amplpy-xpress

v0.2.4 safe
3.0
Low Risk

XPRESS extension for amplpy

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential harvesting activities. The metadata suggests a possibly new or less active maintainer, but this alone does not warrant suspicion.

  • No network calls detected
  • Single package maintained by the author
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
  • 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 might indicate a new or less active account, but no other red flags were found.

📦 Package Quality Overall: Low (3.4/10)

○ 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 (795 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in ampl/ampls-api
  • Two distinct contributors found

🔬 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: ampl.com

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://ampl.com/
✓ Git Repository History

Repository ampl/ampls-api appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Filipe Brandão" 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 amplpy-xpress 
Create a Python-based mini-application that utilizes the 'amplpy-xpress' package to solve linear programming problems. This application should serve as a user-friendly interface where users can input their linear programming problems directly, and the app will leverage the power of AMPL and XPRESS solvers to find optimal solutions efficiently. Here’s a detailed plan on how to build this application:

1. **Setup**: Begin by setting up your development environment. Ensure you have Python installed along with the 'amplpy-xpress' package. You may also need to install AMPL and XPRESS solvers if they are not already available.
2. **User Interface Design**: Develop a simple yet effective command-line interface (CLI) for users to interact with the application. Alternatively, you could create a basic web interface using Flask or Django, allowing users to input their LP problems through a form.
3. **Problem Input Handling**: Implement functionality to accept user-defined linear programming problems. Users should be able to specify constraints, objectives, and variables in a structured format that 'amplpy-xpress' can understand.
4. **Solving Problems with amplpy-xpress**: Utilize 'amplpy-xpress' to formulate and solve these problems. Ensure the application handles various types of LP problems, including maximization and minimization scenarios.
5. **Result Presentation**: After solving the problem, present the results back to the user in a clear, understandable manner. Include all relevant information such as the optimal solution values, objective function value, and any other pertinent details about the solution process.
6. **Additional Features**: Consider adding extra features like saving problem definitions and solutions to files, providing visualizations of the solution space, or integrating a history feature to allow users to revisit previous problems they've solved.
7. **Testing & Documentation**: Thoroughly test the application with different types of linear programming problems to ensure it works correctly across a variety of scenarios. Also, document the code and prepare usage instructions for end-users to facilitate easy adoption.

This project aims to demonstrate the capabilities of 'amplpy-xpress' in solving real-world optimization problems, making complex mathematical modeling accessible to a broader audience.

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