Add Binance-backed Paul Wei trading analysis - #1
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Pull request overview
Adds a standalone Python CLI that fetches Binance BTCUSDT USD‑M perpetual 1m candle archives into a local SQLite cache and performs a reproducible analysis of the (submodule-provided) Paul Wei trading ledger to generate derived CSVs, figures, and a Chinese research report.
Changes:
- Introduces
tradetrace.pywithfetchandanalyzecommands, SQLite caching, candle matching, and report/table generation. - Adds offline unit tests for core timestamp bucketing, candle matching, inverse fill math, and SQLite ingest behavior.
- Adds a primary-source index and checks in generated report artifacts under
reports/.
Reviewed changes
Copilot reviewed 14 out of 36 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
tradetrace.py |
New CLI + analysis pipeline for fetching Binance candles, reconstructing positions, and generating outputs. |
test_tradetrace.py |
Unit tests for several key helper functions and ingest logic. |
research/paulwei-sources.md |
Primary-source index for research claims and usage rules. |
reports/tables/order_summary.csv |
Generated order summary output. |
reports/tables/market_summary.csv |
Generated per-market trading summary output. |
reports/tables/market_data_quality.csv |
Generated market data coverage/gap summary. |
reports/tables/hourly_activity.csv |
Generated hourly activity aggregation. |
reports/tables/execution_summary.csv |
Generated execution/matching summary output. |
reports/tables/data_audit.csv |
Generated input file audit output. |
reports/tables/cycle_summary.csv |
Generated cycle-window summary output. |
reports/tables/case_summary.csv |
Generated case-study window summary output. |
reports/paulwei-analysis.md |
Generated Chinese analysis report (Markdown). |
README.md |
Project usage overview and CLI invocation instructions. |
pyproject.toml |
Project metadata and dependencies (matplotlib). |
.gitignore |
Ignores local market cache directory. |
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| def manifest() -> dict: | ||
| return json.loads(MANIFEST.read_text(encoding="utf-8")) |
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| def dedupe_orders(rows: list[dict]) -> tuple[list[dict], int]: | ||
| seen, result = set(), [] | ||
| for row in rows: | ||
| key = tuple(row.items()) | ||
| if key not in seen: | ||
| seen.add(key) | ||
| result.append(row) | ||
| return result, len(rows) - len(result) |
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| snapshot_position = int(decimal(next(read_csv("api-v1-position.snapshot.csv"))["currentQty"])) | ||
| if position_metrics["terminal_position"] != snapshot_position or snapshot_position != -998_000: | ||
| raise ValueError(f"terminal position mismatch: {position_metrics['terminal_position']}") |
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| def write_csv(path: Path, rows: list[dict], fieldnames: list[str] | None = None) -> None: | ||
| path.parent.mkdir(parents=True, exist_ok=True) | ||
| fields = fieldnames or (list(rows[0]) if rows else []) | ||
| with path.open("w", newline="", encoding="utf-8") as handle: | ||
| writer = csv.DictWriter(handle, fieldnames=fields, lineterminator="\n") | ||
| writer.writeheader() | ||
| writer.writerows(rows) |
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| 对 `BTC-Trading-Since-2020` 公开账本进行可复现研究，并用 Binance USD-M | ||
| `BTCUSDT` 永续 1 分钟 K 线为 XBTUSD 成交提供市场背景。 | ||
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What changed
tradetrace.pyCLI withfetchandanalyzecommands.BTCUSDT1-minute archives, importing them into an ignored SQLite cache.lastPx, align executions to Binance minute ranges, and generate CSV tables, figures, and a Chinese research report.Validation
uv run python -m unittest test_tradetrace.py(6 tests passed).fetch/analyzeruns are idempotent; generated report hashes are unchanged.Binance candles are used only as the XBTUSD market proxy; all fill, position, PnL, and fee calculations retain ledger values.