Create processes.py

processes.py

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+import pandas as pd
+import yfinance as yf
+from datetime import datetime, timedelta
+from data import all_historical_data, df_descargado_ETFs, df_descargado_stocks
+from config import tickers_to_ids
+import plotly.graph_objects as go
+
+#     -----------------------------------------------
+#      Función de Correlación
+#     -----------------------------------------------
+
+def evolucion_correlacion(ticker_company, step, ticker_btc="BTC-USD", window_months=12):
+    """
+    Calcula la evolución de la correlación entre el precio de las acciones de una empresa y Bitcoin.
+    Args:
+        ticker_company (str): El símbolo de cotización de la empresa.
+        step (int): El número de días para el desplazamiento de la correlación.
+        ticker_btc (str): El símbolo de cotización de Bitcoin (por defecto: "BTC-USD").
+        window_months (int): El tamaño de la ventana móvil en meses.
+    outputs:
+        pandas.Series: Una serie con la evolución de la correlación, o None si faltan datos.
+    """
+    end_date = datetime.now()
+    start_date = end_date - timedelta(days=10*365)
+
+    if ticker_company not in all_historical_data:
+        print(f"Descargando datos para {ticker_company}...")
+        data = yf.download(ticker_company, start=start_date, end=end_date)
+        if not data.empty:
+            all_historical_data[ticker_company] = data
+            print(f"Datos de {ticker_company} descargados con éxito.")
+        else:
+            print(f"Error al descargar datos para {ticker_company}.")
+            return None
+
+    if ticker_btc not in all_historical_data:
+        print(f"Descargando datos para {ticker_btc}...")
+        data = yf.download(ticker_btc, start=start_date, end=end_date)
+        if not data.empty:
+            all_historical_data[ticker_btc] = data
+            print(f"Datos de {ticker_btc} descargados con éxito.")
+        else:
+            print(f"Error al descargar datos para {ticker_btc}.")
+            return None
+
+    company_data = all_historical_data.get(ticker_company)
+    btc_data = all_historical_data.get(ticker_btc)
+
+    if company_data.empty or btc_data.empty:
+        print(f"No podemos calcular la correlación dinámica: No hay datos disponibles para {ticker_company} o {ticker_btc}.")
+        return None
+
+    company_prices = company_data['Close']
+    btc_prices = btc_data['Close']
+
+    combined_prices = pd.concat([company_prices, btc_prices], axis=1).dropna()
+    combined_prices.columns = [ticker_company, ticker_btc]
+
+    if combined_prices.empty:
+        print(f"No hay datos históricos en común entre {ticker_company} y {ticker_btc}.")
+        return None
+
+    company_returns = combined_prices[ticker_company].pct_change().dropna()
+    btc_returns = combined_prices[ticker_btc].pct_change().dropna()
+
+    window_days = window_months * 30
+    if step == 0:
+        dynamic_corr = company_returns.rolling(window=f"{window_days}D").corr(btc_returns).iloc[-1]
+        return pd.Series([dynamic_corr], index=[end_date])
+    else:
+        dynamic_corr = company_returns.rolling(window=f"{window_days}D").corr(btc_returns).dropna()
+        return dynamic_corr.iloc[9::step]
+
+
+
+
+#     -----------------------------------------------
+#                PLOT DE LA CORRELACIÓN
+#     -----------------------------------------------
+
+
+
+def plot_evolucion_correlacion_gradio(ticker_company, step, window_months):
+
+    """
+    Genera el gráfico de la evolución de la correlación.
+    """
+    ticker_company = ticker_company.upper()
+    serie = evolucion_correlacion(ticker_company, step, window_months=12)
+
+    if serie is None or serie.empty:
+        return None, f"No hay datos de correlación disponibles para {ticker_company}."
