US stock code supports Windows

qlib/__init__.py

@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 
-__version__ = "0.6.1.dev"
+__version__ = "0.6.1.99.dev"
 
 
 import os
@@ -15,7 +15,7 @@ import platform
 import subprocess
 from pathlib import Path
 
-from .utils import can_use_cache, init_instance_by_config, get_module_by_module_path
+from .utils import can_use_cache, init_instance_by_config, check_qlib_data
 from .workflow.utils import experiment_exit_handler
 
 # init qlib
@@ -88,6 +88,7 @@ def init(default_conf="client", **kwargs):
     R.register(qr)
     # clean up experiment when python program ends
     experiment_exit_handler()
+    check_qlib_data(C)
 
 
 def _mount_nfs_uri(C):

qlib/data/data.py

@@ -15,14 +15,13 @@ import importlib
 import traceback
 import numpy as np
 import pandas as pd
-from pathlib import Path
 from multiprocessing import Pool
 
 from .cache import H
 from ..config import C
 from .ops import *
 from ..log import get_module_logger
-from ..utils import parse_field, read_bin, hash_args, normalize_cache_fields
+from ..utils import parse_field, read_bin, hash_args, normalize_cache_fields, code_to_fname
 from .base import Feature
 from .cache import DiskDatasetCache, DiskExpressionCache
 from ..utils import Wrapper, init_instance_by_config, register_wrapper, get_module_by_module_path
@@ -215,23 +214,6 @@ class InstrumentProvider(abc.ABC):
             return cls.LIST
         raise ValueError(f"Unknown instrument type {inst}")
 
-    def convert_instruments(self, instrument):
-        _instruments_map = getattr(self, "_instruments_map", None)
-        if _instruments_map is None:
-            _df_list = []
-            # FIXME: each process will read these files
-            for _path in Path(C.get_data_path()).joinpath("instruments").glob("*.txt"):
-                _df = pd.read_csv(_path, sep="\t", names=["inst", "start_datetime", "end_datetime", "save_inst"])
-                _df_list.append(_df.iloc[:, [0, -1]])
-            df = pd.concat(_df_list, sort=False)
-            df["inst"] = df["inst"].astype(str)
-            df = df.fillna(axis=1, method="ffill")
-            df = df.sort_values("inst").drop_duplicates(subset=["inst"], keep="first")
-            df["save_inst"] = df["save_inst"].astype(str)
-            _instruments_map = df.set_index("inst").iloc[:, 0].to_dict()
-            setattr(self, "_instruments_map", _instruments_map)
-        return _instruments_map.get(instrument, instrument)
-
 
 class FeatureProvider(abc.ABC):
     """Feature provider class
@@ -590,12 +572,16 @@ class LocalInstrumentProvider(InstrumentProvider):
         fname = self._uri_inst.format(market)
         if not os.path.exists(fname):
             raise ValueError("instruments not exists for market " + market)
+
         _instruments = dict()
-        df = pd.read_csv(fname, sep="\t", names=["inst", "start_datetime", "end_datetime", "save_inst"])
+        df = pd.read_csv(
-        df["start_datetime"] = pd.to_datetime(df["start_datetime"])
+            fname,
-        df["end_datetime"] = pd.to_datetime(df["end_datetime"])
+            sep="\t",
-        df["inst"] = df["inst"].astype(str)
+            usecols=[0, 1, 2],
-        df["save_inst"] = df.loc[:, ["inst", "save_inst"]].fillna(axis=1, method="ffill")["save_inst"].astype(str)
+            names=["inst", "start_datetime", "end_datetime"],
+            dtype={"inst": str},
+            parse_dates=["start_datetime", "end_datetime"],
+        )
         for row in df.itertuples(index=False):
             _instruments.setdefault(row[0], []).append((row[1], row[2]))
         return _instruments
@@ -652,7 +638,7 @@ class LocalFeatureProvider(FeatureProvider):
     def feature(self, instrument, field, start_index, end_index, freq):
         # validate
         field = str(field).lower()[1:]
-        instrument = Inst.convert_instruments(instrument)
+        instrument = code_to_fname(instrument)
         uri_data = self._uri_data.format(instrument.lower(), field, freq)
         if not os.path.exists(uri_data):
             get_module_logger("data").warning("WARN: data not found for %s.%s" % (instrument, field))

qlib/tests/__init__.py

@@ -15,6 +15,10 @@ class TestAutoData(unittest.TestCase):
             print(f"Qlib data is not found in {provider_uri}")
 
