asps-entropy-sort-v5-pro

v1.0.1 safe
1.0
Low Risk

(No description)

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity with low scores across all checks. It does not engage in risky behaviors such as network calls, shell executions, or credential harvesting.

  • No network calls detected
  • No shell execution detected
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ 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 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 asps-entropy-sort-v5-pro 
Develop a Python-based data visualization tool named 'EntropyExplorer' that leverages the 'asps-entropy-sort-v5-pro' package to sort and analyze datasets based on entropy measures. This tool will be particularly useful for data scientists and analysts who need to quickly understand the distribution and randomness of their data. Here’s a detailed plan for building 'EntropyExplorer':

1. **Project Setup**: Start by setting up a virtual environment and installing necessary packages including 'asps-entropy-sort-v5-pro'. Ensure that you document all dependencies in a requirements.txt file.
2. **Data Import**: Create a user-friendly interface where users can upload their dataset (CSV files primarily). The tool should validate the uploaded data and handle common errors gracefully.
3. **Entropy Calculation**: Utilize the 'asps-entropy-sort-v5-pro' package to calculate the entropy of each column in the dataset. Display these calculations in a readable format alongside the original data.
4. **Sorting Mechanism**: Implement a sorting feature that allows users to sort the data based on entropy values. This could be done in ascending or descending order, depending on the user's preference.
5. **Visualization**: Develop visual representations of the sorted data using libraries such as Matplotlib or Seaborn. Visualizations should include histograms, scatter plots, and line graphs to help users better understand the distribution and trends within their data.
6. **Export Functionality**: Provide an option for users to export their analyzed and sorted data back into CSV format for further analysis or record-keeping.
7. **Documentation & Testing**: Write comprehensive documentation for the tool, explaining how to use it and the significance of entropy in data analysis. Conduct thorough testing to ensure the accuracy of entropy calculations and the stability of the sorting mechanism.

**Suggested Features**:
- Integration with popular cloud storage services like Google Drive or Dropbox for direct data import.
- Advanced filtering options to refine the data before performing entropy calculations.
- Support for multiple data formats beyond CSV, such as Excel or SQL databases.
- Interactive dashboards that allow users to manipulate and visualize data in real-time.
- A built-in tutorial or demo mode to guide new users through the basic functionalities of EntropyExplorer.

💬 Discussion Feed

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