+
+    # --- Create the Plotly graph ---
+    fig = go.Figure()
+
+    # Add the correlation series
+    fig.add_trace(go.Scatter(
+        x=serie.index,
+        y=serie.values,
+        mode='lines',
+        name='Correlación',
+        line=dict(color='#2263eb', width=2), # electric blue color for the line
+        fill='tozeroy', # Fill the area down to Y=0 axis
+        fillcolor='rgba(34,99,235,0.1)', # Very faint elctric blue shadow (10% opacity)
+        hovertemplate='Fecha: %{x|%Y-%m-%d}<br>Correlación: %{y:.4f}<extra></extra>'
+    ))
+
+    # --- Configure axes and range selector ---
+    fig.update_layout(
+        title_text=f'<b>Evolución de la correlación entre {ticker_company} y BTC-USD<b>',
+        title_x=0, # Align title to the left
+        height=500, # Graph height
+        template="plotly_white", # Graph theme (clean and modern)
+        margin=dict(l=20, r=20, t=60, b=20), # Graph margins
+        showlegend=False, # No legend needed if only one main series
+
+        xaxis=go.layout.XAxis(
+            rangeslider=dict(
+                visible=True,
+                thickness=0.08, # Rangeslider thickness
+                bgcolor="rgba(50, 0, 128, 0.1)", # Very transparent purple for rangeslider
+                bordercolor="rgba(50, 0, 128, 0.2)", # Slightly more visible border
+                borderwidth=1,
+                range=[serie.index.min(), serie.index.max()] # Initial slider range
+            ),
+            rangeselector=dict(
+                buttons=list([
+                    dict(count=1, label="1m", step="month", stepmode="backward"),
+                    dict(count=3, label="3m", step="month", stepmode="backward"),
+                    dict(count=6, label="6m", step="month", stepmode="backward"),
+                    dict(step="year", count=1, label="YTD", stepmode="todate"), # YTD
+                    dict(count=1, label="1y", step="year", stepmode="backward"),
+                    dict(step="all", label="All")
+                ]),
+                bgcolor="rgba(247,247,247,255)", # Transparent background for buttons
+                bordercolor="rgba(0,0,0,0)", # Transparent border
+                borderwidth=0,
+                activecolor="rgba(230,233,255,255)", # Active button color (slightly darker purple)
+                font=dict(color="#000000", size=10), # Button font style
+                x=0.9, y=1.1, xanchor='right', yanchor='top' # Button position
+            ),
+            type="date",
+            domain=[0, 1], # Occupy full graph width
+            rangeslider_yaxis_rangemode="auto", # Rangeslider Y-axis range adjusts automatically
+            showgrid=False,
+            gridcolor='#e0e0e0',
+            zeroline=False
+        ),
+        yaxis=go.layout.YAxis(
+            title_text='Correlación',
+            side='left',
+            showgrid=True,
+            gridcolor='#e0e0e0',
+            zeroline=False,
+            tickformat=".2f", # 2 decimal places format
+            range=[-1.0, 1.0] # Fixed range for correlation
+        ),
+        hovermode="x unified", # Unify hover to show data for the series
+        paper_bgcolor='rgba(255,255,255,1)', # Transparent background for notebook integration
+        plot_bgcolor='rgba(255,255,255,1)'
+    )
+
+    # --- Add annotation for max value (similar to Matplotlib) ---
+    max_value = serie.max()
+    max_index = serie.idxmax()
+    fig.add_annotation(
+        x=max_index,
+        y=max_value,
+        text=f'Corr_max: {max_value:.4f}<br>Fecha: {max_index.date()}',
+        showarrow=True,
+        arrowhead=2,
+        ax=0,
+        ay=-40, # Adjust vertical position of the annotation
+        bgcolor="rgba(255, 255, 255, 0.8)", # Semi-transparent white background
+        bordercolor="#c7c7c7",
+        borderwidth=1,
+        borderpad=4,
+        font=dict(size=10, color="#333"),
+        # You can adjust text position with xanchor/yanchor if needed
+    )
+
+    return fig, "Gráfico de correlación generado."
+
+
+
+#     -----------------------------------------------
+#             EXPORTACIÓN DE LA CORRELACIÓN
+#     -----------------------------------------------
+
+
+def exportar_correlacion(ticker_company, step, window_months):
+
+    """
+    Exporta la serie de correlación a un archivo Excel.
