🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in network, shell execution, and obfuscation, but it has a new maintainer and missing classifiers, which raises some concerns.

New maintainer
Missing classifiers

Per-check LLM notes

Network: No network calls are expected for a legitimate PyQt6 Data Visualization package.
Shell: No shell executions are expected for a legitimate PyQt6 Data Visualization package.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Low risk due to lack of suspicious elements, but caution advised due to new maintainer and missing classifiers.

🔬 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: riverbankcomputing.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Riverbank Computing Limited" 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 PyQt6-DataVisualization-Qt6

Your task is to develop a Python-based data visualization tool called 'DataVizTool'. This application will allow users to visualize datasets in various forms such as bar charts, pie charts, line graphs, and scatter plots. The primary goal is to provide an intuitive interface where users can easily import their datasets, select types of visualizations, and customize the appearance of the charts.

The application should have the following features:
1. **Data Import**: Users should be able to upload CSV files containing their dataset.
2. **Chart Selection**: After importing the data, users should choose from different chart types including Bar Charts, Pie Charts, Line Graphs, and Scatter Plots.
3. **Customization Options**: Allow users to customize the look of their charts. For example, they should be able to change colors, add titles and labels, and adjust axis properties.
4. **Save Visualization**: Users should have the ability to save their visualized data as an image file.
5. **Real-time Updates**: As users make changes to the data or visualization settings, the chart should update in real-time.

To achieve these functionalities, you'll use the 'PyQt6-DataVisualization-Qt6' package. This package provides essential tools for building interactive user interfaces and integrating powerful data visualization capabilities into your application. Your implementation should leverage its features to create an engaging and responsive UI that allows users to interactively explore their data through dynamic visualizations.

Start by designing the main window layout using PyQt6, ensuring it has areas for data input, chart display, and control panels for customization options. Then, implement the logic for handling data imports, chart rendering based on selected types, and applying customizations. Finally, ensure that all changes are reflected instantly in the displayed chart, providing a seamless user experience.