1a version de comidas en glucometro

comidas.py

+# Import packages
+from dash import Dash, html, dcc, callback, Output, Input 
+import pandas as pd
+import numpy as np
+import plotly.express as px
+import plotly.graph_objects as go
+from nutri_utils import readGlucosa
+from nutri_utils import readPacientes
+from nutri_utils import readVisitas
+from nutri_utils import readFoods, consolidateFoods, aislaFoods
+
+
+app = Dash(__name__)
+
+patients = pd.DataFrame(readPacientes())
+
+app.layout = [
+    html.Div(children='Glucosa de los Pacientes'),
+    dcc.Graph(id = 'glucosa-graph'),
+    dcc.Slider(min=30, max = 216, step=1, marks={i: str(i) for i in range(30,217,18)}, value = 30, tooltip= {'always_visible': True} , updatemode = 'drag',
+               id = 'slider-patient')
+]
+
+@callback(
+    Output('glucosa-graph', 'figure'),
+    Input('slider-patient', 'value'))
+def update_graph(selected_pat):
+    glucosa = readGlucosa(selected_pat)
+    visita = readVisitas(1)
+    foods = aislaFoods(consolidateFoods(readFoods(selected_pat)))
+    y_interp = np.interp(foods['fecha_hora'], glucosa['date_time'], glucosa['value'])
+    fecha_visita1 =  pd.to_datetime(visita.loc[visita['id'] == selected_pat, 'visit_date'].iloc[0])
+    filtered_glucosa = glucosa[(glucosa['date_time'] >= fecha_visita1) & (glucosa['date_time'] <= fecha_visita1 + pd.Timedelta(days=15))]
+    
+    fig = px.line(filtered_glucosa, x='date_time', y='value', labels={'date_time':'Fecha y Hora','value': 'Valor de Glucosa'})
+    fig.add_trace(go.Scatter(x=foods['fecha_hora'], y=y_interp, mode='markers', marker=dict(color='red', size=8)))
+    fig.update_layout(transition_duration=500)
+
+    return fig
+
+if __name__ == '__main__':
+    app.run(debug=True)