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Feat/pandas-ta >= 0.4 compatibility #266

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Merged
rapcmia merged 2 commits into from
Oct 27, 2025
Merged

Feat/pandas-ta >= 0.4 compatibility #266

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6f6b9d5
update bbands use with lower_std and upper_std
lgrawet Oct 22, 2025
0cd75d2
Remove pandas_ta dependency from environment
david-hummingbot Oct 27, 2025
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1 change: 0 additions & 1 deletion environment_conda.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@ dependencies:
- glom
- defillama
- statsmodels
- pandas_ta==0.3.14b
- pyyaml
- pathlib
- streamlit-authenticator==0.3.2
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8 changes: 4 additions & 4 deletions frontend/visualization/indicators.py
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Expand Up @@ -7,10 +7,10 @@

def get_bbands_traces(df, bb_length, bb_std):
tech_colors = theme.get_color_scheme()
df.ta.bbands(length=bb_length, std=bb_std, append=True)
bb_lower = f'BBL_{bb_length}_{bb_std}'
bb_middle = f'BBM_{bb_length}_{bb_std}'
bb_upper = f'BBU_{bb_length}_{bb_std}'
df.ta.bbands(length=bb_length, lower_std=bb_std, upper_std=bb_std, append=True)
bb_lower = f'BBL_{bb_length}_{bb_std}_{bb_std}'
bb_middle = f'BBM_{bb_length}_{bb_std}_{bb_std}'
bb_upper = f'BBU_{bb_length}_{bb_std}_{bb_std}'
traces = [
go.Scatter(x=df.index, y=df[bb_upper], line=dict(color=tech_colors['upper_band']),
name='Upper Band'),
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10 changes: 5 additions & 5 deletions frontend/visualization/signals.py
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Expand Up @@ -20,23 +20,23 @@ def get_signal_traces(buy_signals, sell_signals):
def get_bollinger_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold):
# Add Bollinger Bands
candles = df.copy()
candles.ta.bbands(length=bb_length, std=bb_std, append=True)
candles.ta.bbands(length=bb_length, lower_std=bb_std, upper_std=bb_std, append=True)

# Generate conditions
buy_signals = candles[candles[f"BBP_{bb_length}_{bb_std}"] < bb_long_threshold]
sell_signals = candles[candles[f"BBP_{bb_length}_{bb_std}"] > bb_short_threshold]
buy_signals = candles[candles[f"BBP_{bb_length}_{bb_std}_{bb_std}"] < bb_long_threshold]
sell_signals = candles[candles[f"BBP_{bb_length}_{bb_std}_{bb_std}"] > bb_short_threshold]

return get_signal_traces(buy_signals, sell_signals)


def get_macdbb_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold, macd_fast, macd_slow,
macd_signal):
# Add Bollinger Bands
df.ta.bbands(length=bb_length, std=bb_std, append=True)
df.ta.bbands(length=bb_length, lower_std=bb_std, upper_std=bb_std, append=True)
# Add MACD
df.ta.macd(fast=macd_fast, slow=macd_slow, signal=macd_signal, append=True)
# Decision Logic
bbp = df[f"BBP_{bb_length}_{bb_std}"]
bbp = df[f"BBP_{bb_length}_{bb_std}_{bb_std}"]
macdh = df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"]
macd = df[f"MACD_{macd_fast}_{macd_slow}_{macd_signal}"]

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