使用仪表板创建仪表板

时间:2019-12-26 00:55:16

标签: python-3.x pandas plotly-dash

当我运行下面的代码时,program_exe.update_data()函数将执行两次。避免这种情况的最佳方法是什么?该函数执行比较耗时,因此两次运行它并不理想。任何建议将不胜感激!

app = dash.Dash(__name__)
server = app.server

dict_main = program_exe.update_data() #this creates a nested dictionary
rpm = list(dict_main.keys())
channels = dict_main[rpm[0]]

app.layout = html.Div(
    [
        html.Div([
            dcc.Dropdown(
                id='rpm-dropdown',
                options=[{'label': speed, 'value': speed} for speed in rpm],
                value=list(dict_main.keys())[0],
                # I removed the multi=True because it requires a distinction between the columns in the next dropdown...
                searchable=False
            ),
        ], style={'width': '20%', 'display': 'inline-block'}),
        html.Div([
            dcc.Dropdown(
                id='channel-dropdown',
                multi=True
            ),
        ], style={'width': '20%', 'display': 'inline-block'}
        ),
        html.Div([
            dcc.Graph(
                id='Main-Graph'  # the initial graph is in the callback
            ),
        ], style={'width': '98%', 'display': 'inline-block'}
        )
    ]
)


@app.callback(
    Output('channel-dropdown', 'options'),
    [Input('rpm-dropdown', 'value')])
def update_date_dropdown(speed):
    return [{'label': i, 'value': i} for i in dict_main[speed]]


@app.callback(
    Output('Main-Graph', 'figure'),
    [Input('channel-dropdown', 'value')],
    [State('rpm-dropdown', 'value')])  # This is the way to inform the callback which dataframe is to be charted
def updateGraph(channels, speed):
    if channels:
        # return the entire figure with the different traces
        return go.Figure(data=[go.Scatter(x=dict_main[speed]['Manager'], y=dict_main[speed][i]) for i in channels])
    else:
    # at initialization the graph is returned empty
        return go.Figure(data=[])


if __name__ == '__main__':
    app.run_server(debug=True)




1 个答案:

答案 0 :(得分:1)

您可以使用缓存仅一次点击该功能。有关更多详细信息,请参见this page

简短示例:

from flask_caching import Cache
cache = Cache(app.server, config={
    'CACHE_TYPE': 'filesystem',
    'CACHE_DIR': 'cache-directory',
})

@cache.memoize(timeout=6000)
def my_cached_function():
    return program_exe.update_data()

我没有您的func,但是当我在本地使用占位符对其进行测试时,它最初被调用了两次,但是在添加缓存后才被调用一次。