+    """
+    try:
+        serie = evolucion_correlacion(ticker_company, step, window_months=window_months)
+        if serie is not None and not serie.empty:
+            nombre_archivo = f'{ticker_company}_evolucion_correlacion.xlsx'
+            serie.to_excel(nombre_archivo)
+            return nombre_archivo, "Archivo Excel generado con éxito."
+        else:
+            return None, "No se pudieron generar los datos para exportar."
+    except Exception as e:
+        return None, f"Error al exportar: {e}"
+
+
+#     -----------------------------------------------
+#          EMBED PLOT STOCK VS BTC DE BTC TREASURY
+#     -----------------------------------------------
+
+
+def get_iframe_stock_vs_btc(ticker):
+    """
+    Genera el código HTML para el iframe de Stock vs Bitcoin.
+    """
+    try:
+        entity_id = tickers_to_ids[ticker]
+        iframe_code = f"""
+            <iframe src="https://bitcointreasuries.net/embed?component=StockVsBitcoinChart&entityId={entity_id}"
+            title="Bitcoin Treasuries" credentialless style="width: 100%; height: 660px; border: none;"></iframe>
+        """
+        return iframe_code
+    except KeyError:
+        return f"No hay datos de holding de Bitcoin para {ticker}."
+
+
+
+#     -----------------------------------------------
+#          EMBED PLOT HOLDING BTC DE BTC TREASURY
+#     -----------------------------------------------
+
+
+def get_iframe_holdings(ticker):
+    """
+    Genera el código HTML para el iframe de Bitcoin Holdings.
+    """
+    try:
+        entity_id = tickers_to_ids[ticker]
+        iframe_code = f"""
+            <iframe src="https://bitcointreasuries.net/embed?component=BitcoinHoldingsChart&entityId={entity_id}"
+            title="Bitcoin Holdings Chart" credentialless style="width: 100%; height: 660px; border: none;"></iframe>
+        """
+        return iframe_code
+    except KeyError:
+        return f"No hay datos de holding de Bitcoin para {ticker}."
+
+
+
+
+#     -----------------------------------------------
+#          TABLAS TOP HOLDING RESUMEN
+#     -----------------------------------------------
+
+
+
+df_descargado_ETFs, df_descargado_stocks = top_holding()
+df_descargado_ETFs = df_descargado_ETFs.reset_index()
+
+# Crear un DataFrame de ejemplo
+top5_ETFs = df_descargado_ETFs.copy().iloc[:,[1,2,3]].head()
+top5_ETFs = pd.DataFrame(top5_ETFs)
+
+top5_stocks = df_descargado_stocks.copy().iloc[:,[0,1,2]].head()
+top5_stocks = pd.DataFrame(top5_stocks)
+
+# Aplicar estilo con color de marca y bordes redondeados
+styled_stocks = top5_stocks.style.set_table_attributes(
+    'style="border-collapse: separate; border-spacing: 0; border-radius: 12px; overflow: hidden;"'
+).set_table_styles([
+    {'selector': 'thead th',
+     'props': [('background-color', '#0085CA'), ('color', 'white'), ('padding', '10px'), ('border', '1px solid #0085CA')]},
+    {'selector': 'td',
+     'props': [('background-color', 'white'), ('color', 'black'), ('padding', '10px'), ('border', '1px solid #0085CA')]},
+    {'selector': 'table',
+     'props': [('border', '2px solid #0085CA'), ('border-radius', '12px'), ('overflow', 'hidden')]}
+])
+
+styled_ETFs = top5_ETFs.style.set_table_attributes(
+    'style="border-collapse: separate; border-spacing: 0; border-radius: 12px; overflow: hidden;"' 
+).set_table_styles([
+    {'selector': 'thead th',
+     'props': [('background-color', '#0085CA'), ('color', 'white'), ('padding', '10px'), ('border', '1px solid #0085CA')]},
+    {'selector': 'td',
+     'props': [('background-color', 'white'), ('color', 'black'), ('padding', '10px'), ('border', '1px solid #0085CA')]},
+    {'selector': 'table',
+     'props': [('border', '2px solid #0085CA'), ('border-radius', '12px'), ('overflow', 'hidden')]}
+])