avenir-spectrum-common

v0.1.6 safe
3.0
Low Risk

Shared constants, model variables (modvars), and utilities for Spectrum Engine

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, with no network calls, shell executions, or obfuscations detected. However, its low maintenance status and metadata quality are slightly concerning.

  • Low maintenance and metadata quality
  • No detected network calls or shell executions
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet connectivity.
  • 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 package shows low maintenance and metadata quality indicators, but lacks clear red flags.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (254 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with avenir-spectrum-common 
Create a Python-based mini-application named 'SpectrumAnalyzer' that leverages the 'avenir-spectrum-common' package to analyze and visualize data using predefined models and utilities. The application should perform the following tasks:

1. **Data Ingestion**: Allow users to upload CSV files containing numerical data.
2. **Data Preprocessing**: Use the shared constants and utilities from 'avenir-spectrum-common' to preprocess the data, ensuring it's ready for analysis.
3. **Model Application**: Apply one of the pre-defined models (modvars) available in the package to predict future trends based on historical data.
4. **Visualization**: Generate visual representations (charts/graphs) of both the raw data and the predictions using matplotlib or seaborn.
5. **Report Generation**: Automatically generate a report summarizing the findings, including key statistics and visualizations.

The application should include a user-friendly interface where users can select the model they want to use for prediction, choose visualization types, and specify any parameters needed for data preprocessing. Additionally, ensure that the application handles exceptions gracefully and provides meaningful error messages to guide users through common issues.

💬 Discussion Feed

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