algoux-standard-ranklist-utils

v0.3.0 suspicious
5.0
Medium Risk

Utilities for Standard Ranklist (srk).

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network, shell, and obfuscation, but its recent creation and limited activity with a single maintainer elevate the metadata risk to a level that warrants further scrutiny.

  • Low network, shell, and obfuscation risks
  • Metadata risk due to new package with low activity and single maintainer
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 immediate risk of command injection or similar attacks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package is newly created with low activity and a single maintainer, raising some suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Medium (6.0/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. test_contract.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2073 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 32 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 34 commits in algoux/standard-ranklist-utils
  • Single author but highly active (34 commits)

🔬 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 score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "bLue" 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 algoux-standard-ranklist-utils 
Create a Python-based mini-application named 'Ranklist Explorer' that leverages the 'algoux-standard-ranklist-utils' package to provide users with an interactive way to explore and manipulate ranklists from various competitions or events. This application will serve as a tool for organizers, participants, and enthusiasts to manage rankings, calculate scores, and perform analytics on standard ranklists (SRK).

**Step-by-Step Project Outline:**
1. **Setup Environment**: Begin by setting up a Python virtual environment and installing the 'algoux-standard-ranklist-utils' package along with other necessary libraries such as Pandas for data manipulation and Flask for web framework.
2. **Data Input**: Design a user-friendly interface where users can upload CSV files containing ranklist data or input data directly through a form. Ensure the application supports multiple formats and provides validation checks to ensure data integrity.
3. **Ranklist Processing**: Utilize 'algoux-standard-ranklist-utils' to process the uploaded ranklist data. Implement functionalities like sorting, filtering, and ranking based on different criteria provided by the package.
4. **Interactive Analysis**: Develop tools within the application to allow users to analyze the ranklist data interactively. Features could include calculating average scores, identifying top performers, visualizing performance trends over time, etc.
5. **Customization Options**: Allow users to customize their analysis by applying filters, adjusting parameters, and selecting specific columns for analysis. Use the 'algoux-standard-ranklist-utils' package to handle complex operations efficiently.
6. **Output & Sharing**: Provide options for users to export analyzed data back into CSV format or share insights via downloadable reports. Additionally, implement basic visualization capabilities using Matplotlib or similar libraries to help users visualize their findings.
7. **Documentation & User Guide**: Write comprehensive documentation detailing how to use each feature of the application, including examples and best practices. Include a user guide that explains the importance of standard ranklists and how the application can be used effectively.

**Suggested Features**:
- Support for multiple ranking criteria (points, time, penalties)
- Advanced filtering options (by category, date range, team/individual)
- Integration with popular competition platforms for automatic data import
- Real-time collaboration and sharing of ranklists among users
- Customizable score calculation rules based on competition-specific requirements

By completing this project, you'll not only gain hands-on experience with the 'algoux-standard-ranklist-utils' package but also develop valuable skills in building robust, user-centric applications using Python.

💬 Discussion Feed

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