AI Analysis
The package is assessed as safe due to low risks across all categories except metadata, where it has a moderate risk score. However, there's no evidence suggesting any malicious intent.
- Low risk in network, shell, and obfuscation categories
- Moderate risk in metadata due to lower star and fork counts
Per-check LLM notes
- Network: No network calls detected, which is normal for most utility packages unless they require API interactions.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The low star count and fork count suggest the project may be less established or maintained.
Package Quality Overall: Medium (5.2/10)
Partial test coverage signals detected
Test runner config found: pyproject.tomlTest runner config found: setup.cfg
Some documentation present
Detailed PyPI description (1921 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
202 type-annotated function signatures detected in source
Active multi-contributor project
3 unique contributor(s) across 19 commits in mxr/asyncio-for-ynabSmall but multi-author team (3β4 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: users.noreply.github.com
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
1 maintainer concern(s) found
Author "Max R" 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 personal finance tracker mini-app using the 'asyncio-for-ynab' package. This app will allow users to sync their YNAB budget data and provide them with real-time financial insights. Hereβs a detailed plan on how to implement it: 1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the 'asyncio-for-ynab' package. Use pip to install the package. 2. **Authentication**: Integrate OAuth 2.0 authentication flow to securely connect to the YNAB API. Guide the user through the process of obtaining access tokens. 3. **Data Fetching**: Utilize 'asyncio-for-ynab' to fetch budget data asynchronously. Implement functions to retrieve budgets, accounts, transactions, and categories. 4. **Real-Time Insights**: Develop features that calculate key metrics such as total income, expenses, savings rate, and net worth. Display these insights in a user-friendly format. 5. **Customization**: Allow users to customize which budgets/accounts they want to track and set up alerts for specific spending thresholds. 6. **User Interface**: Design a simple command-line interface (CLI) or a basic web interface using Flask or Django. Ensure the UI is intuitive and easy to navigate. 7. **Testing**: Write tests to ensure all functionalities work as expected. Focus on testing asynchronous operations and edge cases. 8. **Documentation**: Provide comprehensive documentation for both users and developers. Include setup instructions, API references, and examples. This project leverages 'asyncio-for-ynab' to efficiently manage asynchronous requests to the YNAB API, ensuring smooth and fast data retrieval and processing.
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