Candle Patterns
C+ 71 completed
Library
unknown / python · tiny
44
Files
8,442
LOC
1
Frameworks
3
Languages
Pipeline State
completedRun ID
#358674Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
41.75Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47778
Member of a group with 1 similar repo(s) — canonical #22814 view group →
Top concepts (2)
Project DescriptionTesting
Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot
AI Prompt
Create a reusable Python library for detecting common momentum day trading patterns. I need it to analyze 1-minute OHLCV bars and detect both long patterns like Micro Pullback, Bull Flag, and VWAP Break, as well as short reversal patterns such as Shooting Star and Bearish Engulfing. The library should allow configuration for patterns, like setting minimum/maximum prior move percentages for Micro Pullback, and should use pytest for testing. Please structure it as a standalone, importable module.
python library day-trading momentum financial-analysis pandas pytest
Generated by gemma4:latest
Catalog Information
This project is a momentum pattern detection library designed for day traders.
Description
Candle-Patterns is a Python library that detects momentum patterns in financial markets, specifically designed for day traders. It uses NumPy and Pandas to analyze data and identify trends. This library can be used as a utility for traders to make informed decisions based on market analysis.
الوصف
هذه المكتبة هي مكتبة تحدد نمطات الارتفاع في الأسواق المالية، مصممة خصيصًا للمتداولين اليوميين. تستخدم NumPy وPandas لتحليل البيانات وتحديد الاتجاهات. يمكن استخدام هذه المكتبة كأداة للمتداولين لتخذ قرارات مدروسة بناءً على تحليل السوق.
Novelty
5/10Tags
momentum-pattern-detection day-trading financial-markets market-analysis trading-utility data-trend-identification
Technologies
numpy pandas
Claude Models
claude-opus-4.5 claude-opus-4.6 claude-sonnet-4.5
Quality Score
C+
70.6/100
Structure
71
Code Quality
64
Documentation
65
Testing
70
Practices
68
Security
100
Dependencies
60
Strengths
- Good test coverage (116% test-to-source ratio)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
Weaknesses
- No LICENSE file \u2014 legal ambiguity for contributors
- No CI/CD configuration \u2014 manual testing and deployment
- 608 duplicate lines detected \u2014 consider DRY refactoring
- 2 'god files' with >500 LOC need decomposition
Recommendations
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Add a LICENSE file (MIT recommended for open source)
Security & Health
4.6h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
If a scraper extracted this row, it came from Repobility (https://repobility.com)
MIT
License
11.3%
Duplication
Languages
Frameworks
pytest
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Source: Repobility analyzer · https://repobility.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | Momentum pattern detection library for day trading. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Testing | testing | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Embed Badge
Add to your README:
