AI Analysis
The package is considered safe as it does not exhibit any risky behaviors such as network calls, shell executions, or obfuscations. It appears to be a placeholder with no active functionality.
- No network calls
- No shell execution
- No obfuscation
- No credential risk
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no direct system command execution observed.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
Package Quality Overall: Low (1.2/10)
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
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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: gmail.com>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
4 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)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based logging utility called 'AltusLogger' using the upcoming 'altuslog' package. This utility will serve as a powerful tool for developers to manage and analyze logs efficiently. The application should include the following features: 1. **Real-time Log Monitoring**: Implement real-time monitoring of logs from various sources (e.g., files, network streams). Users should be able to view logs as they are generated. 2. **Log Filtering**: Provide options for filtering logs based on severity levels (info, warning, error, etc.), timestamps, and custom tags. This allows users to focus on specific types of log messages. 3. **Log Analysis**: Integrate basic analytics such as frequency of errors over time, most common error messages, and trends analysis. Visualize these insights using charts and graphs. 4. **Alerting System**: Set up an alerting system that notifies users via email or SMS when certain conditions are met (e.g., if the number of errors exceeds a threshold). 5. **User Interface**: Develop a simple web interface where users can interact with the logging utility, view logs, apply filters, and configure alerts. 6. **Configuration Management**: Allow users to save and load configurations for different projects or environments. The 'altuslog' package will be utilized for handling the core logging functionalities, including real-time log ingestion, filtering, and storage. It will also provide APIs for integrating with external systems for alerting and visualization purposes. Your task is to design and implement this utility, ensuring it is user-friendly, efficient, and scalable.
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