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authorDanglewood <85772166+deeleeramone@users.noreply.github.com>2024-06-29 19:35:57 -0700
committerDanglewood <85772166+deeleeramone@users.noreply.github.com>2024-06-29 19:35:57 -0700
commite84b5a5be5009c5a6f0dea03a18b1894d04aa8cc (patch)
tree47b4850f5f837c02d12e13ae692e8361eb28c556
parent9fcbc2e2fcb9ec0cf39a16b50d2c651fd86e5b04 (diff)
pylint
-rw-r--r--openbb_platform/providers/cboe/openbb_cboe/utils/vix.py13
1 files changed, 6 insertions, 7 deletions
diff --git a/openbb_platform/providers/cboe/openbb_cboe/utils/vix.py b/openbb_platform/providers/cboe/openbb_cboe/utils/vix.py
index bbd3eb33432..150e017c90d 100644
--- a/openbb_platform/providers/cboe/openbb_cboe/utils/vix.py
+++ b/openbb_platform/providers/cboe/openbb_cboe/utils/vix.py
@@ -47,9 +47,8 @@ def get_front_month(date: Optional[str] = None):
if today.day > third_wednesday:
# If today is after the third Wednesday of the month, return the next month
return (today.month % 12) + 1
- else:
- # Otherwise, return the current month
- return today.month
+ # Otherwise, return the current month
+ return today.month
def get_vx_symbols(date: Optional[str] = None) -> Dict:
@@ -165,6 +164,7 @@ async def get_vx_current(
return df
+# pylint: disable=too-many-locals
async def get_vx_by_date(
date: Union[str, List[str]],
vx_type: Literal["am", "eod"] = "eod",
@@ -193,7 +193,6 @@ async def get_vx_by_date(
from openbb_core.app.model.abstract.error import OpenBBError
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_cboe.models.equity_historical import CboeEquityHistoricalFetcher
- from numpy import abs
from pandas import Categorical, DataFrame, DatetimeIndex, concat, isna, to_datetime
if vx_type not in ["am", "eod"]:
@@ -263,10 +262,10 @@ async def get_vx_by_date(
df = df.dropna(how="any")
nearest_dates = []
- for date in dates_list:
- nearest_date = df.index.asof(date)
+ for date_ in dates_list:
+ nearest_date = df.index.asof(date_)
if isna(nearest_date): # type: ignore
- differences = abs(df.index - date)
+ differences = abs(df.index - date_)
min_diff_index = differences.argmin()
nearest_date = df.index[min_diff_index]
nearest_dates.append(nearest_date)