AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity and does not engage in risky behaviors such as executing shell commands or obfuscating code. The main concern is the maintainer's limited presence with only one package, which might suggest a less established developer.
- No network calls detected, which is appropriate for this type of package.
- Maintainer has only one published package, potentially indicating a less experienced or less active developer.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution patterns detected, indicating no direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other suspicious activities were flagged.
Package Quality Overall: Low (3.0/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (7988 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
51 type-annotated function signatures detected in source
○ Low
Multiple Contributors
2.0
Single-author or unverifiable project
1 unique contributor(s) across 11 commits in SuperFeda/aioheleketSingle author with few commits — possibly a personal or throwaway project
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository SuperFeda/aioheleket appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "SuperFeda" 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 aioheleket
Your task is to create a fully-functional asynchronous mini-app using the Python package 'aioheleket', which is designed to interact with the Heleket API asynchronously. This app will serve as a personal finance tracker that allows users to monitor their spending habits and financial health over time. The app should include the following core functionalities: 1. **User Authentication**: Implement a simple user authentication system where users can sign up and log in. Once logged in, they should be able to securely access their financial data. 2. **Data Fetching**: Utilize 'aioheleket' to fetch financial transaction data from various sources (e.g., banks, credit cards). The data should include transaction amounts, dates, categories (such as groceries, entertainment, etc.), and any other relevant information provided by the Heleket API. 3. **Data Analysis**: Provide basic analysis on the fetched data such as total monthly expenses, average daily spending, and categorization of expenses. 4. **Visualization**: Display the analyzed data in a visually appealing way using charts or graphs. For instance, you could use libraries like Matplotlib or Plotly to show trends over time. 5. **Notifications**: Set up a feature where users can receive notifications about unusual spending patterns or when they exceed a set budget threshold. 6. **Budget Management**: Allow users to set budgets for different expense categories and track their adherence to these budgets over time. To achieve these goals, you will need to: - Install and import the 'aioheleket' package along with other necessary Python packages. - Use asynchronous programming techniques to ensure smooth and efficient data fetching and processing. - Design a user-friendly interface for interacting with the app. - Ensure all user data is handled securely, especially when it comes to financial information. - Test your application thoroughly to ensure it works as expected under various scenarios. This project not only leverages the capabilities of 'aioheleket' but also provides a practical solution for managing personal finances efficiently.
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