backendfastapi / chart_builder.py
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# chart_builder.py
import plotly.graph_objs as go
import pandas as pd
def build_chart(df, indicators=None):
"""
Build OHLC chart with volume and optional indicators.
df : DataFrame with 'Open','High','Low','Close','Volume'
indicators : dict {name: Series or DataFrame} from indicater.py
"""
if indicators is None:
indicators = {}
fig = go.Figure()
# --- Main OHLC Candlestick chart ---
fig.add_trace(go.Candlestick(
x=df.index,
open=df['Open'],
high=df['High'],
low=df['Low'],
close=df['Close'],
name='Price'
))
# --- Overlay indicators on main chart (SMA, EMA) ---
overlay_indicators = ['SMA5','SMA20','SMA50','SMA200','EMA5','EMA20','EMA50','EMA200']
for ind in overlay_indicators:
if ind in indicators:
fig.add_trace(go.Scatter(
x=df.index,
y=indicators[ind],
mode='lines',
name=ind,
visible='legendonly' # default off, toggle via legend
))
# --- Volume subplot ---
fig.add_trace(go.Bar(
x=df.index,
y=df['Volume'],
name='Volume',
marker_color='lightblue',
yaxis='y2'
))
# --- Subplot indicators (MACD, RSI, SuperTrend, etc.) ---
subplots = ['MACD','MACD_signal','MACD_hist','RSI','STOCH','ADX','CCI','OBV','SuperTrend']
for ind in subplots:
if ind in indicators:
fig.add_trace(go.Scatter(
x=df.index,
y=indicators[ind],
mode='lines',
name=ind,
visible='legendonly',
yaxis='y3'
))
# --- Layout ---
fig.update_layout(
xaxis=dict(domain=[0,1]),
yaxis=dict(title='Price'),
yaxis2=dict(title='Volume', overlaying='y', side='right', showgrid=False, position=0.15),
yaxis3=dict(title='Indicators', anchor='free', overlaying='y', side='right', position=0.85),
legend=dict(orientation='h', y=-0.2),
margin=dict(l=50, r=50, t=50, b=100),
height=700,
template='plotly_white'
)
# --- Add HTML + JS for toggle (legend already allows visibility control) ---
chart_html = fig.to_html(full_html=False, include_plotlyjs='cdn')
# Add optional instructions
instructions = """
<div style="margin:10px 0;color:#555;">
<b>Instructions:</b> Click legend items to enable/disable indicators and overlays.
</div>
"""
return instructions + chart_html