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 Web 应用程序进行正确回调的一些帮助。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，我深表歉意，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)

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。有多种方法可以解决此问题，具体取决于您希望应用程序如何响应输入。一种方法是这样。在这里，主要输入是qoy，回调使用stock input. 因此，在您选择 之前，输入股票输入不会更新应用程序qoy。#!/usr/bin/env pythonfrom plotly.subplots import make_subplotsimport pandas as pdimport requestsimport jsonimport plotlyimport chart_studio.plotly as pyimport plotly.graph_objs as goimport plotly.express as pximport dashimport dash_core_components as dccimport dash_html_components as htmlfrom dash.dependencies import Output, Input, Statefrom dash.exceptions import PreventUpdateexternal_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 [e-mail](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 figif __name__ == '__main__':    app.run_server(debug=False)你可以玩转输入和状态选项，看看应用程序是如何响应的。干杯!PS：我添加了另一个回调，所以在第一个qoy和ticker值之后，您可以简单地更改ticker输入字段并点击输入按钮（因为qoy已经选择了）来更新您的应用程序。希望这能让您更深入地了解回调是如何工作的。