Greppablebenchmarking

D 50 completed
Cli Tool
unknown / yaml · medium
586
Files
1,536,701
LOC
0
Frameworks
6
Languages

Pipeline State

completed
Run ID
#336753
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
70.00
Framework unique
Isolation
Last stage change
2026-05-10 03:35:17
Deduplication group #47956
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Top concepts (1)
Data/ML
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AI Prompt

Create a command-line benchmarking tool written in Python that measures the performance of various regular expression patterns. The tool should read experiment configurations from YAML files, execute the regex tests, and output the results. It should also be able to generate documentation or reports using Markdown, and perhaps store experiment metadata in JSON format.
python cli regex benchmarking yaml markdown json performance
Generated by gemma4:latest

Catalog Information

A command-line tool that benchmarks the performance of regular expression patterns in Python.

Description

GreppableBenchmarking is a lightweight command-line utility designed to measure and compare the execution speed of regular expression patterns. It accepts a set of regex patterns and a sample text, then runs each pattern multiple times to gather timing statistics. The tool outputs clear metrics such as average time per match, total matches found, and CPU usage, enabling developers to identify bottlenecks. It is especially useful for teams that rely heavily on text processing and need to optimize search queries for large datasets. By providing a reproducible benchmark framework, it helps maintain performance standards across codebases.

الوصف

أداة GreppableBenchmarking هي أداة سطر أوامر خفيفة الوزن تهدف إلى قياس ومقارنة سرعة تنفيذ أنماط التعبير العادي في لغة بايثون. تستقبل الأداة مجموعة من الأنماط النصية وعينة نصية، ثم تقوم بتشغيل كل نمط عدة مرات لتجميع إحصائيات زمنية دقيقة. تُظهر النتائج مقاييس واضحة مثل متوسط الوقت لكل مطابقة، إجمالي عدد المطابقات، واستهلاك وحدة المعالجة المركزية، ما يتيح للمطورين تحديد نقاط الاختناق. تُعد الأداة مفيدة بشكل خاص للفرق التي تعتمد على معالجة النصوص وتحتاج إلى تحسين استعلامات البحث في مجموعات بيانات كبيرة. بفضل إطار العمل القابل للتكرار للمعايير، تساعد الأداة على الحفاظ على معايير الأداء عبر قواعد الكود المختلفة، وتوفر وسيلة موثوقة لتقييم وتحسين كفاءة التعبيرات العادية.

Novelty

6/10

Tags

regex-benchmarking performance-testing text-search-optimization pattern-profiling speed-analysis search-engine-comparison

Technologies

anthropic

Claude Models

claude-opus-4.6

Quality Score

D
50.5/100
Structure
36
Code Quality
75
Documentation
45
Testing
20
Practices
49
Security
75
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 7620 duplicate lines detected \u2014 consider DRY refactoring
  • 6 'god files' with >500 LOC need decomposition

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
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

4.6h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (0)
Open data scored by Repobility · https://repobility.com
Unknown
License
77.1%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

yaml
96.3%
python
2.8%
markdown
0.7%
json
0.2%
text
0.0%
shell
0.0%

Frameworks

None detected

Concepts (1)

Same analyzer free for public repos: https://repobility.com
CategoryNameDescriptionConfidence
Repobility · code-quality intelligence · https://repobility.com
auto_categoryData/MLdata-ml70%

Quality Timeline

1 quality score recorded.

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