athena-charts

v1.0.0 suspicious
4.0
Medium Risk

声明式图表规范、主题、运行时协议和通用输出

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network activity, shell execution, and obfuscation. However, its metadata suggests it may be newly created with little effort, raising concerns about potential malicious intent.

  • Metadata risk score is elevated due to newness and low-effort creation.
  • No immediate signs of malicious activities such as network calls or shell executions.
Per-check LLM notes
  • Network: No network calls suggest the package is not designed to communicate externally.
  • Shell: No shell execution patterns indicate that the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of being newly created and potentially low-effort, which raises some suspicion but does not conclusively indicate malice.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (449 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 32 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

  • Only one version has ever been released — brand new package
  • Author "wangmu" 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 athena-charts 
Create a fully-functional mini-application called 'ChartMaster' using the Python package 'athena-charts'. ChartMaster is designed to help data analysts and scientists visualize complex datasets quickly and efficiently. The application should allow users to upload CSV files containing their dataset, select different chart types (such as line charts, bar charts, pie charts, etc.), apply various themes to enhance visual appeal, and export the generated charts in multiple formats like PNG, SVG, or PDF.

Step-by-step guide:
1. Start by setting up a basic user interface using a web framework like Flask or Django, where users can upload their CSV files.
2. Integrate the 'athena-charts' package into your application to handle the declaration of chart specifications, themes, and runtime protocols.
3. Implement functionality that reads the uploaded CSV file and processes it to extract relevant information needed for chart generation.
4. Provide a dropdown menu for users to choose from a variety of chart types supported by 'athena-charts', such as line charts, bar charts, pie charts, scatter plots, etc.
5. Allow users to customize the appearance of their charts by selecting different themes provided by 'athena-charts'. Themes could vary from minimalist to colorful, catering to different preferences.
6. Once the chart is generated, display it on the user interface and provide options to download the chart in various formats (PNG, SVG, PDF).
7. Ensure that the application is responsive and user-friendly, providing clear instructions and feedback at each step of the process.
8. Finally, add error handling to manage cases where the CSV file might be incorrectly formatted or if there are issues during chart generation.

Suggested Features:
- Support for real-time chart updates based on user inputs or changes in the dataset.
- Integration with popular data visualization libraries for additional chart types.
- Ability to save user preferences and settings for future use.
- Incorporation of tooltips and interactive elements in the charts for better data exploration.

How 'athena-charts' is Utilized:
- Use 'athena-charts' to define the structure and layout of different chart types declaratively.
- Apply predefined themes from 'athena-charts' to enhance the visual presentation of the charts.
- Leverage the runtime protocol provided by 'athena-charts' to dynamically generate and render charts based on user selections and dataset characteristics.

💬 Discussion Feed

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