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#!/usr/bin/env python3
"""Download CFTC Commitment of Traders (COT) data.
CFTC publishes weekly COT reports (Tuesday snapshot, released Friday) showing
futures positioning broken down by trader type (dealers, asset managers,
leveraged money for financial futures; commercials, managed money for
commodities). The data is free and useful for sentiment/positioning features.
This downloader uses ``ml4t.data.cot.COTFetcher`` — which wraps the
``cot_reports`` library — to fetch per-product panels and writes one parquet
per product to ``$ML4T_DATA_PATH/futures/positioning/cot/{product}.parquet``. The
``load_cot()`` loader in ``data/futures/loader.py`` consumes these files.
Output layout under ``$ML4T_DATA_PATH/futures/positioning/cot/``::
{PRODUCT}.parquet one parquet per product code (e.g., ES.parquet)
Schema (columns vary by report type but include):
product exchange product code (ES, CL, GC, …)
report_type CFTC report that produced the row
report_date Tuesday snapshot date
open_interest total open interest
<trader>_long long positions per trader category
<trader>_short short positions per trader category
<trader>_net computed long short per category
Usage::
# Default: all products in PRODUCT_MAPPINGS, 2020current year
python data/futures/positioning/cot_download.py
# Restrict to a subset
python data/futures/positioning/cot_download.py --products ES,NQ,CL,GC
# Wider year range
python data/futures/positioning/cot_download.py --start-year 2010 --end-year 2024
# Override output root
python data/futures/positioning/cot_download.py --data-path /tmp/ml4t-data
"""
from __future__ import annotations
import argparse
from pathlib import Path
from ml4t.data.cot import PRODUCT_MAPPINGS, COTConfig, COTFetcher
from utils.downloading import resolve_data_dir
def main() -> int:
parser = argparse.ArgumentParser(
description="Download CFTC Commitment of Traders data",
formatter_class=argparse.RawDescriptionHelpFormatter,
)
parser.add_argument(
"--products",
type=str,
default=None,
help=(
"Comma-separated product codes (default: all in PRODUCT_MAPPINGS). "
f"Available: {', '.join(sorted(PRODUCT_MAPPINGS.keys()))}"
),
)
parser.add_argument(
"--start-year",
type=int,
default=2020,
help="First calendar year to fetch (default: 2020)",
)
parser.add_argument(
"--end-year",
type=int,
default=None,
help="Last calendar year to fetch (default: current year)",
)
parser.add_argument(
"--data-path",
type=Path,
default=None,
help="Override output root (default: $ML4T_DATA_PATH)",
)
args = parser.parse_args()
if args.products:
products = [p.strip().upper() for p in args.products.split(",") if p.strip()]
unknown = [p for p in products if p not in PRODUCT_MAPPINGS]
if unknown:
print(f"ERROR: unknown product code(s): {', '.join(unknown)}")
print(f"Available: {', '.join(sorted(PRODUCT_MAPPINGS.keys()))}")
return 1
else:
products = sorted(PRODUCT_MAPPINGS.keys())
data_path = resolve_data_dir(args.data_path)
output_dir = data_path / "futures" / "positioning" / "cot"
output_dir.mkdir(parents=True, exist_ok=True)
config = COTConfig(
products=products,
start_year=args.start_year,
end_year=args.end_year,
storage_path=output_dir,
)
fetcher = COTFetcher(config)
print()
print(f"Output: {output_dir}")
print(f"Years: {config.start_year}{config.end_year}")
print(f"Products: {len(products)} ({', '.join(products)})")
print()
written = 0
empty = 0
failed: list[str] = []
for i, product in enumerate(products, 1):
print(f" [{i}/{len(products)}] {product}…", end="", flush=True)
try:
df = fetcher.fetch_product(product)
except Exception as e:
failed.append(product)
print(f" FAILED ({e})")
continue
if df.is_empty():
empty += 1
print(" no rows returned")
continue
out_path = output_dir / f"{product}.parquet"
df.write_parquet(out_path)
written += 1
print(f" {len(df):,} rows → {out_path.name}")
print()
print(f"Wrote: {written} parquet(s)")
if empty:
print(f"Empty: {empty} product(s) returned no rows")
if failed:
print(f"Failed: {len(failed)}{', '.join(failed)}")
return 1
return 0
if __name__ == "__main__":
raise SystemExit(main())