AI Analysis
The package exhibits unusually high metadata risk signals without corresponding technical indicators of malicious behavior, suggesting potential supply-chain concerns.
- High metadata risk score
- Suspicious git repository and maintainer 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 likely does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of being potentially malicious due to suspicious git repository and maintainer history flags.
Package Quality Overall: Low (4.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Documentation URL: "Docs" -> https://async-sunspec.readthedocs.io/en/latest/?badge=latestDetailed PyPI description (1317 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
27 type-annotated function signatures detected in source
Single-author or unverifiable project
1 unique contributor(s) across 1 commits in fundacaocerti/asyncio-sunspecSingle author with few commits — possibly a personal or throwaway project
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: certi.org.br>
All external links appear legitimate
Git history flags: Very few commits: 1 total
Very few commits: 1 totalSingle contributor with only 1 commit(s) — possibly throwaway account
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 Python-based utility that leverages the 'async-sunspec' package to monitor and control solar inverters connected via Modbus. This tool will serve as a robust solution for solar panel system operators who need real-time data and control capabilities over their equipment. Step 1: Setup the Project Environment - Initialize a new Python project. - Install necessary packages including 'async-sunspec', 'pandas', and 'matplotlib'. Step 2: Implement Data Retrieval - Use 'async-sunspec' to asynchronously connect to the Modbus server of a solar inverter. - Retrieve real-time data from the inverter such as power output, voltage, current, and temperature. Step 3: Develop Data Analysis - Integrate 'pandas' for data processing and analysis. - Calculate key metrics like efficiency and energy yield based on retrieved data. Step 4: Visualize Data - Utilize 'matplotlib' to create dynamic graphs displaying the analyzed data. - Ensure the visualizations update in real-time or at regular intervals. Suggested Features: - User-friendly command-line interface for initiating data retrieval and analysis processes. - Option to log collected data into a CSV file for historical analysis. - Alert system that notifies users via email or SMS if certain thresholds (e.g., low power output) are breached. - Ability to send control commands back to the inverter to adjust settings based on the analysis results. How 'async-sunspec' is Used: - Establish asynchronous connections to the inverter using 'async-sunspec' to ensure non-blocking operations and efficient data fetching. - Leverage the package's capabilities to handle multiple inverter models and configurations seamlessly. - Implement error handling and reconnection logic to maintain stable communication with the inverter. This project aims to provide a comprehensive tool for managing solar inverter systems efficiently and effectively.
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