如何正确地为 Dash Web 应用程序执行回调和函数

Question

非常感谢有关如何为我的 Dash 网络应用程序进行正确回调的帮助。我在下面有以下代码。它应该返回一个图表，其中包含有关股票财务状况的各种线条。它从 API 获取数据。但我不确定如何为应用回调定义我的函数。我尝试过遵循在线教程，但取得了任何成功。如果它太混乱或效率低下，我很抱歉，我是新手。

'''

#!/usr/bin/env python
import pandas as pd
import requests
import json
import plotly
import chart_studio.plotly as py
import plotly.graph_objs as go
import plotly.express as px
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input


ticker = input("Insert company ticker: ")
qoy = input("QUARTERLY or YEARLY: ")
if qoy == "Yearly" or qoy == "yearly" or qoy == "YEARLY":
    IS = requests.get("https://financialmodelingprep.com/api/v3/financials/income-statement/" + ticker)
elif qoy == "Quarterly" or qoy == "quarterly" or qoy == "QUARTERLY":
    IS = requests.get(
        "https://financialmodelingprep.com/api/v3/financials/income-statement/" + ticker + "?period=quarter")

IS = IS.json()
IS = IS['financials']
IS = pd.DataFrame.from_dict(IS)
IS = IS.set_index("date")

if qoy == "Yearly" or qoy == "yearly" or qoy == "YEARLY":
    BS = requests.get("https://financialmodelingprep.com/api/v3/financials/balance-sheet-statement/" + ticker)
elif qoy == "Quarterly" or qoy == "quarterly" or qoy == "QUARTERLY":
    BS = requests.get(
        "https://financialmodelingprep.com/api/v3/financials/balance-sheet-statement/" + ticker + "?period=quarter")

BS = BS.json()
BS = BS['financials']
BS = pd.DataFrame.from_dict(BS)
BS = BS.set_index("date")

if qoy == "Yearly" or qoy == "yearly" or qoy == "YEARLY":
    CF = requests.get("https://financialmodelingprep.com/api/v3/financials/cash-flow-statement/" + ticker)
elif qoy == "Quarterly" or qoy == "quarterly" or qoy == "QUARTERLY":
    CF = requests.get(
        "https://financialmodelingprep.com/api/v3/financials/cash-flow-statement/" + ticker + "?period=quarter")

CF = CF.json()
CF = CF['financials']
CF = pd.DataFrame.from_dict(CF)
CF = CF.set_index("date")

df_FS = pd.concat([IS, BS, CF], axis=1, sort=True)
Date = df_FS.index
df_FS.fillna(0, inplace=True)
print(df_FS)

from plotly.subplots import make_subplots

# EARNINGS & REVENUE
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x=Date, y=df_FS['Revenue'],
                         mode='lines+markers',
                         name='Revenue'), secondary_y=False, )
fig.add_trace(go.Bar(x=Date, y=df_FS['Profit Margin'],
                     opacity=0.2,
                     name='Profit Margin'), secondary_y=True, )

fig.add_trace(go.Scatter(x=Date, y=df_FS['Consolidated Income'],
                         mode='lines+markers',
                         name='Earnings'), secondary_y=False, )
fig.add_trace(go.Scatter(x=Date, y=df_FS['Operating Cash Flow'],
                         mode='lines+markers',
                         name='Operating Cash Flow'), secondary_y=False, )
fig.add_trace(go.Scatter(x=Date, y=df_FS['Free Cash Flow'],
                         mode='lines+markers',
                         name='Free Cash Flow'), secondary_y=False, )
fig.add_trace(go.Scatter(x=Date, y=df_FS['Operating Expenses'],
                         mode='lines+markers',
                         name='Operating Expenses'), secondary_y=False, )

fig.update_layout(title="EARNINGS & REVENUE", barmode='group', hovermode='x')
fig.update_yaxes(title_text="in USD", secondary_y=False)
fig.update_yaxes(title_text="Profit Margin", secondary_y=True)
fig.update_xaxes(rangeslider_visible=True)

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([
    # Input the stock ticker
    html.Div([
        dcc.Input(id="stock-input", value=ticker, type="text"),
        dcc.RadioItems(
            id="quarterlyoryearly",
            options=[
                {'label': 'Quarterly', 'value': 'quarterly'},
                {'label': 'Yearly', 'value': 'yearly'}
            ],
            value=qoy
        )
    ]),


    # Banner of app
    html.Div([
        html.H2("Stock App")
    ], className="banner"),

    # Graphs
    html.Div([

        # Earnings & Revenue Graph
        html.Div([
            dcc.Graph(
                id="Earnings & Revenue",
                figure=fig
            )
        ], className="six columns"),
    ], className="row")

])

app.css.append_css({"external_url": "https://codepen.io/chriddyp/pen/bWLwgP.css"})


@app.callback(dash.dependencies.Output("Earnings & Revenue","figure"),
              [dash.dependencies.Input("stock-input","value"),
               dash.dependencies.Input("quarterlyoryearly","value")]
              )


#def update_fig(ticker,qoy):


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

'''

