Metrics Miscellany

C 63 completed
Library
cli / toml · tiny
15
Files
3,466
LOC
1
Frameworks
3
Languages

Pipeline State

completed
Run ID
#354897
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
57.15
Framework unique
Isolation
Last stage change
2026-05-10 03:34:57
Deduplication group #58882
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Top concepts (2)
Project DescriptionTesting
Source: Repobility analyzer · https://repobility.com

AI Prompt

I need a command-line tool written in Python that uses pytest for testing. This tool should provide various miscellaneous functions for estimating values, specifically designed to work with pandas DataFrames. It should be structured as a CLI application, and I'd like it to handle configuration using TOML files. Please ensure the project structure is clean and includes necessary setup files like a Makefile.
python cli pandas pytest toml data-analysis scripting command-line
Generated by gemma4:latest

Catalog Information

This project provides miscellaneous functions for estimating values using pandas dataframes.

Description

The metrics-miscellany project offers a collection of utility functions for working with pandas DataFrames, specifically designed to facilitate estimation tasks. It leverages popular libraries like NumPy and SciPy to provide efficient and accurate calculations. This project is intended for data analysts and scientists who need to perform various estimations on their datasets.

الوصف

يعد مشروع metrics-miscellany مجموعة من الوظائف المفيدة لتعامل مع البيانات الموجودة في البيانات الإحصائية، وخاصةً لتحديد القيم المتعلقة بالبيانات. يستفيد هذا المشروع من مكتبات NumPy و SciPy للعمل بشكل فعال وموثوق.

Novelty

3/10

Tags

data-estimation pandas-dataframe numerical-computation data-analysis scientific-computing

Technologies

matplotlib numpy pandas scipy

Claude Models

claude-opus-4.6

Quality Score

C
62.8/100
Structure
49
Code Quality
100
Documentation
40
Testing
0
Practices
80
Security
100
Dependencies
50

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Low average code complexity \u2014 well-structured code
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment

Security & Health

4.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (3)
Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data.
Unknown
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

toml
82.4%
shell
16.2%
text
1.5%

Frameworks

pytest

Concepts (2)

Powered by Repobility · code-quality intelligence
CategoryNameDescriptionConfidence
Repobility · MCP-ready · https://repobility.com
auto_descriptionProject DescriptionMiscellaneous code for estimation involving pandas dataframes.80%
auto_categoryTestingtesting70%

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1 quality score recorded.

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