def register_app(self, theapp):
@theapp.callback([ServersideOutput(self.main_store.id, 'data')],
[Trigger(self.trigger_interval.id, 'n_intervals')])
def _update_main_store():
print(f"EiaAccess._update_main_store")
df = pd.read_csv(self.input_pet_file)
return df
@theapp.callback([
Output(self.data_dt.id, 'data'),
Output(self.data_dt.id, 'columns')
], [
Input(self.main_store.id, 'data'),
Input(self.num_displayable_columns.id, 'value'),
Input(self.eia_cat_div.dropdowns_store.id, 'data')
])
def _populate_data_dt(df_main_store_data, num_displayable_columns,
dropdowns_store):
print(
f"EiaAccess._populate_data_dt number of columns:{len(df_main_store_data.columns.values)}"
)
if dropdowns_store is None:
columns = df_main_store_data.columns.values[:
num_displayable_columns]
else:
padd_name = dropdowns_store['padd_name']
padd_location = None #dropdowns_store['padd_location']
padd_production_type = dropdowns_store['padd_production_type']
padd_fuel_type = dropdowns_store['padd_fuel_type']
gas_price_region = dropdowns_store['gas_price_region']
gas_price_gas_type = dropdowns_store['gas_price_gas_type']
gas_price_grade = dropdowns_store['gas_price_grade']
df_cols = self.eia_cat_div.eia_categories.get_column_set(
padd_name, padd_location, padd_production_type,
padd_fuel_type, gas_price_region, gas_price_gas_type,
gas_price_grade)
columns = list(set(['date'] + list(df_cols.col.values)))
# make date the first column
columns = ['date'] + [c for c in columns if c != 'date']
columns = columns[:num_displayable_columns]
df_ret = df_main_store_data[columns]
ret_columns = [{'label': c, 'id': c} for c in columns]
dict_ret = df_ret.to_dict('records')
return dict_ret, ret_columns
self.eia_cat_div.register_app(theapp)
self.logger.info('registered eia_access')
import dash_html_components as html
from dash_extensions.enrich import Output, Dash, Trigger
app = Dash(prevent_initial_callbacks=True)
app.layout = html.Div([
html.Button("Left", id="left"), html.Button("Right", id="right"), html.Div(id="log"),
])
@app.callback(Output("log", "children"), Trigger("left", "n_clicks"), group="lr") # targets same output as right
def left():
return "left"
@app.callback(Output("log", "children"), Trigger("right", "n_clicks"), group="lr") # targets same output as left
def right():
return "right"
if __name__ == '__main__':
app.run_server()
# raise PreventUpdate
# else:
# spec = np.roll(existing_store['spec'],-1,0)
# spec[-1] = newLine
# existing_store['spec'] = spec
# existing_store['freqs'] = freqs
# existing_store['timestamp'] = timestamp
# return existing_store
@app.callback(
ServersideOutput("userServerStore",
"data"), [Trigger("check_for_data", "n_intervals")],
[State("spec", "relayoutData"),
State("userServerStore", "data")],
prevent_initial_call=True)
def update_server_store(relayoutData, userServerStore):
existing_store = userServerStore
latest_message = numpy_from_Redis(redis_client, 'latest')
latest_integration = np.array(latest_message[:-1], dtype=const.DTYPE)
latest_timestamp = latest_message[-1]
if existing_store == None:
existing_store = {
'spec': start_spec,
'freqs': start_freqs,
'timestamp': 0.0
fig.add_trace(go.Scatter(x=df.index, y=df[col]))
return fig
def make_layout(tag):
return [
dcc.Graph(id=f"graph_{tag}"),
html.Button(f"Update [{tag}]", id=f"btn_{tag}")
]
tags = ["default", "memoize", "prejson"]
memoize = dict(default=None, memoize=True, prejson=plotly_jsonify)
