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8 Commits
bump_versi
...
fix_docs
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091f542b42 | ||
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917e3a725e | ||
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b1e0e77c97 | ||
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ea245f5435 | ||
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3779b5186a | ||
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77d34e080b | ||
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69daea0adc | ||
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975aeb7a99 |
2
.gitignore
vendored
2
.gitignore
vendored
@@ -48,4 +48,4 @@ tags
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*.swp
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./pretrain
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.idea/
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.idea/
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@@ -5,6 +5,12 @@
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# Required
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version: 2
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# Set the version of Python and other tools you might need
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build:
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os: ubuntu-22.04
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tools:
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python: "3.7"
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# Build documentation in the docs/ directory with Sphinx
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sphinx:
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configuration: docs/conf.py
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@@ -14,7 +20,6 @@ formats: all
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# Optionally set the version of Python and requirements required to build your docs
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python:
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version: 3.7
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install:
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- requirements: docs/requirements.txt
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- method: pip
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@@ -25,7 +25,12 @@ import pandas as pd
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from pathlib import Path
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from typing import List, Union, Optional, Callable
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from packaging import version
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from .file import get_or_create_path, save_multiple_parts_file, unpack_archive_with_buffer, get_tmp_file_with_buffer
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from .file import (
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get_or_create_path,
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save_multiple_parts_file,
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unpack_archive_with_buffer,
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get_tmp_file_with_buffer,
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)
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from ..config import C
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from ..log import get_module_logger, set_log_with_config
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@@ -37,7 +42,12 @@ is_deprecated_lexsorted_pandas = version.parse(pd.__version__) > version.parse("
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#################### Server ####################
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def get_redis_connection():
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"""get redis connection instance."""
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return redis.StrictRedis(host=C.redis_host, port=C.redis_port, db=C.redis_task_db, password=C.redis_password)
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return redis.StrictRedis(
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host=C.redis_host,
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port=C.redis_port,
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db=C.redis_task_db,
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password=C.redis_password,
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)
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#################### Data ####################
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@@ -96,7 +106,14 @@ def get_period_offset(first_year, period, quarterly):
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return offset
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def read_period_data(index_path, data_path, period, cur_date_int: int, quarterly, last_period_index: int = None):
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def read_period_data(
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index_path,
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data_path,
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period,
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cur_date_int: int,
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quarterly,
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last_period_index: int = None,
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):
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"""
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At `cur_date`(e.g. 20190102), read the information at `period`(e.g. 201803).
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Only the updating info before cur_date or at cur_date will be used.
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@@ -273,7 +290,10 @@ def parse_field(field):
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# \uff09 -> )
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chinese_punctuation_regex = r"\u3001\uff1a\uff08\uff09"
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for pattern, new in [
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(rf"\$\$([\w{chinese_punctuation_regex}]+)", r'PFeature("\1")'), # $$ must be before $
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(
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rf"\$\$([\w{chinese_punctuation_regex}]+)",
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r'PFeature("\1")',
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), # $$ must be before $
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(rf"\$([\w{chinese_punctuation_regex}]+)", r'Feature("\1")'),
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(r"(\w+\s*)\(", r"Operators.\1("),
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]: # Features # Operators
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@@ -383,7 +403,14 @@ def get_date_range(trading_date, left_shift=0, right_shift=0, future=False):
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return calendar
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def get_date_by_shift(trading_date, shift, future=False, clip_shift=True, freq="day", align: Optional[str] = None):
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def get_date_by_shift(
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trading_date,
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shift,
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future=False,
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clip_shift=True,
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freq="day",
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align: Optional[str] = None,
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):
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"""get trading date with shift bias will cur_date
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e.g. : shift == 1, return next trading date
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shift == -1, return previous trading date
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@@ -569,7 +596,38 @@ def exists_qlib_data(qlib_dir):
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# check instruments
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code_names = set(map(lambda x: fname_to_code(x.name.lower()), features_dir.iterdir()))
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_instrument = instruments_dir.joinpath("all.txt")
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miss_code = set(pd.read_csv(_instrument, sep="\t", header=None).loc[:, 0].apply(str.lower)) - set(code_names)
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# Removed two possible ticker names "NA" and "NULL" from the default na_values list for column 0
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miss_code = set(
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pd.read_csv(
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_instrument,
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sep="\t",
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header=None,
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keep_default_na=False,
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na_values={
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0: [
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" ",
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"#N/A",
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"#N/A N/A",
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"#NA",
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"-1.#IND",
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"-1.#QNAN",
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"-NaN",
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"-nan",
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"1.#IND",
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"1.#QNAN",
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"<NA>",
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"N/A",
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"NaN",
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"None",
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"n/a",
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"nan",
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"null ",
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]
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},
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)
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.loc[:, 0]
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.apply(str.lower)
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) - set(code_names)
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if miss_code and any(map(lambda x: "sht" not in x, miss_code)):
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return False
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@@ -396,14 +396,7 @@ class CSI500Index(CSIIndex):
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today = pd.Timestamp.now()
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date_range = pd.DataFrame(pd.date_range(start="2007-01-15", end=today, freq="7D"))[0].dt.date
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ret_list = []
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col = ["date", "symbol", "code_name"]
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for date in tqdm(date_range, desc="Download CSI500"):
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rs = bs.query_zz500_stocks(date=str(date))
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zz500_stocks = []
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while (rs.error_code == "0") & rs.next():
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zz500_stocks.append(rs.get_row_data())
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result = pd.DataFrame(zz500_stocks, columns=col)
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result["symbol"] = result["symbol"].apply(lambda x: x.replace(".", "").upper())
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result = self.get_data_from_baostock(date)
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ret_list.append(result[["date", "symbol"]])
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bs.logout()
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@@ -3,7 +3,7 @@
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"""
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TODO:
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- A more well-designed PIT database is required.
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- seperated insert, delete, update, query operations are required.
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- separated insert, delete, update, query operations are required.
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"""
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import shutil
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