其内置的功能将用户活动记录保存到数据库中。
- 统计分析：应用其统计功能来分析用户的活动数据，提供有价值的洞察。

💬 Discussion Feed

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