             GetData().qlib_data(
-                name="qlib_data_simple", region="cn", version="latest", interval="1d", target_dir=provider_uri
+                name="qlib_data_simple",
+                region="cn",
+                interval="1d",
+                target_dir=provider_uri,
+                delete_old=False,
             )
         init(provider_uri=provider_uri, region=REG_CN)

qlib/tests/data.py

@@ -1,14 +1,21 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
+
+import re
+import qlib
+import shutil
 import zipfile
 import requests
+import datetime
 from tqdm import tqdm
 from pathlib import Path
 from loguru import logger
 
 
 class GetData:
+    DATASET_VERSION = "v1"
     REMOTE_URL = "http://fintech.msra.cn/stock_data/downloads"
+    QLIB_DATA_NAME = "{dataset_name}_{region}_{interval}_{qlib_version}.zip"
 
     def __init__(self, delete_zip_file=False):
         """
@@ -20,13 +27,24 @@ class GetData:
         """
         self.delete_zip_file = delete_zip_file
 
-    def _download_data(self, file_name: str, target_dir: [Path, str]):
+    def normalize_dataset_version(self, dataset_version: str = None):
+        if dataset_version is None:
+            dataset_version = self.DATASET_VERSION
+        return dataset_version
+
+    def merge_remote_url(self, file_name: str, dataset_version: str = None):
+        return f"{self.REMOTE_URL}/{self.normalize_dataset_version(dataset_version)}/{file_name}"
+
+    def _download_data(
+        self, file_name: str, target_dir: [Path, str], delete_old: bool = True, dataset_version: str = None
+    ):
         target_dir = Path(target_dir).expanduser()
         target_dir.mkdir(exist_ok=True, parents=True)
+        # saved file name
+        _target_file_name = datetime.datetime.now().strftime("%Y%m%d%H%M%S") + "_" + file_name
+        target_path = target_dir.joinpath(_target_file_name)
 
-        url = f"{self.REMOTE_URL}/{file_name}"
+        url = self.merge_remote_url(file_name, dataset_version)
-        target_path = target_dir.joinpath(file_name)
-
         resp = requests.get(url, stream=True)
         if resp.status_code != 200:
             raise requests.exceptions.HTTPError()
@@ -42,19 +60,59 @@ class GetData:
                     fp.write(chuck)
                     p_bar.update(chuck_size)
 
-        self._unzip(target_path, target_dir)
+        self._unzip(target_path, target_dir, delete_old)
         if self.delete_zip_file:
             target_path.unlike()
 
+    def check_dataset(self, file_name: str, dataset_version: str = None):
+        url = self.merge_remote_url(file_name, dataset_version)
+        resp = requests.get(url, stream=True)
+        status = True
+        if resp.status_code == 404:
+            status = False
+        return status
+
     @staticmethod
-    def _unzip(file_path: Path, target_dir: Path):
+    def _unzip(file_path: Path, target_dir: Path, delete_old: bool = True):
+        if delete_old:
+            logger.warning(
+                f"will delete the old qlib data directory(features, instruments, calendars, features_cache, dataset_cache): {target_dir}"
+            )
+            GetData._delete_qlib_data(target_dir)
         logger.info(f"{file_path} unzipping......")
         with zipfile.ZipFile(str(file_path.resolve()), "r") as zp:
             for _file in tqdm(zp.namelist()):
                 zp.extract(_file, str(target_dir.resolve()))
 
