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Fix typos and grammar errors in docstrings and comments (#1366)

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* fix gramma error in doc strings

* fix typos in exchange.py

* fix typos and gramma errors

* fix typo and rename function param to avoid shading python keyword

* remove redundant parathesis; pass kwargs to parent class

* fix pyblack

* further correction

* assign -> be assigned to
This commit is contained in:
YQ Tsui
2022-11-20 14:15:59 +08:00
committed by GitHub
parent 0c4db8b0f8
commit cc01812c62
24 changed files with 77 additions and 72 deletions
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26
qlib/backtest/exchange.py
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@@ -27,10 +27,10 @@ from .high_performance_ds import BaseQuote, NumpyQuote
class Exchange:
# `quote_df` is a pd.DataFrame class that contains basic information for backtesting
# After some processing, the data will later be maintained by `quote_cls` object for faster data retriving.
# After some processing, the data will later be maintained by `quote_cls` object for faster data retrieving.
# Some conventions for `quote_df`
# - $close is for calculating the total value at end of each day.
# - if $close is None, the stock on that day is reguarded as suspended.
# - if $close is None, the stock on that day is regarded as suspended.
# - $factor is for rounding to the trading unit;
# - if any $factor is missing when $close exists, trading unit rounding will be disabled
quote_df: pd.DataFrame
@@ -141,7 +141,7 @@ class Exchange:
if deal_price is None:
deal_price = C.deal_price
# we have some verbose information here. So logging is enable
# we have some verbose information here. So logging is enabled
self.logger = get_module_logger("online operator")
# TODO: the quote, trade_dates, codes are not necessary.
@@ -168,7 +168,7 @@ class Exchange:
self.codes = codes
# Necessary fields
# $close is for calculating the total value at end of each day.
# - if $close is None, the stock on that day is reguarded as suspended.
# - if $close is None, the stock on that day is regarded as suspended.
# $factor is for rounding to the trading unit
# $change is for calculating the limit of the stock
@@ -271,7 +271,7 @@ class Exchange:
raise NotImplementedError(f"This type of `limit_threshold` is not supported")
def _update_limit(self, limit_threshold: Union[Tuple, float, None]) -> None:
# $close is may contains NaN, the nan indicates that the stock is not tradable at that timestamp
# $close may contain NaN, the nan indicates that the stock is not tradable at that timestamp
suspended = self.quote_df["$close"].isna()
# check limit_threshold
limit_type = self._get_limit_type(limit_threshold)
@@ -356,12 +356,12 @@ class Exchange:
Returns
-------
True: the trading of the stock is limted (maybe hit the highest/lowest price), hence the stock is not tradable
True: the trading of the stock is limited (maybe hit the highest/lowest price), hence the stock is not tradable
False: the trading of the stock is not limited, hence the stock may be tradable
"""
# NOTE:
# **all** is used when checking limitation.
# For example, the stock trading is limited in a day if every miniute is limited in a day if every miniute is limited.
# For example, the stock trading is limited in a day if every minute is limited in a day if every minute is limited.
if direction is None:
# The trading limitation is related to the trading direction
# if the direction is not provided, then any limitation from buy or sell will result in trading limitation
@@ -385,17 +385,17 @@ class Exchange:
# is suspended
if stock_id in self.quote.get_all_stock():
# suspended stocks are represented by None $close stock
# The $close may contains NaN,
# The $close may contain NaN,
close = self.quote.get_data(stock_id, start_time, end_time, "$close")
if close is None:
# if no close record exists
return True
elif isinstance(close, IndexData):
# **any** non-NaN $close represents trading opportunity may exists
# **any** non-NaN $close represents trading opportunity may exist
# if all returned is nan, then the stock is suspended
return cast(bool, cast(IndexData, close).isna().all())
else:
# it is single value, make sure is is not None
# it is single value, make sure is not None
return np.isnan(close)
else:
# if the stock is not in the stock list, then it is not tradable and regarded as suspended
@@ -540,8 +540,8 @@ class Exchange:
direction: OrderDir = OrderDir.BUY,
) -> dict:
"""
The generate the target position according to the weight and the cash.
NOTE: All the cash will assigned to the tradable stock.
Generates the target position according to the weight and the cash.
NOTE: All the cash will be assigned to the tradable stock.
Parameter:
weight_position : dict {stock_id : weight}; allocate cash by weight_position
among then, weight must be in this range: 0 < weight < 1
@@ -639,7 +639,7 @@ class Exchange:
random.shuffle(sorted_ids)
for stock_id in sorted_ids:
# Do not generate order for the nontradable stocks
# Do not generate order for the non-tradable stocks
if not self.is_stock_tradable(stock_id=stock_id, start_time=start_time, end_time=end_time):
continue