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)