def dcf_valuation(*args, **kwargs):
if not args[0]:
return [], [], [], dash.no_update
try:
df_dict = args[0]
live_analysis_mode = args[-2]
snapshot_uuid = args[-1]
ticker = list(df_dict.keys())[0]
dcf_store_dict_json = db.get(ticker + '-' + snapshot_uuid)
dcf_store_dict = json.loads(
dcf_store_dict_json) if dcf_store_dict_json else None
safe_get_dcf = dcf_store_dict.get(ticker).get(
'dcf_df_dict') if dcf_store_dict else None
if 1 in live_analysis_mode or not safe_get_dcf:
dcf_df, dcf_output_dict = get_dcf_df(*args)
else:
dcf_df = pd.DataFrame.from_dict(safe_get_dcf)
dcf_output_dict = dcf_store_dict[ticker]['dcf_output_dict']
# Capture all inputs to dcf-store.data
ctx = dash.callback_context
dcf_store_dict = ctx.inputs.pop('fin-store.data')
for k, v in ctx.inputs.items():
dcf_store_dict[ticker][k] = v
dcf_store_dict[ticker]['dcf_df_dict'] = dcf_df.to_dict('records')
dcf_store_dict[ticker]['dcf_output_dict'] = dcf_output_dict
dcf_output_df = pd.DataFrame({
'Price': [dcf_output_dict['last_price']],
'Value':
['{:.2f}'.format(dcf_output_dict['estimated_value_per_share'])],
'Price as % of Value': [
'{:.2f}'.format(100 * dcf_output_dict['last_price'] /
dcf_output_dict['estimated_value_per_share'])
],
'PV Total': [get_string_from_number(dcf_output_dict['PV_sum'])],
'PV Terminal Value':
[get_string_from_number(dcf_output_dict['PV_terminal_value'])],
})
return dcf_store_dict, make_table('dcf-df',
dcf_df), dbc.Table.from_dataframe(
dcf_output_df,
striped=True,
bordered=True,
hover=True), dash.no_update
except TypeError as e:
logger.exception(e)
return [], [], replace_str_element_w_dash_component(
traceback.format_exc()), handler_data_message(
'See Error Message(s) in DCF outputs:', '')
except Exception as e:
logger.exception(e)
raise PreventUpdate
#get options flow from twitter
get_options_flow()
flow = pd.read_sql("select datetime, text from tweets order by datetime desc", conn)
#get reddit data
global dfr
dfr = get_reddit()
####################### Creating the layout #######################
layout1 = html.Div([
dbc.Row([dbc.Col(make_card("Enter Ticker", "success", ticker_inputs('ticker-input', 'date-picker', 36)))]) #row 1
,dbc.Row([dbc.Col([make_card("Twitter Order Flow", 'primary', make_table('table-sorting-filtering2', flow, '17px', 10))])
,dbc.Col([make_card("Fin table ", "secondary", html.Div(id="fin-table"))])
])
, dbc.Row([make_card("select ticker", "warning", "select ticker")],id = 'cards') #row 2
, dbc.Row([
dbc.Col([
dbc.Row([make_card("Wallstreet Bets New Posts", 'primary'
,[html.P(html.Button('Refresh', id='refresh'))
, make_table('table-sorting-filtering', dfr, '17px', 4)])
], justify = 'center')
])
,dbc.Col([dbc.Row([dbc.Alert("__Charts__", color="primary")], justify = 'center')
,dbc.Row(html.Div(id='x-vol-1'), justify = 'center')
, dcc.Interval(
id='interval-component',
interval=1*150000, # in milliseconds
def test_make_table(self):
table = du.make_table(columns=['pclass', 'age'], data=self.df)
self.assertTrue(len(table.columns) == 2)
global dfr
dfr = get_reddit()
layout1 = html.Div([
# html.Div(id = 'cards')
dbc.Row([
dbc.Col(
make_card("Enter Ticker", "success",
ticker_inputs('ticker-input', 'date-picker', 36)))
]) #row 1
,
dbc.Row([
dbc.Col([
make_card("Twitter Order Flow", 'primary',
make_table('table-sorting-filtering2', flow, '17px', 10))
]),
dbc.Col(
[make_card("Fin table ", "secondary", html.Div(id="fin-table"))])
]),
dbc.Row([make_card("select ticker", "warning", "select ticker")],
id='cards') #row 2
,
dbc.Row([
dbc.Col([
dbc.Row([
make_card("Wallstreet Bets New Posts", 'primary', [
html.P(html.Button('Refresh', id='refresh')),
make_table('table-sorting-filtering', dfr, '17px', 4)
])
],
#instantiate dash app server using flask for easier hosting
server = Flask(__name__)
app = dash.Dash(__name__,server = server ,meta_tags=[{ "content": "width=device-width"}], external_stylesheets=[dbc.themes.BOOTSTRAP])
server.wsgi_app = WhiteNoise(server.wsgi_app, root='static/')
#used for dynamic callbacks
app.config.suppress_callback_exceptions = True
#get options flow from twitter
get_options_flow()
flow = pd.read_sql("select datetime, text from tweets order by datetime desc", conn)
#get reddit data
get_reddit()
top_post = pd.read_sql("select title, score, post from reddit order by score desc", conn)
#creating dash layout
layout1 = html.Div([
dbc.Row([dbc.Col([make_card("Twitter Order Flow", 'primary', make_table('table-sorting-filtering2', flow, '17px', 10))])
,dbc.Col([make_card("Wallstreet Bets Top Daily Posts", 'primary', make_table('table-sorting-filtering', top_post, '17px', 4))])
],
no_gutters=True,)#end row
, dbc.Row([dbc.Col(make_card("Enter Ticker", "success", ticker_inputs('ticker-input', 'date-picker', 36)))]) #row 2
, dbc.Row(id = 'cards')
, dbc.Row([
dbc.Col([make_card("Fin table ", "secondary", html.Div(id="fin-table"))])
,dbc.Col([dbc.Row([dbc.Alert("_Charts_", color="primary")], justify = 'center')
,dbc.Row(html.Div(id='x-vol-1'), justify = 'center')
, dcc.Interval(
id='interval-component',
interval=1*150000, # in milliseconds
n_intervals=0)
, dcc.Interval(
id='interval-component2',