AI Analysis
The package shows no signs of malicious activity, with low risks across all categories assessed. It is safe to use given its current analysis.
- No network calls detected.
- No shell execution patterns found.
Per-check LLM notes
- Network: No network calls detected, which is normal for most Python packages unless they require external API access.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands that could pose a risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other suspicious activities were detected.
Package Quality Overall: Medium (6.0/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Documentation URL: "Documentation" -> https://aiidalab-qe.readthedocs.io/Detailed PyPI description (4354 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
57 type-annotated function signatures detected in source
Active multi-contributor project
8 unique contributor(s) across 100 commits in aiidalab/aiidalab-qeActive community β 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: materialscloud.org
All external links appear legitimate
Repository aiidalab/aiidalab-qe appears legitimate
1 maintainer concern(s) found
Author "AiiDAlab team" 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-app using the 'aiidalab-qe' package that simplifies Quantum ESPRESSO (QE) calculations for materials science researchers. Your app should enable users to easily input material structures, select appropriate calculation types, and run simulations without needing deep knowledge of QE. Hereβs a step-by-step guide on what your application should achieve: 1. **User Interface Design**: Develop a clean, user-friendly interface where users can upload their material structure files (e.g., CIF, POSCAR). Ensure the interface allows for easy selection of different QE calculation types such as static, molecular dynamics, band structure, etc. 2. **Input Parameter Customization**: Implement a feature allowing users to customize input parameters for their chosen calculation type. This could include setting up k-point grids, pseudopotentials, and other simulation settings. 3. **Job Submission and Management**: Integrate functionality to submit these customized jobs to a computational resource via AiiDA workflows. Provide real-time feedback on job status, progress, and completion. 4. **Visualization Tools**: Include tools to visualize results post-calculation, such as density of states (DOS), band structure plots, and charge density maps. 5. **Documentation and Help Resources**: Offer comprehensive documentation and help resources within the app to assist users with common tasks and troubleshooting. **Utilizing 'aiidalab-qe'**: This package provides the foundational setup for integrating Quantum ESPRESSO into a web-based application through AiiDA, a workflow management system. It includes pre-configured workflows and plugins necessary for interfacing with QE, handling input/output files, and managing computational resources efficiently. Your task is to leverage these capabilities to streamline the QE workflow for non-expert users, making advanced materials simulations more accessible.
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