Alchemist2026
C 60 completed
Other
library / python · small
110
Files
22,103
LOC
0
Frameworks
7
Languages
Pipeline State
completedRun ID
#394716Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
40.47Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47572
Member of a group with 1 similar repo(s) — canonical #27562 view group →
Top concepts (2)
Project DescriptionData/ML
Repobility · open methodology · https://repobility.com/research/
AI Prompt
Create a modular quantitative trading system in Python. I need it to support backtesting strategies, simulating trades, and performing intelligent analysis. The system should include components for asset management, portfolio tracking, and order handling. Specifically, I'd like to utilize technical indicators like RSI and MACD, and ideally, incorporate GPU acceleration for indicator calculations. The structure should also support data fetching from providers like AlphaVantage and include a web interface using FastAPI for potential visualization and configuration.
python quant-trading backtesting finance machine-learning fastapi gpu simulation
Generated by gemma4:latest
Catalog Information
一个模块化的量化交易系统，支持模拟交易、策略回测和智能分析。
Description
一个模块化的量化交易系统，支持模拟交易、策略回测和智能分析。
Novelty
3/10Tags
python quant-trading backtesting finance machine-learning fastapi gpu simulation
Claude Models
claude-opus-4-6
Quality Score
C
60.0/100
Structure
51
Code Quality
64
Documentation
74
Testing
50
Practices
55
Security
67
Dependencies
60
Strengths
- Well-documented README with substantial content
- Consistent naming conventions (snake_case)
- Containerized deployment (Docker)
Weaknesses
- No LICENSE file \u2014 legal ambiguity for contributors
- No CI/CD configuration \u2014 manual testing and deployment
- Potential hardcoded secrets in 1 files
- 1534 duplicate lines detected \u2014 consider DRY refactoring
- 6 'god files' with >500 LOC need decomposition
Recommendations
- 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)
- Move hardcoded secrets to environment variables or a secrets manager
Security & Health
5.1h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/
Unknown
License
2.9%
Duplication
Languages
Frameworks
None detected
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Repobility — the code-quality scanner for AI-generated software · https://repobility.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | 一个模块化的量化交易系统，支持模拟交易、策略回测和智能分析。 | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Data/ML | data-ml | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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