+    @staticmethod
+    def _delete_qlib_data(file_dir: Path):
+        logger.info(f"delete {file_dir}")
+        rm_dirs = []
+        for _name in ["features", "calendars", "instruments", "features_cache", "dataset_cache"]:
+            _p = file_dir.joinpath(_name)
+            if _p.exists():
+                rm_dirs.append(str(_p.resolve()))
+        if rm_dirs:
+            flag = input(
+                f"Will be deleted: "
+                f"\n\t{rm_dirs}"
+                f"\nIf you do not need to delete {file_dir}, please change the <--target_dir>"
+                f"\nAre you sure you want to delete, yes(Y/y), no (N/n):"
+            )
+            if str(flag) not in ["Y", "y"]:
+                exit()
+            for _p in rm_dirs:
+                logger.warning(f"delete: {_p}")
+                shutil.rmtree(_p)
+
     def qlib_data(
-        self, name="qlib_data", target_dir="~/.qlib/qlib_data/cn_data", version="latest", interval="1d", region="cn"
+        self,
+        name="qlib_data",
+        target_dir="~/.qlib/qlib_data/cn_data",
+        version=None,
+        interval="1d",
+        region="cn",
+        delete_old=True,
     ):
         """download cn qlib data from remote
 
@@ -65,20 +123,31 @@ class GetData:
         name: str
             dataset name, value from [qlib_data, qlib_data_simple], by default qlib_data
         version: str
-            data version, value from [v0, v1, ..., latest], by default latest
+            data version, value from [v1, ...], by default None(use script to specify version)
         interval: str
             data freq, value from [1d], by default 1d
         region: str
             data region, value from [cn, us], by default cn
+        delete_old: bool
+            delete an existing directory, by default True
 
         Examples
         ---------
-        python get_data.py qlib_data --name qlib_data --target_dir ~/.qlib/qlib_data/cn_data --version latest --interval 1d --region cn
+        python get_data.py qlib_data --name qlib_data --target_dir ~/.qlib/qlib_data/cn_data --interval 1d --region cn
         -------
 
         """
-        file_name = f"{name}_{region.lower()}_{interval.lower()}_{version}.zip"
+        qlib_version = ".".join(re.findall(r"(\d+)\.+", qlib.__version__))
-        self._download_data(file_name.lower(), target_dir)
+
+        def _get_file_name(v):
+            return self.QLIB_DATA_NAME.format(
+                dataset_name=name, region=region.lower(), interval=interval.lower(), qlib_version=v
+            )
+
+        file_name = _get_file_name(qlib_version)
+        if not self.check_dataset(file_name, version):
+            file_name = _get_file_name("latest")
+        self._download_data(file_name.lower(), target_dir, delete_old, dataset_version=version)
 
     def csv_data_cn(self, target_dir="~/.qlib/csv_data/cn_data"):
         """download cn csv data from remote

qlib/utils/__init__.py

@@ -26,6 +26,7 @@ import pandas as pd
 from pathlib import Path
 from typing import Union, Tuple
 
+from .. import __version__ as qlib_version
 from ..config import C
 from ..log import get_module_logger
 
@@ -643,15 +644,28 @@ def exists_qlib_data(qlib_dir):
     # check instruments
     code_names = set(map(lambda x: x.name.lower(), features_dir.iterdir()))
     _instrument = instruments_dir.joinpath("all.txt")
-    df = pd.read_csv(_instrument, sep="\t", names=["inst", "start_datetime", "end_datetime", "save_inst"])
+    miss_code = set(pd.read_csv(_instrument, sep="\t", header=None).loc[:, 0].apply(str.lower)) - set(code_names)
-    df = df.iloc[:, [0, -1]].fillna(axis=1, method="ffill")
-    miss_code = set(df.iloc[:, -1].apply(str.lower)) - set(code_names)
     if miss_code and any(map(lambda x: "sht" not in x, miss_code)):
         return False
 
