AI Analysis
The package ansys-fluent-visualization v0.26.1 presents minimal risks across all categories evaluated. It does not engage in network calls, shell executions, or any form of code obfuscation that could suggest malicious intent.
- No network calls detected
- Single package from the author, indicating potential newness but no other suspicious activity
Per-check LLM notes
- Network: No network calls detected, which is normal for a visualization package.
- Shell: No shell execution detected, aligning with the expected behavior of a visualization tool.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
- Metadata: The author has only one package, which might indicate a new or less active account, but no other suspicious elements were found.
Package Quality Overall: Medium (6.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Documentation URL: "Documentation" -> https://visualization.fluent.docs.pyansys.com/Detailed PyPI description (6511 chars)
Some contribution signals present
Separate author ("ANSYS, Inc.") and maintainer ("PyAnsys developers") listedDevelopment Status classifier >= Beta
Partial type annotation coverage
85 type-annotated function signatures detected in source
Active multi-contributor project
9 unique contributor(s) across 100 commits in ansys/pyfluent-visualizationActive community — 5 or more distinct contributors
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
Email domain looks legitimate: ansys.com
All external links appear legitimate
Repository ansys/pyfluent-visualization appears legitimate
1 maintainer concern(s) found
Author "ANSYS, Inc." appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully-functional mini-application that leverages the 'ansys-fluent-visualization' Python package to visualize fluid dynamics simulations. Your application should allow users to load Fluent simulation data files (.cas, .dat), perform basic post-processing operations, and generate interactive visualizations of the flow fields. Step 1: Set up your development environment with Python and install the required packages including 'ansys-fluent-visualization'. Step 2: Design a simple user interface using a library such as Tkinter or PyQt5 where users can browse and select their Fluent data files. Step 3: Implement functionality to read the selected Fluent data file using the 'ansys-fluent-visualization' package. Ensure that the data is correctly parsed and loaded into memory for further processing. Step 4: Develop post-processing capabilities within the application. Allow users to choose from a variety of operations such as contour plots, streamlines, vector plots, and iso-surfaces. Use the 'ansys-fluent-visualization' package to perform these operations on the loaded data. Step 5: Integrate an interactive visualization component that allows users to manipulate the view of the flow field. Users should be able to rotate, zoom, and pan the view. This feature should also support real-time updates based on user interactions. Suggested Features: - Include a feature to save the generated visualizations as image files (PNG, JPEG). - Add the ability to animate the flow over time if the simulation data supports it. - Provide options to customize the appearance of the visualizations, such as color maps and line styles. - Incorporate tooltips or pop-up information when hovering over specific elements in the visualization. The final application should demonstrate proficiency in utilizing the 'ansys-fluent-visualization' package for advanced visualization tasks and provide a user-friendly interface for exploring complex fluid dynamics data.
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