AI Analysis
The package exhibits very low risks across all assessed categories, with no detected network calls, shell executions, or credential harvesting activities. The metadata risk is slightly elevated due to the maintainer's single package history.
- Low risk scores across all primary risk categories.
- Elevated metadata risk due to maintainer's limited package history.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands directly.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, indicating a new or less active account which may warrant further investigation.
Package Quality Overall: Low (4.6/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
Classifier: Typing :: Typed8 type-annotated function signatures (partial)
Active multi-contributor project
5 unique contributor(s) across 100 commits in envoyproxy/toolshedActive community β 5 or more distinct contributors
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: synca.io
All external links appear legitimate
Repository envoyproxy/toolshed appears legitimate
1 maintainer concern(s) found
Author "Ryan Northey" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to create a fully-functional asynchronous task scheduler application using the Python package 'aio.run.runner'. This application will allow users to define and schedule tasks to run at specific times or intervals, providing a robust way to manage asynchronous operations efficiently. Hereβs a step-by-step guide on how to approach this project: 1. **Project Setup**: Start by setting up your Python environment and installing the 'aio.run.runner' package along with any other necessary dependencies such as 'asyncio', 'datetime', and 'click' for command-line interaction. 2. **Define Task Models**: Create models for tasks that include attributes like task name, description, start time, interval (if applicable), and the function to execute. Ensure these models support serialization and deserialization for storage purposes. 3. **Task Scheduling Logic**: Implement the logic to schedule tasks using 'aio.run.runner'. This should involve defining runners that can handle the execution of tasks at specified times or intervals asynchronously. Use 'asyncio' for managing the event loop and scheduling. 4. **Command-Line Interface (CLI)**: Develop a CLI tool using 'click' that allows users to add, remove, and modify tasks. Users should be able to specify when a task should run, how often it should repeat, and what function should be executed. 5. **Database Integration**: Integrate a simple database (like SQLite) to store task definitions persistently. Ensure that tasks are saved when added or modified via the CLI and loaded automatically when the application starts. 6. **Logging and Monitoring**: Add logging capabilities to track the status of tasks, including when they start, complete, and any errors encountered during execution. Optionally, implement monitoring features to display the current state of all scheduled tasks. 7. **Testing and Validation**: Write tests to ensure that your application functions correctly under various conditions. Validate that tasks are scheduled accurately, executed as expected, and stored/retrieved properly from the database. 8. **Documentation and Packaging**: Finally, document your applicationβs usage and functionality thoroughly. Package your application into a distributable format using tools like setuptools. Throughout the development process, focus on leveraging the 'aio.run.runner' package to its fullest potential, especially in handling asynchronous task execution and management. Your goal is to create a reliable, user-friendly, and efficient task scheduler that demonstrates the power of asynchronous programming.