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high_performance_data_structure

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wangwenxi.handsome
2021-07-22 15:20:03 +00:00
parent 10c182e2b0
commit 2c8a3ded08
3 changed files with 453 additions and 344 deletions
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106
qlib/backtest/exchange.py
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@@ -4,7 +4,7 @@
import random
import logging
from typing import List, Tuple, Union
from typing import List, Tuple, Union, Callable, Iterable
import numpy as np
import pandas as pd
@@ -15,6 +15,7 @@ from ..config import C, REG_CN
from ..utils.resam import resam_ts_data, ts_data_last
from ..log import get_module_logger
from .order import Order, OrderDir, OrderHelper
from .high_performane_ds import PandasQuote
class Exchange:
@@ -32,6 +33,7 @@ class Exchange:
close_cost=0.0025,
min_cost=5,
extra_quote=None,
quote_cls=PandasQuote,
**kwargs,
):
"""__init__
@@ -143,7 +145,8 @@ class Exchange:
self.get_quote_from_qlib()
# init quote by quote_df
self.quote = PandasQuote(self.quote_df)
self.quote_cls = quote_cls
self.quote = self.quote_cls(self.quote_df)
def get_quote_from_qlib(self):
# get stock data from qlib
@@ -593,102 +596,3 @@ class Exchange:
# cache to avoid recreate the same instance
self._order_helper = OrderHelper(self)
return self._order_helper
class BaseQuote:
def __init__(self, quote_df: pd.DataFrame):
self.logger = get_module_logger("online operator", level=logging.INFO)
def get_all_stock(self):
"""return all stock codes
Return
------
Union[list, Dict.keys(), set, tuple]
all stock codes
"""
raise NotImplementedError(f"Please implement the `get_all_stock` method")
def get_data(
self,
stock_id: Union[str, list],
start_time: Union[pd.Timestamp, str],
end_time: Union[pd.Timestamp, str],
fields: Union[str, list] = None,
method: Union[str, "Callable"] = None,
):
"""get the specific fields of stock data during start time and end_time,
and apply method to the data.
Example:
.. code-block::
$close $volume
instrument datetime
SH600000 2010-01-04 86.778313 16162960.0
2010-01-05 87.433578 28117442.0
2010-01-06 85.713585 23632884.0
2010-01-07 83.788803 20813402.0
2010-01-08 84.730675 16044853.0
SH600655 2010-01-04 2699.567383 158193.328125
2010-01-08 2612.359619 77501.406250
2010-01-11 2712.982422 160852.390625
2010-01-12 2788.688232 164587.937500
2010-01-13 2790.604004 145460.453125
print(get_data(stock_id=["SH600000", "SH600655"], start_time="2010-01-04", end_time="2010-01-05", fields=["$close", "$volume"], method="last"))
$close $volume
instrument
SH600000 87.433578 28117442.0
SH600655 2699.567383 158193.328125
print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-05", fields=["$close", "$volume"], method="last"))
$close 87.433578
$volume 28117442.0
print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-05", fields="$close", method="last"))
87.433578
Parameters
----------
stock_id: Union[str, list]
start_time : Union[pd.Timestamp, str]
closed start time for backtest
end_time : Union[pd.Timestamp, str]
closed end time for backtest
fields : Union[str, List]
the columns of data to fetch
method : Union[str, Callable]
the method apply to data.
e.g ["None", "last", "all", "sum", "mean", "any", qlib/utils/resam.py/ts_data_last]
Return
----------
Union[None, float, pd.Series, pd.DataFrame]
The resampled DataFrame/Series/value, return None when the resampled data is empty.
"""
raise NotImplementedError(f"Please implement the `get_data` method")
class PandasQuote(BaseQuote):
def __init__(self, quote_df: pd.DataFrame):
super().__init__(quote_df=quote_df)
quote_dict = {}
for stock_id, stock_val in quote_df.groupby(level="instrument"):
quote_dict[stock_id] = stock_val.droplevel(level="instrument")
self.data = quote_dict
def get_all_stock(self):
return self.data.keys()
def get_data(self, stock_id, start_time, end_time, fields=None, method=None):
if fields is None:
return resam_ts_data(self.data[stock_id], start_time, end_time, method=method)
elif isinstance(fields, (str, list)):
return resam_ts_data(self.data[stock_id][fields], start_time, end_time, method=method)
else:
raise ValueError(f"fields must be None, str or list")