Acc

C+ 72 completed
Library
unknown / markdown · small
168
Files
21,381
LOC
1
Frameworks
8
Languages

Pipeline State

completed
Run ID
#304719
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
65.67
Framework unique
Isolation
Last stage change
2026-05-10 03:35:17
Deduplication group #51298
Member of a group with 17 similar repo(s) — canonical #84061 view group →
Top concepts (10)
Project Descriptiondata_accessTestingtestingFactoryTestingSearchLoggingFile ManagementConfiguration
Repobility · MCP-ready · https://repobility.com

AI Prompt

Create a Python application for hierarchical cluster visualization called ACC. It needs to take two similarity matrices—one for local and one for global—loaded from CSV files. The core functionality should combine these two dendrograms to visualize the cluster relationships using concentric circles. The application must have a PyQt5 GUI that guides the user through a three-step workflow: loading the local matrix, loading the global matrix, and finally generating the visualization. It should use Matplotlib for interactive charting and include features for saving the output as PNG or SVG. Please ensure the underlying logic handles the conversion of similarity into diameter and angle for the circular representation.
python pyqt5 matplotlib clustering visualization data-science csv gui scientific
Generated by gemma4:latest

Catalog Information

The ACC project provides a tool for hierarchical cluster visualization using concentric circles.

Description

ACC is a Python-based library that enables the creation of hierarchical cluster visualizations using concentric circles. It leverages popular data science libraries such as matplotlib, numpy, pandas, scikit-learn, and scipy to provide an intuitive and informative representation of complex data structures. This tool is particularly useful for exploratory data analysis and understanding relationships within large datasets.

الوصف

ACC هو مكتبة برمجية مكتوبة بلغة بايثون، تساعد على إنشاء تمثيلات مركزية ل집وصات هرمية باستخدام دوائر محيطة. تستفيد من مكتبات البيانات العلمية الشهيرة مثل matplotlib, numpy, pandas, scikit-learn و scipy لتقديم تمثيل ملموس ومعلوماتي للنظم البيانية المعقدة. هذا الأداة مفيدة بشكل خاص في التحليل المسبق للبيانات وتحديد العلاقات بين البيانات الكبيرة.

Novelty

7/10

Tags

hierarchical-cluster-visualization concentric-circles data-exploration cluster-analysis data-science-toolkit

Technologies

matplotlib numpy pandas scikit-learn scipy

Claude Models

claude (unknown version) claude-opus-4.6 claude-sonnet-4.5 claude-opus-4.5

Quality Score

C+
72.2/100
Structure
87
Code Quality
63
Documentation
85
Testing
85
Practices
47
Security
66
Dependencies
90

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (136% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Properly licensed project

Weaknesses

  • 5 bare except/catch blocks swallowing errors
  • Potential hardcoded secrets in 1 files
  • 1103 duplicate lines detected \u2014 consider DRY refactoring
  • 2 'god files' with >500 LOC need decomposition

Recommendations

  • Replace bare except/catch blocks with specific exception types
  • Move hardcoded secrets to environment variables or a secrets manager

Security & Health

5.3h
Tech Debt (A)
Medium
DORA Rating
A
OWASP (100%)
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PASS
Quality Gate
A
Risk (1)
MIT
License
7.6%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

markdown
49.1%
python
41.4%
restructuredtext
4.8%
yaml
3.4%
toml
0.9%
shell
0.3%
text
0.1%
ini
0.1%

Frameworks

pytest

Symbols

method183
function83
variable44
class27
constant8

Concepts (10)

Findings curated by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Want this analysis on your repo? https://repobility.com/scan/
auto_descriptionProject Description![Tests](https://github.com/jikhanjung/ACC/actions) ![Build](https://github.com/jikhanjung/ACC/actions) ![codecov](https://codecov.io/gh/jikhanjung/ACC)80%
arch_layerdata_accessDetected data_access layer70%
auto_categoryTestingtesting70%
arch_layertestingDetected testing layer70%
design_patternFactoryFound factory/create_ naming patterns60%
business_logicTestingDetected from 33 related files50%
business_logicSearchDetected from 5 related files50%
business_logicLoggingDetected from 52 related files50%
business_logicFile ManagementDetected from 3 related files50%
business_logicConfigurationDetected from 3 related files50%

Quality Timeline

1 quality score recorded.

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BinComp Dependency Hardening

All packages →
5 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nsemver3.0.4 · 0 gadgets · risk 5565.0Cmatplotlib3.10.8 · 2,481 gadgets · risk 0.0Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Fpandas3.0.2 · 6,381 gadgets · risk 0.0Fscipy1.17.1 · 21,805 gadgets · risk 0.0