def main_function(self, mode): external_stylesheets = [ 'https://raw.githubusercontent.com/rab657/explainx/master/explainx.css', dbc.themes.BOOTSTRAP, { 'href': 'https://fonts.googleapis.com/css?family=Montserrat', 'rel': 'stylesheet' } ] local = JupyterDash(__name__, external_stylesheets=external_stylesheets, suppress_callback_exceptions=True) local.title = "explainX.ai - Feature Interaction" local.layout = feature_interaction.layout_interaction( self.data, self.df_with_shap, local) if mode == None: import random port = random.randint(5000, 6000) return local.run_server(port=port) else: import random port = random.randint(5000, 6000) return local.run_server(mode='inline', port=port)
def main_function(self, mode): external_stylesheets = [ 'https://raw.githubusercontent.com/rab657/explainx/master/explainx.css', dbc.themes.BOOTSTRAP, { 'href': 'https://fonts.googleapis.com/css?family=Montserrat', 'rel': 'stylesheet' } ] local = JupyterDash(__name__, external_stylesheets=external_stylesheets, suppress_callback_exceptions=True) local.title = "explainX.ai - Local Level Explanation" local.layout = local_explanation.layout_local(self.shapley_values, self.data, self.df_with_shap, local) debug_value = False if mode is None: import random port = random.randint(6000, 7000) return local.run_server(port=port, debug=debug_value, dev_tools_ui=debug_value, dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True, dev_tools_hot_reload=True) else: import random port = random.randint(6000, 7000) return local.run_server(mode='inline', port=port, debug=debug_value, dev_tools_ui=debug_value, dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True, dev_tools_hot_reload=True)
def main_function(self, mode): external_stylesheets = [ 'https://raw.githubusercontent.com/rab657/explainx/master/explainx.css', dbc.themes.BOOTSTRAP, { 'href': 'https://fonts.googleapis.com/css?family=Montserrat', 'rel': 'stylesheet' } ] cohort = JupyterDash(__name__, external_stylesheets=external_stylesheets, suppress_callback_exceptions=True) cohort.title = "explainX.ai - Model Performance Analysis" cohort.layout = cohort_app.test_func(self.data, self.model, cohort) debug_value = False if mode == None: import random port = random.randint(4000, 5000) return cohort.run_server(port=port, debug=debug_value, dev_tools_ui=debug_value, dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True, dev_tools_hot_reload=True) else: import random port = random.randint(4000, 5000) return cohort.run_server(mode='inline', port=port, debug=debug_value, dev_tools_ui=debug_value, dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True, dev_tools_hot_reload=True)
""" from grid2viz.main_callbacks import register_callbacks_main from grid2viz.layout import make_layout as layout from grid2viz.src.episodes.episodes_clbk import register_callbacks_episodes from grid2viz.src.overview.overview_clbk import ( register_callbacks_overview, ) # as overview_clbk from grid2viz.src.macro.macro_clbk import register_callbacks_macro # as macro_clbk from grid2viz.src.micro.micro_clbk import register_callbacks_micro # as micro_clbk """ End Warning """ app.config.suppress_callback_exceptions = True app.title = "Grid2Viz" app.server.secret_key = "Grid2Viz" ##create layout layout(app) ##create callbaks register_callbacks_main(app) register_callbacks_episodes(app) register_callbacks_overview(app) register_callbacks_macro(app) register_callbacks_micro(app) def app_run(port=8050, debug=False): app.run_server(port=port, debug=debug)
def run_dash(path, search_criteria, mode=None): PLOTLY_LOGO = "https://images.plot.ly/logo/new-branding/plotly-logomark.png" # instantiating dash application #app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP]) app = JupyterDash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP]) app.title = "Resume Analyzer" files = [f for f in listdir(path) if isfile(join(path, f))] nlp = en_core_web_sm.load() search_bar = dbc.Row( [ dbc.Badge( str(len(files)) + " Resume found", id="doc_info", href="#", color="warning", className="mr-1", ), dbc.Col( dbc.Button("Process ⚙️", color="primary", className="ml-2", id="button", n_clicks=1), width="12", ), ], no_gutters=True, className="ml-auto flex-nowrap mt-3 mt-md-0", align="center", ) navbar = dbc.Navbar( [ html.A( # Use row and col to control vertical alignment of logo / brand dbc.Row( [ dbc.Col(html.Img(src=PLOTLY_LOGO, height="30px")), dbc.Col( dbc.NavbarBrand("Resume Analyzer", className="ml-2")), ], align="center", no_gutters=True, ), href="https://shivanandroy.com", ), dbc.NavbarToggler(id="navbar-toggler"), dbc.Collapse(search_bar, id="navbar-collapse", navbar=True), ], color="dark", dark=True, ) text = "**The table is filterable and sortable" summary = html.Div([ dbc.Row([ dbc.Col(dcc.Loading( html.Div([ html.Div(text, style={'font-size': '10px'}), dash_table.DataTable( id='table', sort_action="native", filter_action="native", style_cell={ 'font_family': 'Trebuchet MS', 'font_size': '15px', 'text_align': 'center' }, style_header={ 'backgroundColor': 'rgb(230, 230, 230)', 'fontWeight': 'bold' }, style_header_conditional=[{ 'if': { 'column_id': 'RANKING', }, 'backgroundColor': '#A8A8A8', 'color': 'black' }, { 'if': { 'column_id': 'TOTAL SCORE', }, 'backgroundColor': '#A8A8A8', 'color': 'black' }, { 'if': { 'column_id': 'RATING', }, 'backgroundColor': '#A8A8A8', 'color': 'black' }]) ])), width={ 'size': 10, 'offset': 1 }) ], align='end') ]) app.layout = html.Div([navbar, html.Br(), summary]) @app.callback( [Output("table", "columns"), Output("table", "data")], [Input("button", "n_clicks")], ) def toggle_navbar_collapse(n): if n is None: raise PreventUpdate else: files = [f for f in listdir(path) if isfile(join(path, f))] df = rank(path=path, search_criteria=search_criteria) return [{ "name": i, "id": i } for i in df.columns], df.to_dict('records') if mode == "browser": app.run_server(debug=True) if mode == "notebook": app.run_server(debug=True, mode="inline", width=950)