Refresh theme palette and translate SMA notice

.dockerignore

@@ -0,0 +1,8 @@
+__pycache__/
+*/__pycache__/*
+.venv/
+venv/
+.git/
+.github/
+.streamlit/cache/
+data/*

.streamlit/config.toml

@@ -4,4 +4,3 @@ primaryColor = "#F97316"
 backgroundColor = "#0F1115"
 secondaryBackgroundColor = "#1A1D23"
 textColor = "#E5E7EB"
-font = "sans serif"

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+ENV PIP_NO_CACHE_DIR=1
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 8501
+
+CMD ["streamlit", "run", "streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

README.md

@@ -51,3 +51,12 @@ source .venv/bin/activate
 python -m pip install --upgrade pip
 pip install -r requirements.txt
 python -m streamlit run streamlit_app.py
+
+### Ejecutar con Docker
+```bash
+# Construir la imagen
+docker build -t quantboard .
+
+# Ejecutar el contenedor (Streamlit en http://localhost:8501)
+docker run -p 8501:8501 quantboard
+```

pages/02_SMA_Heatmap.py

@@ -65,21 +65,27 @@ def main() -> None:
             ticker = st.text_input("Ticker", value=ticker_default).strip().upper()
             end = st.date_input("To", value=end_default)
             start = st.date_input("From", value=start_default)
-            fast_min, fast_max = st.slider("Fast SMA range", 5, 60, (fast_min_default, fast_max_default))
-            slow_min, slow_max = st.slider("Slow SMA range", 20, 240, (slow_min_default, slow_max_default))
+            fast_min, fast_max = st.slider(
+                "Fast SMA range", 5, 60, (fast_min_default, fast_max_default)
+            )
+            slow_min, slow_max = st.slider(
+                "Slow SMA range", 20, 240, (slow_min_default, slow_max_default)
+            )
             submitted = st.form_submit_button("Run search", type="primary")
 
-    if not submitted:
-        st.info("Choose parameters and click **Run search**.")
-        return
+        # If the form was not submitted, show a hint and exit early
+        if not submitted:
+            st.info("Choose parameters and click **Run search**.")
+            return
 
-    set_param("ticker", ticker or None)
-    set_param("heat_end", end)
-    set_param("heat_start", start)
-    set_param("heat_fast_min", int(fast_min))
-    set_param("heat_fast_max", int(fast_max))
-    set_param("heat_slow_min", int(slow_min))
-    set_param("heat_slow_max", int(slow_max))
+        # Persist parameters for sharable links / reload
+        set_param("ticker", ticker or None)
+        set_param("heat_end", end)
+        set_param("heat_start", start)
+        set_param("heat_fast_min", int(fast_min))
+        set_param("heat_fast_max", int(fast_max))
+        set_param("heat_slow_min", int(slow_min))
+        set_param("heat_slow_max", int(slow_max))
 
     if fast_min >= slow_min:
         st.error("Fast SMA range must stay below the Slow SMA range.")
@@ -107,7 +113,10 @@ def main() -> None:
                 z.loc[fast_window, slow_window] = float("nan")
 
     st.subheader("Heatmap (Sharpe)")
-    st.plotly_chart(heatmap_metric(z, title="SMA grid — Sharpe"), use_container_width=True)
+    st.plotly_chart(
+        heatmap_metric(z, title="SMA grid — Sharpe"),
+        use_container_width=True,
+    )
 
     stacked = z.stack().dropna().astype(float)
     if stacked.empty:

pages/03_Backtest.py

@@ -105,6 +105,31 @@ def _run_signals(close: pd.Series, fast: int, slow: int) -> pd.Series:
     return sig.replace(0, pd.NA).ffill().fillna(0.0)
 
 
+def _clean_prices(df: pd.DataFrame) -> pd.DataFrame | None:
+    price_cols = ["open", "high", "low", "close", "volume"]
+    numeric = {col: pd.to_numeric(df.get(col), errors="coerce") for col in price_cols if col in df}
+    clean = df.assign(**numeric).dropna(subset=["close"])
+    if clean.empty:
+        st.error("No price data available after cleaning.")
+        return None
+    return clean
+
+
+def _run_signals(close: pd.Series, fast: int, slow: int) -> pd.Series:
+    if signals_sma_crossover is not None:
+        sig, _ = signals_sma_crossover(close, fast=fast, slow=slow)
+        return sig
+
+    sma_fast = sma(close, fast)
+    sma_slow = sma(close, slow)
+    cross_up = (sma_fast > sma_slow) & (sma_fast.shift(1) <= sma_slow.shift(1))
+    cross_dn = (sma_fast < sma_slow) & (sma_fast.shift(1) >= sma_slow.shift(1))
+    sig = pd.Series(0.0, index=close.index)
+    sig = sig.where(~cross_up, 1.0)
+    sig = sig.where(~cross_dn, -1.0)
+    return sig.replace(0, pd.NA).ffill().fillna(0.0)
+
+
 def main() -> None:
     st.title("Backtest — SMA crossover")
 
@@ -142,12 +167,7 @@ def main() -> None:
             fee_bps = st.number_input("Fees (bps)", 0, 50, int(fee_default), step=1)
             slip_bps = st.number_input("Slippage (bps)", 0, 50, int(slip_default), step=1)
             submitted = st.form_submit_button("Run backtest", type="primary")
-
-    st.info("Configure the sidebar parameters and run the backtest.")
-
-    if not submitted:
-        return
-
+
     set_param("ticker", ticker or None)
     set_param("bt_end", end)
     set_param("bt_start", start)
@@ -157,6 +177,18 @@ def main() -> None:
     set_param("fee_bps", int(fee_bps))
     set_param("slippage_bps", int(slip_bps))
 
+    st.info("Configure the sidebar parameters and run the backtest.")
+
+    if not submitted:
+        return
+
+    if fast >= slow:
+        st.error("Fast SMA must be smaller than Slow SMA.")
+        return
+
+    with st.spinner("Fetching data..."):
+        df = _load_prices(ticker, start=start, end=end)
+
     if fast >= slow:
         st.error("Fast SMA must be smaller than Slow SMA.")
         return

pages/2_Optimizacion_SMA.py

@@ -7,5 +7,7 @@
 
 shareable_link_button()
 
-st.info("Esta página fue reemplazada por **SMA Heatmap**. Usá el ítem *SMA Heatmap* del menú para optimizar parámetros.")
-
+st.info(
+    "This page was replaced by **SMA Heatmap**. "
+    "Use the *SMA Heatmap* menu item to optimize parameters."
+)