AI Analysis
The package shows no signs of immediate malicious behavior but has a high metadata risk due to its newness and lack of detailed author information.
- High metadata risk due to limited author information.
- No direct evidence of malicious activities.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communication.
- Shell: No shell execution patterns detected, indicating no immediate risk from command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating safe handling of sensitive information.
- Metadata: The package is new with limited information about the author, raising concerns about its legitimacy.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (3469 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
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 fully-functional asynchronous task scheduler application using the 'aion-scheduler' package in Python. This application will allow users to define, schedule, and manage tasks that run asynchronously. Each task can be a function that performs any operation, such as sending emails, processing data, or making API calls. The application should have a user-friendly interface where tasks can be added, edited, deleted, and their status can be monitored. Key Features: 1. Add new tasks with a description, function to execute, and scheduled time. 2. Edit existing tasks to change their details or reschedule them. 3. Delete tasks from the system. 4. View the current status of all tasks, including when they were last executed and their execution status. 5. Use 'aion-scheduler' to handle the scheduling and execution of these tasks in an asynchronous manner. 6. Implement logging for each task execution to track errors and successes. 7. Provide a simple command-line interface (CLI) for interacting with the application. 8. Include documentation on how to use the CLI and set up the application. Steps to Build the Application: 1. Set up your Python environment and install the 'aion-scheduler' package. 2. Design the structure of your application, deciding how you will store tasks and their details. 3. Create functions to add, edit, delete, and view tasks. 4. Integrate 'aion-scheduler' to handle the scheduling and execution of tasks asynchronously. 5. Implement logging functionality to record task execution statuses. 6. Develop a CLI for users to interact with the application. 7. Test the application thoroughly to ensure it works as expected. 8. Write documentation explaining how to use the application and set up the CLI. This project will demonstrate the power of asynchronous programming and how 'aion-scheduler' can simplify the process of managing complex task schedules.
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