Support more timeframes in charts

src/datasource.py

@@ -53,10 +53,25 @@ def get_client():
     return StockHistoricalDataClient(ALPACA_API_KEY, ALPACA_SECRET_KEY)
 
 
-def get_stock_bars(symbol_or_symbols, date_start, date_end, interval=1):
+def parse_timeframe(timeframe_str):
+    """Parse timeframe string and return TimeFrame object"""
+    timeframe_mapping = {
+        "1m": TimeFrame(amount=1, unit=TimeFrameUnit.Minute),
+        "5m": TimeFrame(amount=5, unit=TimeFrameUnit.Minute),
+        "15m": TimeFrame(amount=15, unit=TimeFrameUnit.Minute),
+        "30m": TimeFrame(amount=30, unit=TimeFrameUnit.Minute),
+        "1h": TimeFrame(amount=1, unit=TimeFrameUnit.Hour),
+        "1d": TimeFrame(amount=1, unit=TimeFrameUnit.Day),
+    }
+    return timeframe_mapping.get(
+        timeframe_str, TimeFrame(amount=1, unit=TimeFrameUnit.Minute)
+    )
+
+
+def get_stock_bars(symbol_or_symbols, date_start, date_end, interval="1min"):
     req = StockBarsRequest(
         symbol_or_symbols=symbol_or_symbols,
-        timeframe=TimeFrame(amount=interval, unit=TimeFrameUnit.Minute),
+        timeframe=parse_timeframe(interval),
         start=str(date_start),
         end=str(date_end),
     )

src/pages/chart.py

@@ -1,11 +1,17 @@
 from datetime import datetime, timedelta
-
 import pandas as pd
 import plotly.graph_objs as go
 import streamlit as st
+import pytz
 
 from datasource import get_stock_bars
 
+
+def get_ny_today():
+    ny_tz = pytz.timezone("America/New_York")
+    return datetime.now(ny_tz).date()
+
+
 st.set_page_config(layout="wide")
 st.title("Candlestick Chart")
 st.sidebar.title("Filters")
@@ -13,14 +19,23 @@ st.sidebar.title("Filters")
 symbol = st.sidebar.text_input("Ticker symbol", value="TSLA").upper()
 date_start = st.sidebar.date_input(
     "Start date",
-    datetime.today() - timedelta(days=1),
-    max_value=datetime.today() - timedelta(days=1),
+    get_ny_today() - timedelta(days=1),
+    max_value=get_ny_today() - timedelta(days=1),
+)
+timeframe = st.sidebar.selectbox(
+    "Timeframe", options=["1m", "5m", "15m", "30m", "1h", "1d"], index=2
 )
-timeframe = st.sidebar.selectbox("Timeframe", options=["1", "5", "15"], index=2)
 
 try:
+    if timeframe == "1d":
+        actual_start_date = date_start - timedelta(days=29)  # 29 + 1 = 30 days total
+        actual_end_date = date_start + timedelta(days=1)
+    else:
+        actual_start_date = date_start
+        actual_end_date = date_start + timedelta(days=1)
+
     bars = get_stock_bars(
-        symbol, date_start, date_start + timedelta(days=1), interval=int(timeframe)
+        symbol, actual_start_date, actual_end_date, interval=timeframe
     )
     if bars.empty:
         st.warning("No data. Check symbol and dates.")
@@ -35,10 +50,13 @@ try:
             "volume"
         ].cumsum()
 
-        premarket_mask = bars.index.time < pd.to_datetime("09:30:00").time()
-        premarket_high = (
-            bars.loc[premarket_mask, "high"].max() if premarket_mask.any() else None
-        )
+        if timeframe != "1d":
+            premarket_mask = bars.index.time < pd.to_datetime("09:30:00").time()
+            premarket_high = (
+                bars.loc[premarket_mask, "high"].max() if premarket_mask.any() else None
+            )
+        else:
+            premarket_high = None
 
         timestamps = [ts.strftime("%Y-%m-%d %H:%M:%S") for ts in bars.index]
         open_vals = bars["open"].tolist()
@@ -71,7 +89,7 @@ try:
         if premarket_high is not None and pd.notna(premarket_high):
             fig.add_trace(
                 go.Scatter(
-                    x=[timestamps[0], timestamps[-1]],
+                    x=[timestamps, timestamps[-1]],
                     y=[premarket_high, premarket_high],
                     mode="lines",
                     line=dict(color="red", width=1, dash="dash"),
@@ -89,30 +107,36 @@ try:
             )
         )
 
-        bars_dates = pd.to_datetime(bars.index.date).unique()
-        for day in bars_dates:
-            dm = pd.Timestamp(day).strftime("%Y-%m-%d")
-            fig.add_vrect(
-                x0=f"{dm} 04:00:00",
-                x1=f"{dm} 09:30:00",
-                fillcolor="rgba(0, 200, 255, 0.10)",
-                layer="below",
-                line_width=0,
-                annotation_text="Pre-market",
-                annotation_position="top left",
-            )
-            fig.add_vrect(
-                x0=f"{dm} 16:00:00",
-                x1=f"{dm} 20:00:00",
-                fillcolor="rgba(255, 200, 0, 0.08)",
-                layer="below",
-                line_width=0,
-                annotation_text="After-hours",
-                annotation_position="top left",
-            )
+        if timeframe != "1d":
+            bars_dates = pd.to_datetime(bars.index.date).unique()
+            for day in bars_dates:
+                dm = pd.Timestamp(day).strftime("%Y-%m-%d")
+                fig.add_vrect(
+                    x0=f"{dm} 04:00:00",
+                    x1=f"{dm} 09:30:00",
+                    fillcolor="rgba(0, 200, 255, 0.10)",
+                    layer="below",
+                    line_width=0,
+                    annotation_text="Pre-market",
+                    annotation_position="top left",
+                )
+                fig.add_vrect(
+                    x0=f"{dm} 16:00:00",
+                    x1=f"{dm} 20:00:00",
+                    fillcolor="rgba(255, 200, 0, 0.08)",
+                    layer="below",
+                    line_width=0,
+                    annotation_text="After-hours",
+                    annotation_position="top left",
+                )
+
+        if timeframe == "1d":
+            title = f"{symbol} - {timeframe} ({actual_start_date.strftime('%Y-%m-%d')} to {date_start.strftime('%Y-%m-%d')})"
+        else:
+            title = f"{symbol} - {timeframe}"
 
         fig.update_layout(
-            title=f"{symbol} - {timeframe}m",
+            title=title,
             xaxis_title="Date/Time",
             yaxis_title="Price",
             xaxis_rangeslider_visible=False,