amplpy-cplex

v0.2.4 safe
3.0
Low Risk

CPLEX extension for amplpy

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

🤖 AI Analysis

Final verdict: SAFE

The package amplpy-cplex v0.2.4 presents minimal risks based on the analysis notes provided. It lacks any network calls, shell executions, or signs of obfuscation or credential harvesting.

  • No network calls
  • No shell executions
  • No obfuscation or credential harvesting detected
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell executions detected, indicating no immediate risk of command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has only one package, which may indicate a new or less active maintainer, but no other red flags are present.

📦 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 (793 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-cplex 
Your task is to create a simple yet powerful application that leverages the 'amplpy-cplex' package to solve linear programming problems. This application will serve as a user-friendly interface for defining and solving optimization problems, making it accessible even to those without extensive knowledge of mathematical programming. Here are the steps and features your application should include:

1. **Application Setup**: Begin by setting up a Python environment where you can install 'amplpy-cplex'. Ensure all necessary dependencies are installed.
2. **User Interface**: Design a basic command-line interface (CLI) or a simple graphical user interface (GUI) using Tkinter. The UI should allow users to input their problem details such as decision variables, objective function, and constraints.
3. **Problem Definition**: Implement functionality within the application to accept user-defined linear programming problems. Users should be able to specify the type of optimization (maximization or minimization), the coefficients of the objective function, and the constraints.
4. **Solving with CPLEX**: Utilize the 'amplpy-cplex' package to solve the defined problems. This involves setting up the model in AMPL format, passing it to CPLEX for computation, and retrieving the solution.
5. **Solution Presentation**: After solving, present the results back to the user in a clear and understandable format. Include both the optimal value and the values of the decision variables.
6. **Additional Features**: Consider adding features like saving/loading problem definitions from files, providing examples of common LP problems, and offering explanations of the solution process.
7. **Testing and Validation**: Test your application thoroughly with various test cases to ensure it handles different types of linear programming problems correctly.
8. **Documentation**: Write documentation that explains how to use the application, including any limitations or assumptions made during development.

This project not only showcases the power of 'amplpy-cplex' but also provides a practical tool for anyone interested in learning about and applying linear programming techniques.

💬 Discussion Feed

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