async def serve(q: Q):
if not q.client.initialized:
q.page['meta'] = ui.meta_card(box='', theme='neon')
q.page['controls'] = ui.form_card(box='1 1 2 8', items=[
ui.text_xl('Form'),
ui.textbox(name='textbox', label='Textbox'),
ui.toggle(name='toggle', label='Toggle'),
ui.choice_group(name='choice_group', label='Choice group', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.checklist(name='checklist', label='Checklist', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.dropdown(name='dropdown', label='Dropdown', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.slider(name='slider', label='Slider'),
ui.button(name='toggle_theme', label='Toggle Theme', primary=True)
])
q.client.theme = 'default'
q.client.initialized = True
meta = q.page['meta']
if q.args.toggle_theme:
meta.theme = q.client.theme = 'neon' if q.client.theme == 'default' else 'default'
await q.page.save()
def init(q: Q):
q.page['meta'] = ui.meta_card(
box='',
title='Explain Ratings',
layouts=[
ui.layout(breakpoint='xs',
zones=[
ui.zone('header'),
ui.zone('body',
direction=ui.ZoneDirection.ROW,
size='calc(100vh - 70px)',
zones=[
ui.zone('sidebar', size='350px'),
ui.zone('content',
direction=ui.ZoneDirection.ROW)
])
]),
])
q.page['header'] = ui.header_card(box='header',
title='Hotel Reviews',
subtitle='Explains the hotel reviews',
icon='ReviewSolid',
icon_color='#00A8E0')
q.client.review = config.review_column_list[0]
form_filters = []
for column in config.filterable_columns:
choices = [ui.choice(name='empty', label='All')] + [
ui.choice(name=str(column), label=str(column))
for column in config.dataset[column].drop_duplicates()
]
form_filters.append(
ui.dropdown(name=f'filter_{column}',
label=config.column_mapping[column],
trigger=True,
value='empty',
choices=choices))
sidebar_items = [
ui.dropdown(name='review',
label='Review type',
value=q.client.review,
trigger=True,
choices=[
ui.choice(name=column,
label=config.column_mapping[column])
for column in config.dataset[config.review_column_list]
]),
ui.separator('Filters')
] + form_filters
q.page['sidebar'] = ui.form_card(box='sidebar', items=sidebar_items)
q.page['original'] = ui.image_card(box='content',
title='Original',
type='png',
image=plot_word_cloud(
config.dataset[q.client.review], q))
async def render(self, q: Q):
"""
Render card in Wave.
Args:
q: Wave server
"""
model_choices = [ui.choice(name=str(x), label=str(x)) for x in self.input_models]
card = ui.section_card(
box=self.box,
title=self.title,
subtitle=self.subtitle,
items=[
ui.dropdown(
name='input_model',
label='Select model',
value=self.input_model,
choices=model_choices,
trigger=True
)
],
commands=self.commands
)
q.page[self.name] = card
def make_blurb(q: Q, example: Example):
blurb_card = q.page['blurb']
blurb_card.title = example.title
blurb_card.subtitle = example.description
# HACK: Recreate dropdown every time (by dynamic name) to control value (needed for next / prev btn functionality).
items = [
ui.dropdown(name=q.args['#'] or default_example_name,
width='300px',
value=example.name,
trigger=True,
choices=[
ui.choice(name=e.name, label=e.title)
for e in catalog.values()
])
]
if example.previous_example:
items.append(
ui.button(name=f'#{example.previous_example.name}',
label='Previous'))
if example.next_example:
items.append(
ui.button(name=f'#{example.next_example.name}',
label='Next',
primary=True))
blurb_card.items = items
def populate_dropdown_list(q: Q):
filter_choices = [
ui.choice(
name=json.dumps({"id": q.client.filter_count + 1, "attr": column, "attr_val": None}),
label=config.column_mapping[column]
) for column in config.filterable_columns
]
items = [
ui.text_l("Filter reviews"),
]
for key, value in q.client.filters.items():
for attr, attr_val in value.items():
items.append(ui.dropdown(
name="filter",
label="Choose a review attribute",
placeholder=config.column_mapping[attr],
choices=[
ui.choice(
name=json.dumps({'id': key, 'attr': column, 'attr_val': None}),
label=config.column_mapping[column]
) for column in config.filterable_columns
],
trigger=True,
), )
items.append(ui.dropdown(
name="filter_value",
label="Choose a value for selected review attribute",
placeholder=attr_val,
choices=[ui.choice(name=json.dumps({'id': key, 'attr': attr, 'attr_val': column}), label=column) for
column in config.dataset[attr].drop_duplicates()],
trigger=True,
), )
items.append(ui.separator())
if (q.args.add_filter and all(q.client.filters.values())) or q.args.review_choice or q.args.reset_filters:
items.append(ui.dropdown(
name="filter",
label="Choose a review attribute",
placeholder="Please select a category to filter",
choices=filter_choices,
trigger=True
), )
items.append(ui.button(name="compare_review_button", label="Compare Reviews", primary=True))
return items
async def serve(q: Q):
if q.args.train:
# train WaveML Model using H2O-3 AutoML
copy_expando(q.args, q.client)
q.client.wave_model = build_model(
train_df=q.client.train_df,
target_column='target',
model_type=ModelType.H2O3,
_h2o3_max_runtime_secs=30,
_h2o3_nfolds=2,
_h2o3_include_algos=[q.client.algo]
)
model_id = q.client.wave_model.model.model_id
accuracy = round(100 - q.client.wave_model.model.mean_per_class_error() * 100, 2)
# show training details and prediction option
q.page['example'].items[1].choice_group.value = q.client.algo
q.page['example'].items[2].buttons.items[1].button.disabled = False
q.page['example'].items[3].message_bar.type = 'success'
q.page['example'].items[3].message_bar.text = 'Training successfully completed!'