     return True
 
 
+def check_qlib_data(qlib_config):
+    inst_dir = Path(qlib_config["provider_uri"]).joinpath("instruments")
+    for _p in inst_dir.glob("*.txt"):
+        try:
+            assert len(pd.read_csv(_p, sep="\t", nrows=0, header=None).columns) == 3, (
+                f"\nThe {str(_p.resolve())} of qlib data is not equal to 3 columns:"
+                f"\n\tIf you are using the data provided by qlib: "
+                f"https://qlib.readthedocs.io/en/latest/component/data.html#qlib-format-dataset"
+                f"\n\tIf you are using your own data, please dump the data again: "
+                f"https://qlib.readthedocs.io/en/latest/component/data.html#converting-csv-format-into-qlib-format"
+            )
+        except AssertionError:
+            raise
+
+
 def lazy_sort_index(df: pd.DataFrame, axis=0) -> pd.DataFrame:
     """
     make the df index sorted
@@ -742,3 +756,36 @@ def load_dataset(path_or_obj):
     elif extension == ".csv":
         return pd.read_csv(path_or_obj, parse_dates=True, index_col=[0, 1])
     raise ValueError(f"unsupported file type `{extension}`")
+
+
+def code_to_fname(code: str):
+    """stock code to file name
+
+    Parameters
+    ----------
+    code: str
+    """
+    # NOTE: In windows, the following name is I/O device, and the file with the corresponding name cannot be created
+    # reference: https://superuser.com/questions/86999/why-cant-i-name-a-folder-or-file-con-in-windows
+    replace_names = ["CON", "PRN", "AUX", "NUL"]
+    replace_names += [f"COM{i}" for i in range(10)]
+    replace_names += [f"LPT{i}" for i in range(10)]
+
+    prefix = "_qlib_"
+    if str(code).upper() in replace_names:
+        code = prefix + str(code)
+
+    return code
+
+
+def fname_to_code(fname: str):
+    """file name to stock code
+
+    Parameters
+    ----------
+    fname: str
+    """
+    prefix = "_qlib_"
+    if fname.startswith(prefix):
+        fname = fname.lstrip(prefix)
+    return fname

scripts/data_collector/yahoo/README.md

@@ -20,7 +20,7 @@ pip install -r requirements.txt
 
 ### Download data and Normalize data
 ```bash
-python collector.py collector_data --source_dir ~/.qlib/stock_data/source --region CN --start 2020-11-01 --end 2020-11-10 --delay 0.1 --interval 1d
+python collector.py collector_data --source_dir ~/.qlib/stock_data/source --region CN --start 2020-11-01 --end 2020-11-10 --delay 0.1 --interval 1d --normalize_dir ~/.qlib/stock_data/normalize
 ```
 
 ### Download Data

scripts/data_collector/yahoo/collector.py

@@ -18,6 +18,7 @@ from tqdm import tqdm
 from loguru import logger
 from yahooquery import Ticker
 from dateutil.tz import tzlocal
+from qlib.utils import code_to_fname
 
 CUR_DIR = Path(__file__).resolve().parent
 sys.path.append(str(CUR_DIR.parent.parent))
@@ -40,7 +41,7 @@ class YahooCollector:
         end=None,
         interval="1d",
         max_workers=4,
-        max_collector_count=5,
+        max_collector_count=2,
         delay=0,
         check_data_length: bool = False,
         limit_nums: int = None,
@@ -55,7 +56,7 @@ class YahooCollector:
         max_workers: int
             workers, default 4
         max_collector_count: int
-            default 5
+            default 2
         delay: float
             time.sleep(delay), default 0
         interval: str
@@ -147,11 +148,10 @@ class YahooCollector:
         stock_path = self.save_dir.joinpath(f"{symbol}.csv")
         df["symbol"] = symbol
         if stock_path.exists():
-            with stock_path.open("a") as fp:
+            _temp_df = pd.read_csv(stock_path, nrows=0)
-                df.to_csv(fp, index=False, header=False)
+            df.loc[:, _temp_df.columns].to_csv(stock_path, index=False, header=False, mode="a")
         else:
-            with stock_path.open("w") as fp:
+            df.to_csv(stock_path, index=False, mode="w")
-                df.to_csv(fp, index=False)
 
     def _save_small_data(self, symbol, df):
         if len(df) <= self.min_numbers_trading:
@@ -350,7 +350,7 @@ class YahooCollectorUS(YahooCollector):
         pass
 
     def normalize_symbol(self, symbol):
-        return symbol.upper()
+        return code_to_fname(symbol).upper()
 
     @property
     def _timezone(self):

scripts/dump_bin.py

@@ -14,6 +14,7 @@ import numpy as np
 import pandas as pd
 from tqdm import tqdm
 from loguru import logger
+from qlib.utils import fname_to_code, code_to_fname
 
 
 class DumpDataBase:
@@ -27,7 +28,6 @@ class DumpDataBase:
     HIGH_FREQ_FORMAT = "%Y-%m-%d %H:%M:%S"
     INSTRUMENTS_SEP = "\t"
     INSTRUMENTS_FILE_NAME = "all.txt"
-    SAVE_INST_FIELD = "save_inst"
 
