AI Analysis
The package has a relatively low risk score due to the absence of network calls, shell executions, obfuscations, and credential risks. However, the metadata risk is elevated due to suspicious git repository activity and lack of maintainer history, raising concerns about potential supply-chain attacks.
- Elevated metadata risk due to suspicious git repository activity
- Lack of maintainer history
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package is expected to perform network operations.
- Shell: No shell execution detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting the package does not pose a threat for stealing secrets or credentials.
- Metadata: The package shows signs of being potentially malicious due to suspicious git repository activity and lack of maintainer history.
Package Quality Overall: Medium (5.0/10)
Test suite present — 2 test file(s) found
Test runner config found: pyproject.toml2 test file(s) detected (e.g. test_container.py)
Some documentation present
Detailed PyPI description (2437 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
Classifier: Typing :: TypedType checker (mypy / pyright / pytype) referenced in project61 type-annotated function signatures detected in source
Single-author or unverifiable project
1 unique contributor(s) across 4 commits in Dongbumlee/appfx-diSingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: outlook.com>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forksSingle contributor with only 4 commit(s) — possibly throwaway accountAll 4 commits happened within 24 hours
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a simple task management application using Python, which leverages the 'appfx-di' package for dependency injection. This application will allow users to create tasks, assign them to different categories, mark tasks as completed, and delete tasks. The goal of this project is to demonstrate how 'appfx-di' simplifies the process of managing dependencies within complex applications, making it easier to manage objects and their relationships without directly handling dependencies yourself. ### Features: - **Task Creation:** Users can add new tasks with a title, description, and category. - **Category Management:** Users can create, modify, and delete categories to organize tasks. - **Task Completion:** Users can mark tasks as completed. - **Task Deletion:** Users can remove tasks from the system. - **Dependency Injection:** Utilize 'appfx-di' to inject dependencies such as data access layers, service providers, and logging into your application components. ### Steps: 1. **Setup Project Structure:** Initialize your Python environment and install necessary packages including 'appfx-di'. 2. **Define Application Components:** Create classes for tasks, categories, and services that interact with these entities. 3. **Configure 'appfx-di':** Use 'appfx-di' to define bindings between interfaces and implementations, ensuring that services and repositories are properly injected into your components. 4. **Implement Core Functionality:** Write functions to handle CRUD operations on tasks and categories, utilizing the dependency-injected services. 5. **Testing:** Ensure all functionalities work as expected by testing each feature thoroughly. 6. **Deployment:** Prepare your application for deployment, considering packaging and possibly setting up a web interface or CLI for user interaction. By following these steps and focusing on the integration of 'appfx-di', you'll not only build a functional task manager but also gain valuable experience in dependency injection and Python application development.
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