AI Analysis
Final verdict: SAFE
The package argus-cache v0.1.8 exhibits very low risk based on the analysis notes. It shows no signs of network calls, shell execution, obfuscation, or credential harvesting.
- No network calls detected
- Single package by maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating the package does not execute external commands.
- 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 potentially new or less active account.
Package Quality Overall: Low (4.8/10)
✦ High
Test Suite
9.0
Test suite present — 5 test file(s) found
5 test file(s) detected (e.g. test_compression_loss.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (19626 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
26 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Muhammed Emin Çelik" 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 argus-cache
Create a Python-based command-line utility that leverages the 'argus-cache' package to manage a dynamic, quantized key-value cache system. This utility will be particularly useful for developers who need to efficiently store and retrieve data while managing memory usage effectively. Here’s a detailed breakdown of what the utility should achieve: 1. **Initialization**: The utility should allow users to initialize a cache instance using the 'argus-cache' package. Users should be able to specify parameters such as cache size, quantization level, and storage strategy. 2. **Data Insertion**: Implement a feature where users can insert key-value pairs into the cache. The utility should automatically handle any necessary quantization of the values based on the specified quantization level. 3. **Data Retrieval**: Provide functionality for users to retrieve values from the cache using their respective keys. The utility should also support retrieving multiple keys at once. 4. **Cache Management**: Include commands for managing the cache, such as checking the current state of the cache (e.g., number of entries, total size), purging expired or least recently used entries, and resizing the cache dynamically. 5. **Error Handling**: Ensure robust error handling for cases like inserting duplicate keys, attempting to retrieve non-existent keys, or running out of space in the cache. 6. **Advanced Features** (Optional): Consider adding advanced features such as setting expiration times for cache entries, implementing custom eviction policies, or providing a way to dump the current state of the cache to a file for backup purposes. To utilize the 'argus-cache' package effectively, follow these steps: - Import the necessary classes and functions from 'argus-cache'. - Initialize a cache instance with appropriate parameters. - Use the provided methods for inserting and retrieving data, ensuring to handle the returned objects correctly. - Leverage the dynamic and quantized nature of the cache to optimize performance and memory usage. - For advanced features, explore additional functionalities offered by 'argus-cache' and integrate them into your utility. This project aims to demonstrate the capabilities of 'argus-cache' in a practical, real-world scenario, making it easier for developers to understand and utilize this powerful caching mechanism.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue