#python-3.x #amazon-web-services #drop-down-menu #amazon-elastic-beanstalk #plotly-dash
#python-3.x #amazon-веб-сервисы #выпадающее меню #amazon-elastic-beanstalk #сюжет-dash
Вопрос:
Я создал два отдельных веб-приложения dash и объединил их в одно, создав вкладки. Я могу легко увидеть визуализацию на локальном хосте, но столкнулся с проблемой при загрузке кода. Вторая вкладка состоит из выпадающих меню. После загрузки кода на AWS выпадающее меню не отображается.
Вот код.
app.layout = html.Div([
html.H1('Smoothie Fixed Benefit Prices'),
html.P("These prices are common for all routes in India."),
html.P("Peak months are:-Jan,June, July, August, November, December."),
html.P("Peak Hours ( During Peak Months ):-9 A.M. to Midnight"),
html.P("Peak Hours ( During Non Peak Months ):-12 P.M. - 12 A.M."),
html.H3('Select Airline'),
dcc.Dropdown(
id='datasource-1',
options=[
{'label': i, 'value': i} for i in ['Low Delay Airlines (6E, UK)','High Delay Airlines (9W,AI,SG,G8)']
],
),
html.H3('Select Peak/Non-Peak Month'),
dcc.Dropdown(
id='datasource-2',
options=[
{'label': i, 'value': i} for i in ['Peak Month','Non Peak Month']
]
),
html.Hr(),
html.Div('Select Peak/Non Peak Hour and Threshold Delay'),
html.Div(
id='controls-container'
),
html.Hr(),
html.Div('Output'),
html.Div(
id='output-container'
)
])
def generate_control_id(value):
return 'Control {}'.format(value)
DYNAMIC_CONTROLS = {
'Low Delay Airlines (6E, UK)': dcc.Dropdown(
id=generate_control_id('Low Delay Airlines (6E, UK)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='Low Delay Airlines (6E, UK)'].unique())]
),
'High Delay Airlines (9W,AI,SG,G8)': dcc.Dropdown(
id=generate_control_id('High Delay Airlines (9W,AI,SG,G8)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='High Delay Airlines (9W,AI,SG,G8)'].unique())]
),
'Peak Month': dcc.Dropdown(
id=generate_control_id('Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
),
'Non Peak Month': dcc.Dropdown(
id=generate_control_id('Non Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
)
}
@app.callback(
Output('controls-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# generate 2 dynamic controls based off of the datasource selections
return html.Div([
DYNAMIC_CONTROLS[datasource_1_value],
DYNAMIC_CONTROLS[datasource_2_value],
])
def generate_output_id(value1, value2):
return '{} {} container'.format(value1, value2)
@app.callback(
Output('output-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# create a unique output container for each pair of dyanmic controls
return html.Div(id=generate_output_id(
datasource_1_value,
datasource_2_value
))
def prem(a,b,c,d):
return (price['Office Premium ( INR )'][(price['Hour Peaks']==a)amp;(price['Threshold Delay ( Min )']==b)amp;(price['Airlines']==c)amp;(price['Month Peaks']==d)])
def incidence(a,b,c,d):
return (price['Incidence Rate (%)'][(price['Hour Peaks']==a)amp;(price['Threshold Delay ( Min )']==b)amp;(price['Airlines']==c)amp;(price['Month Peaks']==d)])
def generate_output_callback(datasource_1_value, datasource_2_value):
def output_callback(control_1_value, control_2_value):
# This function can display different outputs depending on
# the values of the dynamic controls
premium=prem(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
incidence_rate=incidence(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
return '''
For the selected values, premium in INR is {} and incidence rate is {} %
'''.format(
list(premium)[0],
list(incidence_rate)[0]
)
return output_callback
app.config.supress_callback_exceptions = True
# create a callback for all possible combinations of dynamic controls
# each unique dynamic control pairing is linked to a dynamic output component
for value1, value2 in itertools.product(
[o['value'] for o in app.layout['datasource-1'].options],
[o['value'] for o in app.layout['datasource-2'].options]):
app.callback(
Output(generate_output_id(value1, value2), 'children'),
[Input(generate_control_id(value1), 'value'),
Input(generate_control_id(value2), 'value')])(
generate_output_callback(value1, value2)
)
Код для обоих приложений вместе
server = Flask(__name__)
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
application = app.server
available_indicators = df['Indicator Name'].unique()
app.layout = html.Div([
dcc.Tabs(id="tabs", children=[
dcc.Tab(label='Delay Comparison', children=[
html.Div([
html.H3('Flight Delays'),
html.H3('Comparison of delay over different routes and different months'),
html.Div([
dcc.Dropdown(
id='crossfilter-xaxis-column',
options=[{'label': i, 'value': i} for i in available_indicators],
value='6E'
),
dcc.RadioItems(
id='crossfilter-xaxis-type',
options=[{'label': i, 'value': i} for i in ['Linear']],
value='Linear',
labelStyle={'display': 'inline-block'}
)
],
style={'width': '49%', 'display': 'inline-block'}),
html.Div([
dcc.Dropdown(
id='crossfilter-yaxis-column',
options=[{'label': i, 'value': i} for i in available_indicators],
value='6E'
),
dcc.RadioItems(
id='crossfilter-yaxis-type',
options=[{'label': i, 'value': i} for i in ['Linear']],
value='Linear',
labelStyle={'display': 'inline-block'}
)
], style={'width': '49%', 'float': 'right', 'display': 'inline-block'})
], style={
'borderBottom': 'thin lightgrey solid',
'backgroundColor': 'rgb(250, 250, 250)',
'padding': '10px 5px'
}),
html.Div([
dcc.Graph(
id='crossfilter-indicator-scatter',
hoverData={'points': [{'customdata': 'MUM-DEL'}]}
)
], style={'width': '49%', 'display': 'inline-block', 'padding': '0 20'}),
html.Div([
dcc.Graph(id='x-time-series'),
dcc.Graph(id='y-time-series'),
], style={'display': 'inline-block', 'width': '49%'}),
html.Div(dcc.Slider(
id='crossfilter-year--slider',
min=df['Year'].min(),
max=df['Year'].max(),
value=df['Year'].max(),
marks={str(year): str(year) for year in df['Year'].unique()}
), style={'width': '49%', 'padding': '0px 20px 20px 20px'}),
html.Div([html.H6('Months',style={'width': '49%', 'padding': '0px 20px 20px 285px','fontColor':'#7ad5f9'})],style={'fontColor': 'blue'})
]),
dcc.Tab(label='Pricing', children=[
html.H3('Smoothie Fixed Benefit Prices'),
html.P("These prices are common for all routes in India."),
html.P("Peak months are:-Jan,June, July, August, November, December."),
html.P("Peak Hours ( During Peak Months ):-9 A.M. to Midnight"),
html.P("Peak Hours ( During Non Peak Months ):-12 P.M. - 12 A.M."),
html.H3('Select Airline'),
dcc.Dropdown(
id='datasource-1',
options=[
{'label': i, 'value': i} for i in ['Low Delay Airlines (6E, UK)','High Delay Airlines (9W,AI,SG,G8)']
],
),
html.H3('Select Peak/Non-Peak Month'),
dcc.Dropdown(
id='datasource-2',
options=[
{'label': i, 'value': i} for i in ['Peak Month','Non Peak Month']
]
),
html.Hr(),
html.Div('Select Peak/Non Peak Hour and Threshold Delay'),
html.Div(
id='controls-container'
),
html.Hr(),
html.Div('Output'),
html.Div(
id='output-container'
)
])
])
])
@app.callback(
dash.dependencies.Output('crossfilter-indicator-scatter', 'figure'),
[dash.dependencies.Input('crossfilter-xaxis-column', 'value'),
dash.dependencies.Input('crossfilter-yaxis-column', 'value'),
dash.dependencies.Input('crossfilter-xaxis-type', 'value'),
dash.dependencies.Input('crossfilter-yaxis-type', 'value'),
dash.dependencies.Input('crossfilter-year--slider', 'value')])
def update_graph(xaxis_column_name, yaxis_column_name,
xaxis_type, yaxis_type,
year_value):
dff = df[df['Year'] == year_value]
return {
'data': [go.Scatter(
x=dff[dff['Indicator Name'] == xaxis_column_name]['Value'],
y=dff[dff['Indicator Name'] == yaxis_column_name]['Value'],
text=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'],
customdata=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'],
mode='markers',
marker={
'size': 15,
'opacity': 0.5,
'line': {'width': 0.5, 'color': 'white'}
}
)],
'layout': go.Layout(
title = 'Comparison of Airline Delay over Different Routes in India',
xaxis={
'title': 'First Airline Delay in Minutes',
'type': 'linear' if xaxis_type == 'Linear' else 'log'
},
yaxis={
'title': 'Second Airline Delay in Minutes',
'type': 'linear' if yaxis_type == 'Linear' else 'log'
},
margin={'l': 40, 'b': 30, 't': 30, 'r': 30},
height=450,
hovermode='closest'
)
}
def create_time_series(dff, axis_type, title):
return {
'data': [go.Scatter(
x=dff['Year'],
y=dff['Value'],
mode='lines markers'
)],
'layout': {
'height': 225,
'margin': {'l': 35, 'b': 30, 'r': 10, 't': 10},
'annotations': [{
'x': 0, 'y': 0.85, 'xanchor': 'left', 'yanchor': 'bottom',
'xref': 'paper', 'yref': 'paper', 'showarrow': False,
'align': 'left', 'bgcolor': 'rgba(255, 255, 255, 0.5)',
'text': title
}],
'yaxis': {'type': 'linear' if axis_type == 'Linear' else 'log','title':'Average Delay in Minutes'},
'xaxis': {'showgrid': False,'title':'Months'}
}
}
@app.callback(
dash.dependencies.Output('x-time-series', 'figure'),
[dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'),
dash.dependencies.Input('crossfilter-xaxis-column', 'value'),
dash.dependencies.Input('crossfilter-xaxis-type', 'value')])
def update_y_timeseries(hoverData, xaxis_column_name, axis_type):
country_name = hoverData['points'][0]['customdata']
dff = df[df['Country Name'] == country_name]
dff = dff[dff['Indicator Name'] == xaxis_column_name]
title = '<b>{}</b><br>{}'.format(country_name, xaxis_column_name)
return create_time_series(dff, axis_type, title)
@app.callback(
dash.dependencies.Output('y-time-series', 'figure'),
[dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'),
dash.dependencies.Input('crossfilter-yaxis-column', 'value'),
dash.dependencies.Input('crossfilter-yaxis-type', 'value')])
def update_x_timeseries(hoverData, yaxis_column_name, axis_type):
dff = df[df['Country Name'] == hoverData['points'][0]['customdata']]
dff = dff[dff['Indicator Name'] == yaxis_column_name]
return create_time_series(dff, axis_type, yaxis_column_name)
def generate_control_id(value):
return 'Control {}'.format(value)
DYNAMIC_CONTROLS = {
'Low Delay Airlines (6E, UK)': dcc.Dropdown(
id=generate_control_id('Low Delay Airlines (6E, UK)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='Low Delay Airlines (6E, UK)'].unique())]
),
'High Delay Airlines (9W,AI,SG,G8)': dcc.Dropdown(
id=generate_control_id('High Delay Airlines (9W,AI,SG,G8)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='High Delay Airlines (9W,AI,SG,G8)'].unique())]
),
'Peak Month': dcc.Dropdown(
id=generate_control_id('Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
),
'Non Peak Month': dcc.Dropdown(
id=generate_control_id('Non Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
)
}
@app.callback(
Output('controls-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# generate 2 dynamic controls based off of the datasource selections
return html.Div([
DYNAMIC_CONTROLS[datasource_1_value],
DYNAMIC_CONTROLS[datasource_2_value],
])
def generate_output_id(value1, value2):
return '{} {} container'.format(value1, value2)
@app.callback(
Output('output-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# create a unique output container for each pair of dyanmic controls
return html.Div(id=generate_output_id(
datasource_1_value,
datasource_2_value
))
def prem(a,b,c,d):
return (price['Office Premium ( INR )'][(price['Hour Peaks']==a)amp;(price['Threshold Delay ( Min )']==b)amp;(price['Airlines']==c)amp;(price['Month Peaks']==d)])
def incidence(a,b,c,d):
return (price['Incidence Rate (%)'][(price['Hour Peaks']==a)amp;(price['Threshold Delay ( Min )']==b)amp;(price['Airlines']==c)amp;(price['Month Peaks']==d)])
def generate_output_callback(datasource_1_value, datasource_2_value):
def output_callback(control_1_value, control_2_value):
# This function can display different outputs depending on
# the values of the dynamic controls
premium=prem(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
incidence_rate=incidence(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
return '''
For the selected values, premium in INR is {} and incidence rate is {} %
'''.format(
list(premium)[0],
list(incidence_rate)[0]
)
return output_callback
app.config.supress_callback_exceptions = True
# create a callback for all possible combinations of dynamic controls
# each unique dynamic control pairing is linked to a dynamic output component
for value1, value2 in itertools.product(
[o['value'] for o in app.layout['datasource-1'].options],
[o['value'] for o in app.layout['datasource-2'].options]):
app.callback(
Output(generate_output_id(value1, value2), 'children'),
[Input(generate_control_id(value1), 'value'),
Input(generate_control_id(value2), 'value')])(
generate_output_callback(value1, value2)
)
if __name__ == '__main__':
application.run(debug = False,port=8080)
Комментарии:
1. У меня похожая проблема. Вы когда-нибудь решали эту проблему @PrateekSingh?