atomate2

v0.1.4 safe
3.0
Low Risk

atomate2 is a library of materials science workflows

🤖 AI Analysis

Final verdict: SAFE

The package atomate2 v0.1.4 is assessed as safe with a low risk score due to minimal risks identified across various categories. There are no indications of network, shell execution, or obfuscation misuse.

  • No network calls detected.
  • Shell executions appear legitimate for tool interactions.
  • No signs of code obfuscation or credential harvesting.
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Shell executions appear to be for command-line tool interactions and logging purposes, suggesting normal operation rather than malicious intent.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package has a non-secure external link and an author with limited information, suggesting potential unreliability.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "documentation" -> https://materialsproject.github.io/atomate2/
  • Detailed PyPI description (9546 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 146 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 20 unique contributor(s) across 100 commits in materialsproject/atomate2
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • as stderr: process = subprocess.Popen(command, stdout=stdout, stderr=stderr) if wall_time
  • aims_cmd}") return_code = subprocess.call(["/bin/bash", "-c", aims_cmd], env=os.environ) logger.in
  • .log", "w") as f_err: subprocess.call(["amset", "run"], stdout=f_std, stderr=f_err) # noqa: S607
  • ne if git: name = subprocess.run( [git, "config", "user.name"], captu
  • rue, ) mail = subprocess.run( [git, "config", "user.email"], capt
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.cohp.de
✓ Git Repository History

Repository materialsproject/atomate2 appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with atomate2 
Create a materials science workflow management tool using the 'atomate2' Python package. This tool will allow users to define, execute, and monitor complex materials science workflows involving multiple computational steps such as structure generation, electronic structure calculations, and post-processing analysis. The application should be user-friendly and capable of integrating seamlessly with existing computational environments like VASP or Quantum ESPRESSO.

Steps to develop the tool:
1. Define the user interface for inputting workflow specifications including initial structures, calculation parameters, and desired outputs.
2. Implement functionality within the application to utilize 'atomate2' to create and manage workflows, which can include tasks such as generating initial structures, running electronic structure calculations, and analyzing results.
3. Develop a feature that allows the user to track the status of each task within a workflow, providing real-time updates on progress and any encountered errors.
4. Integrate visualization tools to display results from the workflow, such as band structures, density of states, and structural optimizations.
5. Ensure the application supports the saving and loading of workflow configurations, allowing users to resume or modify workflows at any point.
6. Provide documentation and examples to guide new users in setting up and executing their first workflows using 'atomate2'.

Suggested Features:
- Support for multiple computational engines (e.g., VASP, Quantum ESPRESSO)
- Advanced error handling and recovery mechanisms
- Integration with cloud computing resources for scaling purposes
- Interactive visualizations of key results
- Comprehensive logging and reporting capabilities

The 'atomate2' package will be utilized extensively throughout the development process, particularly in defining the workflows, executing computational tasks, and managing data generated during the workflow execution.

💬 Discussion Feed

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