| |
| |
|
|
| from pathlib import Path |
| from concurrent.futures import ProcessPoolExecutor |
|
|
| import qlib |
| from qlib.data import D |
|
|
| import fire |
| import datacompy |
| import pandas as pd |
| from tqdm import tqdm |
| from loguru import logger |
|
|
|
|
| class CheckBin: |
| NOT_IN_FEATURES = "not in features" |
| COMPARE_FALSE = "compare False" |
| COMPARE_TRUE = "compare True" |
| COMPARE_ERROR = "compare error" |
|
|
| def __init__( |
| self, |
| qlib_dir: str, |
| csv_path: str, |
| check_fields: str = None, |
| freq: str = "day", |
| symbol_field_name: str = "symbol", |
| date_field_name: str = "date", |
| file_suffix: str = ".csv", |
| max_workers: int = 16, |
| ): |
| """ |
| |
| Parameters |
| ---------- |
| qlib_dir : str |
| qlib dir |
| csv_path : str |
| origin csv path |
| check_fields : str, optional |
| check fields, by default None, check qlib_dir/features/<first_dir>/*.<freq>.bin |
| freq : str, optional |
| freq, value from ["day", "1m"] |
| symbol_field_name: str, optional |
| symbol field name, by default "symbol" |
| date_field_name: str, optional |
| date field name, by default "date" |
| file_suffix: str, optional |
| csv file suffix, by default ".csv" |
| max_workers: int, optional |
| max workers, by default 16 |
| """ |
| self.qlib_dir = Path(qlib_dir).expanduser() |
| bin_path_list = list(self.qlib_dir.joinpath("features").iterdir()) |
| self.qlib_symbols = sorted(map(lambda x: x.name.lower(), bin_path_list)) |
| qlib.init( |
| provider_uri=str(self.qlib_dir.resolve()), |
| mount_path=str(self.qlib_dir.resolve()), |
| auto_mount=False, |
| redis_port=-1, |
| ) |
| csv_path = Path(csv_path).expanduser() |
| self.csv_files = sorted(csv_path.glob(f"*{file_suffix}") if csv_path.is_dir() else [csv_path]) |
|
|
| if check_fields is None: |
| check_fields = list(map(lambda x: x.name.split(".")[0], bin_path_list[0].glob(f"*.bin"))) |
| else: |
| check_fields = check_fields.split(",") if isinstance(check_fields, str) else check_fields |
| self.check_fields = list(map(lambda x: x.strip(), check_fields)) |
| self.qlib_fields = list(map(lambda x: f"${x}", self.check_fields)) |
| self.max_workers = max_workers |
| self.symbol_field_name = symbol_field_name |
| self.date_field_name = date_field_name |
| self.freq = freq |
| self.file_suffix = file_suffix |
|
|
| def _compare(self, file_path: Path): |
| symbol = file_path.name.strip(self.file_suffix) |
| if symbol.lower() not in self.qlib_symbols: |
| return self.NOT_IN_FEATURES |
| |
| qlib_df = D.features([symbol], self.qlib_fields, freq=self.freq) |
| qlib_df.rename(columns={_c: _c.strip("$") for _c in qlib_df.columns}, inplace=True) |
| |
| origin_df = pd.read_csv(file_path) |
| origin_df[self.date_field_name] = pd.to_datetime(origin_df[self.date_field_name]) |
| if self.symbol_field_name not in origin_df.columns: |
| origin_df[self.symbol_field_name] = symbol |
| origin_df.set_index([self.symbol_field_name, self.date_field_name], inplace=True) |
| origin_df.index.names = qlib_df.index.names |
| origin_df = origin_df.reindex(qlib_df.index) |
| try: |
| compare = datacompy.Compare( |
| origin_df, |
| qlib_df, |
| on_index=True, |
| abs_tol=1e-08, |
| rel_tol=1e-05, |
| df1_name="Original", |
| df2_name="New", |
| ) |
| _r = compare.matches(ignore_extra_columns=True) |
| return self.COMPARE_TRUE if _r else self.COMPARE_FALSE |
| except Exception as e: |
| logger.warning(f"{symbol} compare error: {e}") |
| return self.COMPARE_ERROR |
|
|
| def check(self): |
| """Check whether the bin file after ``dump_bin.py`` is executed is consistent with the original csv file data""" |
| logger.info("start check......") |
|
|
| error_list = [] |
| not_in_features = [] |
| compare_false = [] |
| with tqdm(total=len(self.csv_files)) as p_bar: |
| with ProcessPoolExecutor(max_workers=self.max_workers) as executor: |
| for file_path, _check_res in zip(self.csv_files, executor.map(self._compare, self.csv_files)): |
| symbol = file_path.name.strip(self.file_suffix) |
| if _check_res == self.NOT_IN_FEATURES: |
| not_in_features.append(symbol) |
| elif _check_res == self.COMPARE_ERROR: |
| error_list.append(symbol) |
| elif _check_res == self.COMPARE_FALSE: |
| compare_false.append(symbol) |
| p_bar.update() |
|
|
| logger.info("end of check......") |
| if error_list: |
| logger.warning(f"compare error: {error_list}") |
| if not_in_features: |
| logger.warning(f"not in features: {not_in_features}") |
| if compare_false: |
| logger.warning(f"compare False: {compare_false}") |
| logger.info( |
| f"total {len(self.csv_files)}, {len(error_list)} errors, {len(not_in_features)} not in features, {len(compare_false)} compare false" |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| fire.Fire(CheckBin) |
|
|
