...

src/mplchart/indicators.py

@@ -1,4 +1,4 @@
-""" technical analysis indicators """
+"""technical analysis indicators"""
 
 import numpy as np
 
@@ -9,7 +9,6 @@
 from .colors import default_edgecolor, closest_color
 
 
-
 class SMA(Indicator):
     """Simple Moving Average"""
 
@@ -104,8 +103,6 @@ def __call__(self, prices):
         return library.calc_slope(series, self.period)
 
 
-
-
 class RSI(Indicator):
     """Relative Strengh Index"""
 
@@ -167,7 +164,6 @@ def plot_result(self, data, chart, ax=None):
         ax.grid(axis="y", which="major", linestyle="-", linewidth=2)
 
 
-
 class DMI(Indicator):
     """Directional Movement Index"""
 
@@ -187,7 +183,6 @@ def plot_result(self, data, chart, ax=None):
         pdi = data.iloc[:, 1]
         ndi = data.iloc[:, 2]
 
-
         adxcolor = default_edgecolor()
         pdicolor = closest_color("green")
         ndicolor = closest_color("red")

src/mplchart/library.py

@@ -1,10 +1,10 @@
-""" technical analysis library """
+"""technical analysis library"""
 
 import math
 import numpy as np
 import pandas as pd
 
-from .utils import get_series # noqa F401
+from .utils import get_series  # noqa F401
 
 # TODO remove get_series import
 
@@ -43,9 +43,9 @@ def calc_hma(series, period: int = 20):
     if period <= 0:
         raise ValueError("period must be greater than zero")
 
-    m1 = calc_wma(series, round(period/2))
+    m1 = calc_wma(series, round(period / 2))
     m2 = calc_wma(series, period)
-    m3 = (2 *  m1) - m2
+    m3 = (2 * m1) - m2
 
     result = calc_wma(m3, round(math.sqrt(period)))
 
@@ -68,17 +68,17 @@ def calc_rsi(series, period: int = 14):
 def calc_atr(prices, period: int = 14, *, percent: bool = False):
     """Average True Range"""
 
-    hlc = prices.filter(['high', 'low']).join(prices['close'].shift(1))
+    hlc = prices.filter(["high", "low"]).join(prices["close"].shift(1))
     trange = hlc.max(axis=1) - hlc.min(axis=1)
 
     if period > 0:
         ewm = dict(alpha=1 / period, min_periods=period, adjust=True, ignore_na=True)
         result = trange.ewm(**ewm).mean()
     else:
         result = trange
-    
+
     if percent:
-        result = 100 * result / prices['close']
+        result = 100 * result / prices["close"]
 
     return result
 
@@ -152,7 +152,6 @@ def calc_ndi(prices, period: int = 14):
     return calc_dmi(prices, period).ndi
 
 
-
 def calc_slope(series, period: int = 20):
     """calculates the slope (lnear regression) over a rolling window"""
 

tox.ini

@@ -18,3 +18,8 @@ basepython = python3
 skip_install = true
 setenv = RUFF_CACHE_DIR={env:TMPDIR}/ruff_cache
 
+[flake8]
+exclude = .*, build, dist
+max-line-length = 88
+per-file-ignores =
+    __init__.py: F401