# Create dummy data.
df = pd.DataFrame(index=pd.date_range("2020-01", "2021-01", freq="H"),
columns=list("ABCDEFGHIJK"),
data=pd.np.nan)
df[:] = np.random.random(df.values.shape)
# Create example app.
app = Dash(prevent_initial_callbacks=True)
app.layout = html.Div(
list(itertools.chain.from_iterable([make_layout(tag) for tag in tags])))
# Attach callbacks.
for t in tags:
app.callback(Output(f"graph_{t}", "figure"),
Trigger(f"btn_{t}", "n_clicks"),
memoize=memoize[t])(make_figure)
if __name__ == '__main__':
app.run_server(port=8877, debug=True)
import time
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
from dash_extensions.enrich import Dash, Output, Input, Trigger, ServersideOutput
app = Dash(prevent_initial_callbacks=True)
app.layout = html.Div([
html.Button("Query data", id="btn"),
dcc.Dropdown(id="dd"),
dcc.Graph(id="graph"),
dcc.Loading(dcc.Store(id='store'), fullscreen=True, type="dot")
])
@app.callback(ServersideOutput("store", "data"), Trigger("btn", "n_clicks"))
def query_data():
time.sleep(1)
return px.data.gapminder() # no JSON serialization here
@app.callback(Input("store", "data"), Output("dd", "options"))
def update_dd(df):
return [{
"label": column,
"value": column
} for column in df["year"]] # no JSON de-serialization here
@app.callback(
Output("graph", "figure"),
import dash_html_components as html
from dash_extensions.enrich import Output, Dash, Trigger
app = Dash(prevent_initial_callbacks=True)
app.layout = html.Div([html.Button("Click me", id="btn"), html.Div(id="log")])
@app.callback(Output("log", "children"), Trigger("btn", "n_clicks"))
def func(): # argument is omitted from the function
return "You clicked the button"
if __name__ == '__main__':
app.run_server()
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
from dash_extensions.enrich import Dash, Output, Input, Trigger, ServersideOutput
app = Dash(prevent_initial_callbacks=True)
app.layout = html.Div([
html.Button("Query data", id="btn"),
dcc.Dropdown(id="dd"),
dcc.Graph(id="graph"),
dcc.Loading(dcc.Store(id='store'), fullscreen=True, type="dot")
])
@app.callback(ServersideOutput("store", "data"),
Trigger("btn", "n_clicks"),
memoize=True)
def query_data():
time.sleep(1)
return px.data.gapminder()
@app.callback(Input("store", "data"), Output("dd", "options"))
def update_dd(df):
return [{"label": column, "value": column} for column in df["year"]]
@app.callback(
Output("graph", "figure"),
[Input("store", "data"), Input("dd", "value")])
def update_graph(df, value):
'hoverinfo': 'text',
'text': hover_text
}],
'layout': {
'title': '<b>Feature Pairwise Co-occurrence</b> ',
}
}
return {
'layout': {
'title': '<b>Feature Pairwise Co-occurrence</b> ',
}
}
@app.callback(Output('scatter', 'figure'), [
Trigger('prog-len-filter-slider', 'value'),
Input('crossfilter-xaxis-column', 'value'),
Input('crossfilter-yaxis-column', 'value'),
Input('co-occurrence-graph', 'clickData'),
Input('ori-df-store', 'data')
])
def update_two_feature_scatter_plot_using_filters(xaxis_column_index,
yaxis_column_index,
co_click_data, ori_df):
X, y = ResultProcessing.read_dataset_X_y(ori_df)
names = ResultProcessing.read_dataset_names(ori_df)
ctx = dash.callback_context
trigger_id = ctx.triggered[0]['prop_id'].split('.')[0]
if trigger_id == 'crossfilter-xaxis-column' or trigger_id == 'crossfilter-yaxis-column':
xaxis_column_index = int(xaxis_column_index)
yaxis_column_index = int(yaxis_column_index)