here is my code i can able to upload and download files on locally unable to download files after deployement
Preformatted textimport base64
import datetime
import io
from dash.dependencies import Input, Output, State
from dash import html, Dash
import plotly.express as px
from dash import dcc
import pandas as pd
from dash.dash import no_update
import dash_auth
VALID_USERNAME_PASSWORD_PAIRS = {
‘user’: ‘password’
}
external_stylesheets = [‘https://codepen.io/chriddyp/pen/bWLwgP.css’]
app = Dash(name, external_stylesheets=external_stylesheets)
server=app.server
auth = dash_auth.BasicAuth(
app,
VALID_USERNAME_PASSWORD_PAIRS
)
app.layout = html.Div([
html.H1(‘Convertion of FMS logdata to parced data’),
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.B('Select Files')
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
# Allow multiple files to be uploaded
multiple=True
),
html.Div(id='output-data-upload'),
html.Div(
[
html.Button("download", id="btn"),
dcc.Download(id="download")])],className='container')
def parse_contents(contents, filename, date):
content_type, content_string = contents.split(‘,’)
decoded = base64.b64decode(content_string)
global dh3
try:
if ‘csv’ in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode(‘utf-8’)))
elif ‘xls’ in filename:
df = pd.read_excel(io.BytesIO(decoded), skiprows=10, nrows=16729, usecols=[12], header=None)
df2 = pd.read_excel(io.BytesIO(decoded), skiprows=8, usecols=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11])
dfn = df.applymap(lambda x: x.replace(':::5548###[', ' ') if isinstance(x, str) else x)
dfm = dfn.applymap(lambda x: x.replace(' ]]######', '') if isinstance(x, str) else x)
dfl = dfm.applymap(lambda x: x.replace('###', '') if isinstance(x, str) else x)
dfk = dfl.applymap(lambda x: x.replace(',', ' ') if isinstance(x, str) else x)
df1 = df[12].str.extract(
r"\[Priority=(\d*)\] \[GPS element=\[X=(-?\d*)\] \[Y=(-?\d*)\] \[Speed=(-?\d*)\] \[Angle=(-?\d*)\] \[Altitude=(-?\d*)\] \[Satellites=(-?\d*)\]]")
df1.columns = ["Priority", "X", "Y", "Speed", "Angle", "Altitude", "Satellites"]
df3 = dfk[12].str.extract(r"\[Timestamp=(-?\d*)\]")
df4 = dfk[12].str.extract(r"\[EventSource=(-?\d*)\]")
df5 = dfk[12].str.extract(r"\[IMEI = (-?\d*)\]")
df6 = dfk[12].str.extract(r"\[IMEI = (-?\d*)\]")
df7 = dfk[12].str.extract(r"\[Latitude = (-?\d*)\]")
df8 = dfk[12].str.extract(r"\[Longitude = (-?\d*)\]")
df9 = dfk[12].str.extract(r"\[Speed = (-?\d*)\]")
df10 = dfk[12].str.extract(r"\[Angle = (-?\d*)\]")
df11 = dfk[12].str.extract(r"\[Altitude = (-?\d*)\]")
df12 = dfk[12].str.extract(r"\[Odometer = (-?\d*)\]")
df13 = dfk[12].str.extract(r"\[IO = \[Power = (-?\d*)\]")
df14 = dfk[12].str.extract(r"\[Digital Input 1 = (-?\d*)\]")
df15 = dfk[12].str.extract(r"\[Digital Input 2 = (-?\d*)\]")
df16 = dfk[12].str.extract(r"\[Battery Current = (-?\d*)\]")
df17 = dfk[12].str.extract(r"\[Analog Input 2 = (-?\d*)\]")
df18 = dfk[12].str.extract(r"\[Sleep Mode = (-?\d*)\]")
df19 = dfk[12].str.extract(r"\[Analog Input 1 = (-?\d*)\]")
df20 = dfk[12].str.extract(r"\[ICCID = (-?\d*)\]")
df21 = dfk[12].str.extract(r"\[ICCID2 = (-?\d*)\]")
df22 = dfk[12].str.extract(r"\[Axis X = (-?\d*)\]")
df23 = dfk[12].str.extract(r"\[Asis Y = (-?\d*)\]")
df24 = dfk[12].str.extract(r"\[Asis Z = (-?\d*)\]")
df25 = dfk[12].str.extract(r"\[Data Mode = (-?\d*)\]")
df26 = dfk[12].str.extract(r"\[PDOP = (-?\d*)\]")
df27 = dfk[12].str.extract(r"\[Speed = (-?\d*)\]")
