2233admin / prediction-market-backtesting
Code health
2233admin/prediction-market-backtesting scores 5.7 out of 10 on defect risk, which Repowise rates Fair. Maintainability scores 6.7 out of 10. Static performance risk scores 9.6 out of 10. The three are scored separately and never blended into a single number. 38 of 229 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 229
- Symbols
- 3.8k
- Modules
- 37
- Doc pages
- 0
- Dead exports
- 40
Where the risk concentrates
All 38 hotspotsRanked by prior bug fixes and change frequency, mined from the full git history rather than from the code alone.
| File | Churn | Prior fixes | Maintainers | Commits 90d |
|---|---|---|---|---|
| pmxt.pyprediction_market_extensions/backtesting/data_sources | 99.0th %ile | 3 | 2bus factor 1 | 23 |
| main.py | 98.0th %ile | 3 | 2bus factor 1 | 7 |
| replay_adapters.pyprediction_market_extensions/backtesting/data_sources |
Read more about 2233admin/prediction-market-backtesting
- OverviewFiles, symbols, languages, packages, git intelligence
- ArchitectureDependency graph, layered architecture, symbol index, and third-party dependencies
- Code healthPer-file health scores, hotspots, test coverage, dead code, and refactoring targets
- AI explanationsProModule-by-module documentation generated from source
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Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/2233admin/prediction-market-backtesting)How 2233admin/prediction-market-backtesting works
This page is an auto-generated, always-fresh map of the 2233admin/prediction-market-backtesting repository, written primarily in python. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 229 source files, 3,824 symbols, and 7 languages, organised into 37 modules, led by python, markdown, rust. Static analysis leaves 1,534 open findings across the three health dimensions.
Use the links above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.