     UPDATE_MODE = "update"
     ALL_MODE = "all"
@@ -45,7 +45,6 @@ class DumpDataBase:
         exclude_fields: str = "",
         include_fields: str = "",
         limit_nums: int = None,
-        inst_prefix: str = "",
     ):
         """
 
@@ -73,9 +72,6 @@ class DumpDataBase:
             fields not dumped
         limit_nums: int
             Use when debugging, default None
-        inst_prefix: str
-            add a column to the instruments file and record the saved instrument name,
-            the US stock code contains "PRN", and the directory cannot be created on Windows system, use the "_" prefix.
         """
         csv_path = Path(csv_path).expanduser()
         if isinstance(exclude_fields, str):
@@ -84,7 +80,6 @@ class DumpDataBase:
             include_fields = include_fields.split(",")
         self._exclude_fields = tuple(filter(lambda x: len(x) > 0, map(str.strip, exclude_fields)))
         self._include_fields = tuple(filter(lambda x: len(x) > 0, map(str.strip, include_fields)))
-        self._inst_prefix = inst_prefix.strip()
         self.file_suffix = file_suffix
         self.symbol_field_name = symbol_field_name
         self.csv_files = sorted(csv_path.glob(f"*{self.file_suffix}") if csv_path.is_dir() else [csv_path])
@@ -145,7 +140,7 @@ class DumpDataBase:
         return df
 
     def get_symbol_from_file(self, file_path: Path) -> str:
-        return file_path.name[: -len(self.file_suffix)].strip().lower()
+        return fname_to_code(file_path.name[: -len(self.file_suffix)].strip().lower())
 
     def get_dump_fields(self, df_columns: Iterable[str]) -> Iterable[str]:
         return (
@@ -173,7 +168,6 @@ class DumpDataBase:
                 self.symbol_field_name,
                 self.INSTRUMENTS_START_FIELD,
                 self.INSTRUMENTS_END_FIELD,
-                self.SAVE_INST_FIELD,
             ],
         )
 
@@ -190,13 +184,11 @@ class DumpDataBase:
         instruments_path = str(self._instruments_dir.joinpath(self.INSTRUMENTS_FILE_NAME).resolve())
         if isinstance(instruments_data, pd.DataFrame):
             _df_fields = [self.symbol_field_name, self.INSTRUMENTS_START_FIELD, self.INSTRUMENTS_END_FIELD]
-            if self._inst_prefix:
-                _df_fields.append(self.SAVE_INST_FIELD)
-                instruments_data[self.SAVE_INST_FIELD] = instruments_data[self.symbol_field_name].apply(
-                    lambda x: f"{self._inst_prefix}{x}"
-                )
             instruments_data = instruments_data.loc[:, _df_fields]
-            instruments_data.to_csv(instruments_path, header=False, sep=self.INSTRUMENTS_SEP)
+            instruments_data[self.symbol_field_name] = instruments_data[self.symbol_field_name].apply(
+                lambda x: fname_to_code(x.lower()).upper()
+            )
+            instruments_data.to_csv(instruments_path, header=False, sep=self.INSTRUMENTS_SEP, index=False)
         else:
             np.savetxt(instruments_path, instruments_data, fmt="%s", encoding="utf-8")
 
@@ -223,26 +215,26 @@ class DumpDataBase:
             logger.warning(f"{features_dir.name} data is None or empty")
             return
         # align index
-        _df = self.data_merge_calendar(df, self._calendars_list)
+        _df = self.data_merge_calendar(df, calendar_list)
+        # used when creating a bin file
         date_index = self.get_datetime_index(_df, calendar_list)
         for field in self.get_dump_fields(_df.columns):
             bin_path = features_dir.joinpath(f"{field}.{self.freq}{self.DUMP_FILE_SUFFIX}")
             if field not in _df.columns:
                 continue
-            if self._mode == self.UPDATE_MODE:
+            if bin_path.exists() and self._mode == self.UPDATE_MODE:
                 # update
                 with bin_path.open("ab") as fp:
                     np.array(_df[field]).astype("<f").tofile(fp)
-            elif self._mode == self.ALL_MODE:
-                np.hstack([date_index, _df[field]]).astype("<f").tofile(str(bin_path.resolve()))
             else:
-                raise ValueError(f"{self._mode} cannot support!")
+                # append; self._mode == self.ALL_MODE or not bin_path.exists()
+                np.hstack([date_index, _df[field]]).astype("<f").tofile(str(bin_path.resolve()))
 
     def _dump_bin(self, file_or_data: [Path, pd.DataFrame], calendar_list: List[pd.Timestamp]):
         if isinstance(file_or_data, pd.DataFrame):
             if file_or_data.empty:
                 return
-            code = file_or_data.iloc[0][self.symbol_field_name].lower()
+            code = fname_to_code(file_or_data.iloc[0][self.symbol_field_name].lower())
             df = file_or_data
         elif isinstance(file_or_data, Path):
             code = self.get_symbol_from_file(file_or_data)
@@ -253,8 +245,7 @@ class DumpDataBase:
             logger.warning(f"{code} data is None or empty")
             return
         # features save dir
-        code = self._inst_prefix + code if self._inst_prefix else code
+        features_dir = self._features_dir.joinpath(code_to_fname(code).lower())
-        features_dir = self._features_dir.joinpath(code)
         features_dir.mkdir(parents=True, exist_ok=True)
         self._data_to_bin(df, calendar_list, features_dir)
 
@@ -283,8 +274,6 @@ class DumpDataAll(DumpDataBase):
                         _end_time = self._format_datetime(_end_time)
                         symbol = self.get_symbol_from_file(file_path)
                         _inst_fields = [symbol.upper(), _begin_time, _end_time]
-                        if self._inst_prefix:
-                            _inst_fields.append(self._inst_prefix + symbol.upper())
                         date_range_list.append(f"{self.INSTRUMENTS_SEP.join(_inst_fields)}")
                     p_bar.update()
         self._kwargs["all_datetime_set"] = all_datetime
@@ -323,12 +312,18 @@ class DumpDataFix(DumpDataAll):
     def _dump_instruments(self):
         logger.info("start dump instruments......")
         _fun = partial(self._get_date, is_begin_end=True)
-        new_stock_files = sorted(filter(lambda x: x.name not in self._old_instruments, self.csv_files))
+        new_stock_files = sorted(
+            filter(
+                lambda x: fname_to_code(x.name[: -len(self.file_suffix)].strip().lower()).upper()
+                not in self._old_instruments,
+                self.csv_files,
+            )
+        )
         with tqdm(total=len(new_stock_files)) as p_bar:
             with ProcessPoolExecutor(max_workers=self.works) as execute:
                 for file_path, (_begin_time, _end_time) in zip(new_stock_files, execute.map(_fun, new_stock_files)):
                     if isinstance(_begin_time, pd.Timestamp) and isinstance(_end_time, pd.Timestamp):
-                        symbol = self.get_symbol_from_file(file_path).upper()
+                        symbol = fname_to_code(self.get_symbol_from_file(file_path).lower()).upper()
                         _dt_map = self._old_instruments.setdefault(symbol, dict())
                         _dt_map[self.INSTRUMENTS_START_FIELD] = self._format_datetime(_begin_time)
                         _dt_map[self.INSTRUMENTS_END_FIELD] = self._format_datetime(_end_time)
@@ -406,10 +401,10 @@ class DumpDataUpdate(DumpDataBase):
         )
         self._mode = self.UPDATE_MODE
         self._old_calendar_list = self._read_calendars(self._calendars_dir.joinpath(f"{self.freq}.txt"))
-        self._update_instruments = self._read_instruments(
+        self._update_instruments = (
-            self._instruments_dir.joinpath(self.INSTRUMENTS_FILE_NAME)
+            self._read_instruments(self._instruments_dir.joinpath(self.INSTRUMENTS_FILE_NAME))
-        ).to_dict(
+            .set_index([self.symbol_field_name])
-            orient="index"
+            .to_dict(orient="index")
         )  # type: dict
 
         # load all csv files
@@ -425,10 +420,7 @@ class DumpDataUpdate(DumpDataBase):
         all_df = []
 
         def _read_csv(file_path: Path):
-            if self._include_fields:
+            _df = pd.read_csv(file_path, parse_dates=[self.date_field_name])
-                _df = pd.read_csv(file_path, usecols=self._include_fields)
-            else:
-                _df = pd.read_csv(file_path)
             if self.symbol_field_name not in _df.columns:
                 _df[self.symbol_field_name] = self.get_symbol_from_file(file_path)
             return _df
@@ -436,7 +428,7 @@ class DumpDataUpdate(DumpDataBase):
         with tqdm(total=len(self.csv_files)) as p_bar:
             with ThreadPoolExecutor(max_workers=self.works) as executor:
                 for df in executor.map(_read_csv, self.csv_files):
-                    if df:
+                    if not df.empty:
                         all_df.append(df)
                     p_bar.update()
 
@@ -455,25 +447,27 @@ class DumpDataUpdate(DumpDataBase):
         with ProcessPoolExecutor(max_workers=self.works) as executor:
             futures = {}
             for _code, _df in self._all_data.groupby(self.symbol_field_name):
-                _code = str(_code).upper()
+                _code = fname_to_code(str(_code).lower()).upper()
                 _start, _end = self._get_date(_df, is_begin_end=True)
                 if not (isinstance(_start, pd.Timestamp) and isinstance(_end, pd.Timestamp)):
                     continue
                 if _code in self._update_instruments:
-                    self._update_instruments[_code]["end_time"] = _end
+                    self._update_instruments[_code][self.INSTRUMENTS_END_FIELD] = self._format_datetime(_end)
                     futures[executor.submit(self._dump_bin, _df, self._update_calendars)] = _code
                 else:
                     # new stock
                     _dt_range = self._update_instruments.setdefault(_code, dict())
-                    _dt_range["start_time"] = _start
+                    _dt_range[self.INSTRUMENTS_START_FIELD] = self._format_datetime(_start)
-                    _dt_range["end_time"] = _end
+                    _dt_range[self.INSTRUMENTS_END_FIELD] = self._format_datetime(_end)
                     futures[executor.submit(self._dump_bin, _df, self._new_calendar_list)] = _code
 
-            for _future in tqdm(as_completed(futures)):
+            with tqdm(total=len(futures)) as p_bar:
-                try:
+                for _future in as_completed(futures):
-                    _future.result()
+                    try:
-                except Exception:
+                        _future.result()
-                    error_code[futures[_future]] = traceback.format_exc()
+                    except Exception:
+                        error_code[futures[_future]] = traceback.format_exc()
+                    p_bar.update()
             logger.info(f"dump bin errors： {error_code}")
 
         logger.info("end of features dump.\n")
@@ -481,7 +475,9 @@ class DumpDataUpdate(DumpDataBase):
     def dump(self):
         self.save_calendars(self._new_calendar_list)
         self._dump_features()
-        self.save_instruments(pd.DataFrame.from_dict(self._update_instruments, orient="index"))
+        df = pd.DataFrame.from_dict(self._update_instruments, orient="index")
+        df.index.names = [self.symbol_field_name]
+        self.save_instruments(df.reset_index())
 
 
 if __name__ == "__main__":

scripts/get_data.py

@@ -1,5 +1,6 @@
 #  Copyright (c) Microsoft Corporation.
 #  Licensed under the MIT License.
+
 import fire
 from qlib.tests.data import GetData
 

setup.py

@@ -11,7 +11,7 @@ NAME = "pyqlib"
 DESCRIPTION = "A Quantitative-research Platform"
 REQUIRES_PYTHON = ">=3.5.0"
 
-VERSION = "0.6.1.dev"
+VERSION = "0.6.1.99.dev"
 
 # Detect Cython
 try:

tests/test_get_data.py

@@ -37,7 +37,7 @@ class TestGetData(unittest.TestCase):
 
     def test_0_qlib_data(self):
 
-        GetData().qlib_data(name="qlib_data_simple", target_dir=QLIB_DIR, region="cn", interval="1d", version="latest")
+        GetData().qlib_data(name="qlib_data_simple", target_dir=QLIB_DIR, region="cn", interval="1d", delete_old=False)
         df = D.features(D.instruments("csi300"), self.FIELDS)
         self.assertListEqual(list(df.columns), self.FIELDS, "get qlib data failed")
         self.assertFalse(df.dropna().empty, "get qlib data failed")