df28 = dfk[12].str.extract(r"\[External Voltage = (-?\d*)\]")
df29 = dfk[12].str.extract(r"\[Battery Voltage = (-?\d*)\]")
df30 = dfk[12].str.extract(r"\[GSM Signal = (-?\d*)\]")
df31 = dfk[12].str.extract(r"\[GPS Validity = (-?\d*)\]")
df32 = dfk[12].str.extract(r"\[Battery Percentage = (-?\d*)\]")
df33 = dfk[12].str.extract(r"\[Ignition = (-?\d*)\]")
df34 = dfk[12].str.extract(r"\[Movement = (-?\d*)\]")
df35 = dfk[12].str.extract(r"\[Active GSM Operator = (-?\d*)\]")
df36 = dfk[12].str.extract(r"\[Digital Output 1 = (-?\d*)\]")
df37 = dfk[12].str.extract(r"\[Digital Output 2 = (-?\d*)\]")
df38 = dfk[12].str.extract(r"\[Voltage = (-?\d*)\]")
df39 = dfk[12].str.extract(r"\Device Time : (-?\d*-?\d*-?\d* \d*:\d*:\d*)")
df3.columns = ["Time_stamp"]
df4.columns = ["EventSource"]
df5.columns = ["IMEI"]
df6.columns = ["IMEI"]
df7.columns = ["Latitude"]
df8.columns = ["Longitude"]
df9.columns = ["Speed"]
df10.columns = ["Angle"]
df11.columns = ["Altitude"]
df12.columns = ["Odometer"]
df13.columns = ["IO(Power)"]
df14.columns = ["Digital input(1)"]
df15.columns = ["Digital input(2)"]
df16.columns = ["Battery Current"]
df17.columns = ["Analog Input 2 "]
df18.columns = ["Sleep Mode"]
df19.columns = ["Analog Input 1 "]
df20.columns = ["ICCID"]
df21.columns = ["ICCID2"]
df22.columns = ["Axis X"]
df23.columns = ["Axis Y"]
df24.columns = ["Axis Z"]
df25.columns = ["Data Mode"]
df26.columns = ["PDOP"]
df27.columns = ["Speed"]
df28.columns = ["External Voltage"]
df29.columns = ["Battery Voltage"]
df30.columns = ["GSM Signal"]
df31.columns = ["GPS Validity"]
df32.columns = ["Battery Percentage"]
df33.columns = ["Ignition"]
df34.columns = ["Movement"]
df35.columns = ["Active GSM Operator"]
df36.columns = ["Digital Output 1"]
df37.columns = ["Digital Output 2"]
df38.columns = ["Voltage "]
df39.columns = ["Device Time"]
dataframe = pd.concat(
[df2, df1, df3, df4, df5, df6, df7, df8, df9, df10, df11, df12, df13, df14, df15, df16, df17, df18,
df19,
df20, df21, df22, df23, df24, df25, df26, df27, df28, df29, df30, df31, df32, df33, df34, df35, df36,
df37, df38, df39], axis=1)
dh1 = dataframe.applymap(lambda x: x.replace("On", '1') if isinstance(x, str) else x)
dh2 = dh1.applymap(lambda x: x.replace("Immobilize=", '') if isinstance(x, str) else x)
dh2["Time_stamp"] = dh2["Time_stamp"].apply(pd.to_numeric)
dh2["Analog Input 2 "] = dh2["Analog Input 2 "].apply(pd.to_numeric)
dh2["Analog Input 2 "] = dh2["Analog Input 2 "].astype(float) * 0.001
dh3 = dh2.applymap(lambda x: x.replace("Off", '0') if isinstance(x, str) else x)
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
return html.Div([
html.P('Analog Input2 with Respect to Timestamp'),
dcc.Graph(
figure=px.line(dh3,x='Time_stamp',y='Analog Input 2 ',template="plotly_dark").update_layout(
{"plot_bgcolor": "rgba(0, 0, 0, 0)", "paper_bgcolor": "rgba(0, 0, 0, 0)"}),
),
])
@app.callback(
Output(“download”, “data”),
[Input(“btn”, “n_clicks”)],
prevent_initial_call=True,
)
def func(n_clicks):
return dcc.send_data_frame(dh3.to_excel, “new parced excel data.xlsx”)
@app.callback(Output(‘output-data-upload’,‘children’),
Input(‘upload-data’, ‘contents’),
State(‘upload-data’, ‘filename’),
State(‘upload-data’, ‘last_modified’))
def update_output(list_of_contents, list_of_names, list_of_dates):
if list_of_contents is not None:
children = [
parse_contents(c, n, d) for c, n, d in
zip(list_of_contents, list_of_names, list_of_dates)]
return children
if name == ‘main’:
app.run_server(debug=True,port=4)
`