autoinject

v2.0.0 safe
3.0
Low Risk

Automated dependency injection for Python

🤖 AI Analysis

Final verdict: SAFE

The package autoinject v2.0.0 shows minimal risks across all assessed categories. While the maintainer's account activity is somewhat questionable due to having only one package, there are no signs of malicious intent or suspicious behavior.

  • No network calls detected
  • No shell execution detected
  • No obfuscation or credential harvesting patterns detected
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network functionality.
  • Shell: No shell execution detected, which is expected and safe.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, suggesting a potentially new or less active account.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 13 test file(s) found

  • 13 test file(s) detected (e.g. test_cache_manager.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://autoinject.readthedocs.io/en/latest/
  • Detailed PyPI description (878 chars)
○ 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

  • 159 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 55 commits in turnbullerin/autoinject
  • 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: gmail.com

Suspicious Page Links

All external links appear legitimate

Git Repository History

Repository turnbullerin/autoinject appears legitimate

Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Erin Turnbull" 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 autoinject
Create a small, fully-functional mini-application in Python that leverages the 'autoinject' package for automated dependency injection. This application will be a simple task management tool called 'TaskMaster', designed to help users manage their daily tasks efficiently. The app should allow users to add new tasks, mark tasks as completed, view all current tasks, and delete completed tasks. Additionally, it should have a feature to categorize tasks into different lists such as 'Work', 'Personal', etc., allowing users to filter tasks based on these categories.

The application should consist of several components:
1. A Task class that represents individual tasks with attributes like title, description, completion status, and category.
2. A TaskManager class that manages the lifecycle of tasks, including adding, marking as completed, viewing, and deleting tasks.
3. A Categorizer class that helps in organizing tasks into different categories and filtering them based on these categories.
4. A CLI interface that allows users to interact with the TaskManager and perform various operations.

Utilize the 'autoinject' package to automatically handle dependencies between these classes. For example, the TaskManager should automatically receive instances of the Task and Categorizer classes without needing explicit instantiation in the code. This will demonstrate how 'autoinject' simplifies dependency management in Python applications.

Additionally, implement a simple logging mechanism using Python's built-in logging module to log important events such as task creation, updates, and deletions.

Your final deliverable should include a README file detailing how to set up and run the application, along with instructions on how to install and configure the 'autoinject' package.

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