如果数据图位于线程内

Question

我正在设计一个Kafka解决方案。最后，我创建了一个带有破折号和绘图的仪表板。通常，我可以在图表上解析后显示数据。但是，当我从另一个在线程内运行的函数中获取数据时，该图不会绘制任何内容。

我使用Python 3.5

正常代码有效。我获取数据，解析时间戳（13:20:15-13:20:55）和消息计数。图总是根据时间间隔重新加载。

import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly
from dash.dependencies import Input, Output

TIME_INTERVAL = 100

veri = [[['2019-04-09 13:11:25'], ['INFO'], ['Istanbul'], ['Hello-From-Istanbul']], [['2019-04-09 13:11:26'], ['FATAL'], ['London'], ['Hello-From-London']], [['2019-04-09 13:11:27'], ['FATAL'], ['Istanbul'], ['Hello-From-Istanbul']], [['2019-04-09 13:11:28'], ['INFO'], ['Moskow'], ['Hello-From-Moskow']], [['2019-04-09 13:11:29'], ['INFO'], ['Moskow'], ['Hello-From-Moskow']], [['2019-04-09 13:11:30'], ['FATAL'], ['Tokyo'], ['Hello-From-Tokyo']], [['2019-04-09 13:11:31'], ['DEBUG'], ['Istanbul'], ['Hello-From-Istanbul']], [['2019-04-09 13:11:32'], ['FATAL'], ['Beijing'], ['Hello-From-Beijing']] ..... ]

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(
    html.Div([
        html.H4('Kafka Dashboard'),
        dcc.Graph(id='live-update-graph'),
        dcc.Interval(
            id='interval-component',
            interval=1 *1000,
            n_intervals=0
        )
    ])
)
countofmessage=[]
timeseries=[]

for i in range(len(veri)):
    times = veri[i][0][0].split(" ")[1]
    timeseries.append(times)

if len(veri) % TIME_INTERVAL == 0:
    rest = 0
    next = 0
else:
    rest = len(veri) % TIME_INTERVAL
    next = 1

for i in range(0, int(len(veri)/TIME_INTERVAL)+next):
    countofmessage.append([0, 0, 0, 0, 0])

for i in range(0, int(len(veri)/TIME_INTERVAL)+next):
    d = i * TIME_INTERVAL
    if i == int(len(veri)/TIME_INTERVAL):
        plus = rest
    else:
        plus = TIME_INTERVAL

    for a in range(d, d+plus):
        if veri[a][2][0] == "Moskow":
            countofmessage[i][0] += 1
        if veri[a][2][0] == "Istanbul":
            countofmessage[i][1] += 1
        if veri[a][2][0] == "Tokyo":
            countofmessage[i][2] += 1
        if veri[a][2][0] == "Beijing":
            countofmessage[i][3] += 1
        if veri[a][2][0] == "London":
            countofmessage[i][4] += 1


@app.callback(Output('live-update-graph', 'figure'),
              [Input('interval-component', 'n_intervals')])
def update_graph_live(n) :
    data = {
        'moskow_x': [],
        'moskow_y': [],

        'istanbul_x': [],
        'istanbul_y': [],

        'tokyo_x': [],
        'tokyo_y': [],

        'beijing_x': [],
        'beijing_y': [],

        'london_x': [],
        'london_y': [],

    }

    # Collect some data
    for i in range(0, int(len(veri)/TIME_INTERVAL)+next):
        data['moskow_x'].append(timeseries[i*TIME_INTERVAL])
        data['istanbul_x'].append(timeseries[i * TIME_INTERVAL])
        data['tokyo_x'].append(timeseries[i * TIME_INTERVAL])
        data['beijing_x'].append(timeseries[i * TIME_INTERVAL])
        data['london_x'].append(timeseries[i * TIME_INTERVAL])

    for i in range(len(countofmessage)) :
        data['moskow_y'].append(countofmessage[i][0])
        data['istanbul_y'].append(countofmessage[i][1])
        data['tokyo_y'].append(countofmessage[i][2])
        data['beijing_y'].append(countofmessage[i][3])
        data['london_y'].append(countofmessage[i][4])

    fig = plotly.tools.make_subplots(rows=1, cols=1, vertical_spacing=0.2)
    fig['layout']['margin'] = {
        'l' : 30, 'r' : 10, 'b' : 30, 't' : 10
    }
    fig['layout']['legend'] = {'x' : 0, 'y' : 1, 'xanchor' : 'left'}

    fig.append_trace({
        'x' : data['moskow_x'],
        'y' : data['moskow_y'],
        'name' : 'Moskow',
        'mode' : 'lines+markers',
        'type' : 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x' : data['istanbul_x'],
        'y' : data['istanbul_y'],
        'name' : 'Istanbul',
        'mode' : 'lines+markers',
        'type' : 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x' : data['tokyo_x'],
        'y' : data['tokyo_y'],
        'name' : 'Tokyo',
        'mode' : 'lines+markers',
        'type' : 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x' : data['beijing_x'],
        'y' : data['beijing_y'],
        'name' : 'Beijing',
        'mode' : 'lines+markers',
        'type' : 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x' : data['london_x'],
        'y' : data['london_y'],
        'name' : 'London',
        'mode' : 'lines+markers',
        'type' : 'scatter'
    }, 1, 1)

    return fig


app.run_server()

