html.A('Select Files')]),
style={
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
},
className='uploader',
# Allow multiple files to be uploaded
multiple=True),
])
page.layout = html.Div([
html.Div([dcc.Store(id='store-local-data', storage_type='session')]),
trade_table_display,
html.H4("Upload excel sheet"),
trade_upload,
])
def parse_contents(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
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:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded))
except Exception as e:
start_date=(datetime.today() - timedelta(30)).date(),
end_date=datetime.today().date(),
display_format='MMM Do, YY',
persistence=True,
persisted_props=['start_date'],
updatemode='bothdates',
),
html.Br(),
dcc.Graph(id='exit-quality-indicator', figure=exit_quality_fig)
])
page.layout = [
html.H1(
page.name,
style={
"margin-bottom": "10px",
"margin-left": "4px",
},
),
generate_analysis_mode_dropdown(page.id), gauge_layout
]
@app.callback(Output('exit-quality-indicator', 'figure'), [
Input('date-picker', 'start_date'),
Input('date-picker', 'end_date'),
Input('exit-quality-asset-dropdown', 'value')
], [
State(page.id + '-buy-price-dict', 'data'),
State(page.id + '-sell-price-dict', 'data')
])
def update_exit_quality_indicator(start_date, end_date, stock_code,