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如何正確地為 Dash Web 應(yīng)用程序執(zhí)行回調(diào)和函數(shù)

Python

POPMUISE 2022-10-06 16:13:51

非常感謝有關(guān)如何為我的 Dash Web 應(yīng)用程序進(jìn)行正確回調(diào)的一些幫助。我在下面有以下代碼。它應(yīng)該返回一個(gè)圖表，其中包含有關(guān)股票財(cái)務(wù)狀況的各種線(xiàn)條。它從 API 獲取數(shù)據(jù)。但我不確定如何為應(yīng)用回調(diào)定義我的函數(shù)。我嘗試過(guò)遵循在線(xiàn)教程，但取得了任何成功。如果它太混亂或效率低下，我深表歉意，我是新手。'''#!/usr/bin/env pythonimport 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, Inputticker = 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.indexdf_FS.fillna(0, inplace=True)print(df_FS)

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1 回答

慕碼人2483693

TA貢獻(xiàn)1860條經(jīng)驗(yàn) 獲得超9個(gè)贊

您必須在回調(diào)中執(zhí)行所有數(shù)據(jù)處理，因?yàn)樗鼈冃枰斎牒桶粹o值。有多種方法可以解決此問(wèn)題，具體取決于您希望應(yīng)用程序如何響應(yīng)輸入。一種方法是這樣。在這里，主要輸入是qoy，回調(diào)使用stock input. 因此，在您選擇之前，輸入股票輸入不會(huì)更新應(yīng)用程序qoy。

#!/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)

你可以玩轉(zhuǎn)輸入和狀態(tài)選項(xiàng)，看看應(yīng)用程序是如何響應(yīng)的。干杯!

PS：我添加了另一個(gè)回調(diào)，所以在第一個(gè)qoy和ticker值之后，您可以簡(jiǎn)單地更改ticker輸入字段并點(diǎn)擊輸入按鈕（因?yàn)閝oy已經(jīng)選擇了）來(lái)更新您的應(yīng)用程序。希望這能讓您更深入地了解回調(diào)是如何工作的。

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