Answer 1

您必须在回调中执行所有数据处理，因为它们需要输入和按钮值。根据您希望应用程序如何响应输入，有多种方法可以解决此问题。一种方法是这样。这里，主要输入是qoy，回调使用stock input 的状态。因此，在您选择qoy 之前，输入股票输入不会更新应用程序。

#!/usr/bin/env python
from plotly.subplots import make_subplots
import pandas as pd
import requests
import json
import plotly
import chart_studio.plotly as py
import plotly.graph_objs as go
import plotly.express as px
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input, State
from dash.exceptions import PreventUpdate

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([
    # Input the stock ticker
    html.Div([
        dcc.Input(id="stock-input",
                  placeholder='Please insert stock', type="text"),
        dcc.RadioItems(
            id="quarterlyoryearly",
            options=[
                {'label': 'Quarterly', 'value': 'quarterly'},
                {'label': 'Yearly', 'value': 'yearly'}
            ]
        )
    ]),


    # Banner of app
    html.Div([
        html.H2("Stock App")
    ], className="banner"),

    # Graphs
    html.Div([

        # Earnings & Revenue Graph
        html.Div([
            dcc.Graph(
                id="Earnings & Revenue",
                # figure=fig
            )
        ], className="six columns"),
    ], className="row")

])

@app.callback(Output("quarterlyoryearly", "value"),
              [Input("stock-input", "n_submit")],
              [State("quarterlyoryearly", "value")])
def enter_key(n_sub, qoy):
    if n_sub:
        return qoy

@app.callback(dash.dependencies.Output("Earnings & Revenue", "figure"),
              [dash.dependencies.Input("quarterlyoryearly", "value")],
              [dash.dependencies.State("stock-input", "value")]
              )
def update_fig(*args):

    if not any(args):
        raise PreventUpdate
    else:
        qoy, ticker = args

        if qoy.lower() == "yearly":
            IS = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/income-statement/" + ticker)
        elif qoy.lower() == "quarterly":
            IS = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/income-statement/" + ticker + "?period=quarter")

        IS = IS.json()
        IS = IS['financials']
        IS = pd.DataFrame.from_dict(IS)
        IS = IS.set_index("date")

        if qoy == "Yearly" or qoy == "yearly" or qoy == "YEARLY":
            BS = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/balance-sheet-statement/" + ticker)
        elif qoy == "Quarterly" or qoy == "quarterly" or qoy == "QUARTERLY":
            BS = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/balance-sheet-statement/" + ticker + "?period=quarter")

        BS = BS.json()
        BS = BS['financials']
        BS = pd.DataFrame.from_dict(BS)
        BS = BS.set_index("date")

        if qoy == "Yearly" or qoy == "yearly" or qoy == "YEARLY":
            CF = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/cash-flow-statement/" + ticker)
        elif qoy == "Quarterly" or qoy == "quarterly" or qoy == "QUARTERLY":
            CF = requests.get(
                "https://financialmodelingprep.com/api/v3/financials/cash-flow-statement/" + ticker + "?period=quarter")

        CF = CF.json()
        CF = CF['financials']
        CF = pd.DataFrame.from_dict(CF)
        CF = CF.set_index("date")

        df_FS = pd.concat([IS, BS, CF], axis=1, sort=True)
        Date = df_FS.index
        df_FS.fillna(0, inplace=True)

        # EARNINGS & REVENUE
        fig = make_subplots(specs=[[{"secondary_y": True}]])
        fig.add_trace(go.Scatter(x=Date, y=df_FS['Revenue'],
                                 mode='lines+markers',
                                 name='Revenue'), secondary_y=False, )
        fig.add_trace(go.Bar(x=Date, y=df_FS['Profit Margin'],
                             opacity=0.2,
                             name='Profit Margin'), secondary_y=True, )

        fig.add_trace(go.Scatter(x=Date, y=df_FS['Consolidated Income'],
                                 mode='lines+markers',
                                 name='Earnings'), secondary_y=False, )
        fig.add_trace(go.Scatter(x=Date, y=df_FS['Operating Cash Flow'],
                                 mode='lines+markers',
                                 name='Operating Cash Flow'), secondary_y=False, )
        fig.add_trace(go.Scatter(x=Date, y=df_FS['Free Cash Flow'],
                                 mode='lines+markers',
                                 name='Free Cash Flow'), secondary_y=False, )
        fig.add_trace(go.Scatter(x=Date, y=df_FS['Operating Expenses'],
                                 mode='lines+markers',
                                 name='Operating Expenses'), secondary_y=False, )

        fig.update_layout(title="EARNINGS & REVENUE",
                          barmode='group', hovermode='x')
        fig.update_yaxes(title_text="in USD", secondary_y=False)
        fig.update_yaxes(title_text="Profit Margin", secondary_y=True)
        fig.update_xaxes(rangeslider_visible=True)
        return fig


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

您可以玩转输入和状态选项，看看应用如何响应。干杯！

PS：我添加了另一个回调，所以在第一个 qoy 和 ticker 值之后，您可以简单地在输入字段中更改 ticker 并点击回车按钮 （因为 qoy 已经已选择） 以更新您的应用。希望这能让您更深入地了解回调的工作原理。