autoregistry

v1.3.0 safe
3.0
Low Risk

Automatic registry design-pattern for mapping names to functionality.

🤖 AI Analysis

Final verdict: SAFE

The package shows very low risks across all checks with no network calls, shell executions, or obfuscations detected. The metadata risk is slightly elevated due to the maintainer having only one package on PyPI.

  • No network calls detected
  • Single package by maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The maintainer has only one package on PyPI, which may indicate a new or less active account.

📦 Package Quality Overall: Medium (5.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5071 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 18 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in BrianPugh/autoregistry
  • Small but multi-author team (3–4 contributors)

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository BrianPugh/autoregistry appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Brian Pugh" 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 autoregistry 
Create a mini-application named 'ModuleManager' using Python, which leverages the 'autoregistry' package to manage and dynamically load various modules based on user input. The application should allow users to register different types of modules (e.g., data processing, visualization, analytics) and then select and execute specific functionalities provided by these modules without needing to know their exact implementation details.

### Core Features:
- **Module Registration:** Users should be able to add new modules to the system easily. Each module will have a unique name and associated functionality (functions).
- **Dynamic Loading:** Modules should be loaded and executed dynamically based on user input. For example, if a user selects 'data processing', the application should load and execute the registered data processing functions.
- **User Interface:** Implement a simple command-line interface (CLI) where users can interact with the application. This CLI should support commands like 'register', 'list', 'execute', etc.
- **Extensibility:** Ensure the application is easy to extend. New modules and functionalities should be added without modifying existing code.

### Implementation Steps:
1. **Setup Environment:** Create a Python virtual environment and install the required packages, including 'autoregistry'.
2. **Design Modules:** Design several sample modules (e.g., data processing, visualization, analytics). Each module should include at least one function that performs a specific task.
3. **Register Modules:** Use the 'autoregistry' package to automatically register each module's functions under a unique name. Ensure that the registration process is seamless and does not require manual intervention.
4. **Build CLI:** Develop a command-line interface that allows users to:
   - Register new modules (if needed)
   - List all available modules and their functionalities
   - Execute a selected functionality by specifying the module name and function name
5. **Testing:** Thoroughly test the application to ensure that modules are correctly registered, loaded, and executed as expected.
6. **Documentation:** Write documentation explaining how to use the application, how to add new modules, and any other relevant information.

### Example Workflow:
- User starts the application and sees a menu of options.
- User chooses to list all available modules and their functionalities.
- User decides to execute a data processing function.
- Application loads the specified module and executes the requested function.
- Results are displayed to the user.

This project aims to showcase the power and flexibility of the 'autoregistry' package in managing complex systems with dynamic component loading.

💬 Discussion Feed

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