我从kafka获取数据。然后在getdata（）中解析。然后用图形查看值，但什么也没画。 listen（）getdata（）和update_graph同时工作。

from confluent_kafka import Consumer
from pymongo import MongoClient
import threading
import datetime
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly
from dash.dependencies import Input, Output
from multiprocessing import Process


veri = []

TIME_INTERVAL=30

next=0
oldveri = 0

timeseries=[['13:11:25']]
countofmessage=[]
splitted = []
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(
    html.Div([
        html.H4('Kafka Dashboard'),
        dcc.Graph(id='live-update-graph'),
        dcc.Interval(
            id='interval-component',
            interval=1 * 1000,
            n_intervals=0
        )
    ])
)
client = MongoClient("localhost", 27017)
db = client.get_database("people")
messages = db.get_collection("messages")

c = Consumer({
    'bootstrap.servers': 'localhost:9092',
    'group.id': 'my-group',
    'auto.offset.reset': 'earliest'
})

c.subscribe(['my-topic'])


def listen():
    while True :
        msg = c.poll(1.0)
        if msg is None :
            continue
        if msg.error() :
            print("Consumer error: {}".format(msg.error()))
            continue

        splitted = msg.value().decode('utf-8').split(" ")
        veri.append([[splitted[0] + " " + splitted[1]], [splitted[2]], [splitted[3]], [splitted[4]]])


    c.close()


def getdata():
    while True:
        if oldveri < len(veri):
            global oldveri
            oldveri = len(veri)
            for i in range(len(veri)):
                times = veri[i][0][0].split(" ")[1]
                timeseries.append(times)

            if len(veri) % TIME_INTERVAL == 0 :
                rest = 0
                next = 0
            else :
                rest = len(veri) % TIME_INTERVAL
                next = 1

            for i in range(0, int(len(veri) / TIME_INTERVAL) + next) :
                countofmessage.append([0, 0, 0, 0, 0])

            for i in range(0, int(len(veri) / TIME_INTERVAL) + next) :
                a = i * TIME_INTERVAL
                if i == int(len(veri) / TIME_INTERVAL) :
                    plus = rest
                else :
                    plus = TIME_INTERVAL

                for a in range(a, a + plus) :
                    if veri[a][2][0] == "Moskow" :
                        countofmessage[i][0] += 1
                    if veri[a][2][0] == "Istanbul" :
                        countofmessage[i][1] += 1
                    if veri[a][2][0] == "Tokyo" :
                        countofmessage[i][2] += 1
                    if veri[a][2][0] == "Beijing" :
                        countofmessage[i][3] += 1
                    if veri[a][2][0] == "London" :
                        countofmessage[i][4] += 1


@app.callback(Output('live-update-graph', 'figure'),
                  [Input('interval-component', 'n_intervals')])
def update_graph_live(n):
    data = {
        'moskow_x': [],
        'moskow_y': [],

        'istanbul_x': [],
        'istanbul_y': [],

        'tokyo_x': [],
        'tokyo_y': [],

        'beijing_x': [],
        'beijing_y': [],

        'london_x': [],
        'london_y': [],

    }

    # Collect some data
    for i in range(0, int(len(veri)/30)+next+1):
        data['moskow_x'].append(timeseries[i*30])
        data['istanbul_x'].append(timeseries[i*30])
        data['tokyo_x'].append(timeseries[i*30])
        data['beijing_x'].append(timeseries[i*30])
        data['london_x'].append(timeseries[i*30])

    for i in range(len(countofmessage)):
        data['moskow_y'].append(countofmessage[i][0])
        data['istanbul_y'].append(countofmessage[i][1])
        data['tokyo_y'].append(countofmessage[i][2])
        data['beijing_y'].append(countofmessage[i][3])
        data['london_y'].append(countofmessage[i][4])

    fig = plotly.tools.make_subplots(rows=1, cols=1, vertical_spacing=0.2)
    fig['layout']['margin'] = {
        'l': 30, 'r': 10, 'b': 30, 't': 10
    }
    fig['layout']['legend'] = {'x': 0, 'y': 1, 'xanchor': 'left'}

    fig.append_trace({
        'x': data['moskow_x'],
        'y': data['moskow_y'],
        'name': 'Moskow',
        'mode': 'lines+markers',
        'type': 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x': data['istanbul_x'],
        'y': data['istanbul_y'],
        'name': 'Istanbul',
        'mode': 'lines+markers',
        'type': 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x': data['tokyo_x'],
        'y': data['tokyo_y'],
        'name': 'Tokyo',
        'mode': 'lines+markers',
        'type': 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x': data['beijing_x'],
        'y': data['beijing_y'],
        'name': 'Beijing',
        'mode': 'lines+marTIME_INTERVALkers',
        'type': 'scatter'
    }, 1, 1)
    fig.append_trace({
        'x': data['london_x'],
        'y': data['london_y'],
        'name': 'London',
        'mode': 'lines+markers',
        'type': 'scatter'
    }, 1, 1)

    return fig

def startserver():
    app.run_server()


sv = threading.Thread(name='startserver', target=startserver)
tb = threading.Thread(name='getdata', target=getdata)
ta = threading.Thread(name='listen', target=listen)


sv.start()
tb.start()
ta.start()

我该如何解决？