anbor-types

v0.0.48 safe
3.0
Low Risk

Anbor typing lib

🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risks across various categories with no indications of malicious activities. However, the metadata suggests the maintainer might be new or less active, warranting cautious monitoring.

  • 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 communication.
  • Shell: No shell execution detected, indicating no immediate risk of command injection or system manipulation.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package on PyPI, indicating potential new or inactive status which raises some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 4 type-annotated function signatures (partial)
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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: gmail.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Joniibek" 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 anbor-types 
Create a Python-based mini-application called 'TypeChecker' that leverages the 'anbor-types' library to provide advanced type checking and validation capabilities for user input. This application should serve as a tool for developers to test and validate data types in their Python code snippets. Here’s a detailed breakdown of the application requirements:

1. **Setup**: Begin by installing the 'anbor-types' package using pip. Ensure your development environment is set up correctly for Python development.
2. **Core Functionality**: Implement a function `validate_type` which takes two arguments - a variable and a specified type from the 'anbor-types' library. This function will return True if the variable matches the specified type, otherwise False. Utilize 'anbor-types' for its enhanced type checking capabilities beyond basic Python types.
3. **User Interface**: Develop a simple command-line interface (CLI) where users can input a piece of Python code containing a variable and a type they wish to validate. The CLI should then use the `validate_type` function to check the type and output whether it matches or not.
4. **Advanced Features**:
   - Support for multiple types in a single validation request.
   - Option to perform strict vs non-strict type checks (e.g., considering subclasses).
5. **Documentation**: Write comprehensive documentation explaining how to install and use 'TypeChecker', including examples of common use cases and how 'anbor-types' enhances type checking over standard Python methods.
6. **Testing**: Include a suite of unit tests that cover all functionalities of the 'TypeChecker', ensuring robustness and reliability of the application.
7. **Deployment**: Package 'TypeChecker' into a distributable format (such as a wheel file) and include instructions on how to deploy and run the application on different environments.

This project aims to demonstrate the power of 'anbor-types' in providing sophisticated type validation and checking mechanisms, making it easier for developers to ensure type correctness in their Python applications.

💬 Discussion Feed

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