q.page['example'].items[4].text.content = f'''**H2O AutoML model id:** {model_id} <br />
**Accuracy:** {accuracy}%'''
q.page['example'].items[5].text.content = ''
elif q.args.predict:
# predict on test data
preds = q.client.wave_model.predict(test_df=q.client.test_df)
# show predictions
q.page['example'].items[3].message_bar.text = 'Prediction successfully completed!'
q.page['example'].items[5].text.content = f'''**Example predictions:** <br />
{preds[0]} <br /> {preds[1]} <br /> {preds[2]}'''
else:
# prepare sample train and test dataframes
data = load_wine(as_frame=True)['frame']
q.client.train_df, q.client.test_df = train_test_split(data, train_size=0.8)
# algos
algo_choices = [ui.choice(x, x) for x in ['DRF', 'GLM', 'XGBoost', 'GBM', 'DeepLearning']]
# display ui
q.page['example'] = ui.form_card(
box='1 1 -1 -1',
items=[
ui.text(content='''The sample dataset used is the
<a href="https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html" target="_blank">wine dataset</a>.'''),
ui.choice_group(name='algo', label='Select Algo', choices=algo_choices, value='DRF'),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True),
ui.button(name='predict', label='Predict', primary=True, disabled=True),
]),
ui.message_bar(type='warning', text='Training will take a few seconds'),
ui.text(content=''),
ui.text(content='')
]
)
await q.page.save()
def init(q: Q):
q.client.primary_color = '$blue'
q.client.secondary_color = '$cyan'
q.client.tertiary_color = '$azure'
q.page['meta'] = ui.meta_card(
box='',
title='Telco Churn Analytics',
layouts=[
ui.layout(breakpoint='xs',
zones=[
ui.zone('header'),
ui.zone('title'),
ui.zone('content',
zones=[
ui.zone('code'),
ui.zone('top',
direction=ui.ZoneDirection.ROW,
zones=[
ui.zone('top-plot',
size='70%'),
ui.zone('top-stats')
]),
ui.zone('middle',
direction=ui.ZoneDirection.ROW),
])
])
])
q.page['header'] = ui.header_card(
box='header',
title='Telecom Churn Analytics',
subtitle='EDA & Churn Modeling with AutoML & Wave',
nav=[
ui.nav_group('Main Menu',
items=[
ui.nav_item(name='analysis', label='Analysis'),
ui.nav_item(name='code',
label='Application Code'),
])
])
q.page['title'] = ui.section_card(
box='title',
title='Customer profiles from model predictions',
subtitle='Customer: No customer chosen',
items=[
# TODO: Replace with dropdown after https://github.com/h2oai/wave/pull/303 merged.
ui.picker(name='customers',
label='Customer Phone Number',
choices=[
ui.choice(name=str(phone), label=str(phone))
for phone in df['Phone']
],
max_choices=1,
trigger=True),
ui.toggle(name='theme', label='Dark Theme', trigger=True)
])
def get_user_input_items(sales_data, user_inputs, progress=False):
return [
ui.text_l('**Select Area of Interest**'),
ui.dropdown(
name='stores',
label='Store IDs',
values=[str(x) for x in user_inputs.stores],
choices=[ui.choice(name=str(x), label=str(x)) for x in sales_data.stores_unique],
tooltip='Select the Stores to include in the prediction',
trigger=True,
),
ui.text_xs('⠀'),
ui.dropdown(
name='departments',
label='Product IDs',
values=[str(x) for x in user_inputs.departments],
choices=[ui.choice(name=str(x), label=str(x)) for x in sales_data.departments_unique],
tooltip='Select the Products to include in the prediction',
trigger=True,
),
ui.frame(content=' ', height="40px"),
ui.text_l('**Generate Sales Forecast**'),
ui.slider(
name='n_forecast_weeks',
label='Number of Weeks',
min=0,
max=len(sales_data.prediction_dates) - 1,
step=1,
value=user_inputs.n_forecast_weeks,
trigger=True,
tooltip='Select the number of weeks into the future to predict'
),
ui.text_xs('⠀'),
ui.button(
name='reset',
label='Reset',
primary=True,
tooltip='Click to reset all values to defaults'
),
ui.text_xs('⠀'),
ui.progress(label='', caption='', visible=progress),
]
def add_sidebar_card(box, customer_ids):
id_choices = [ui.choice(_, "Customer:" + str(_)) for _ in customer_ids]
return ui.form_card(box=box,
items=[
ui.text_xl(content='Select Customer Record'),
ui.dropdown(name='customer_id',
label='CustomerID',
choices=id_choices),
ui.button(name='predict',
label='Generate',
primary=True)
])
async def serve(q: Q):
if q.args.show_inputs:
q.page['example'].items = [
ui.text(f'selected={q.args.checklist}'),
ui.button(name='show_form', label='Back', primary=True),
]
else:
q.page['example'] = ui.form_card(box='1 1 4 10', items=[
ui.checklist(name='checklist', label='Choices',
choices=[ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']]),
ui.button(name='show_inputs', label='Submit', primary=True),
])
await q.page.save()
def get_user_input_items(sales_data, user_inputs, progress=False):
return [
ui.text_l('**Prediction Configuration**'),
ui.dropdown(
name='stores',
label='Store IDs',
values=[str(x) for x in user_inputs.stores],
choices=[
ui.choice(name=str(x), label=str(x))
for x in sales_data.stores_unique
],
trigger=True,
),
ui.dropdown(
name='departments',
label='Product IDs',
values=[str(x) for x in user_inputs.departments],
choices=[
ui.choice(name=str(x), label=str(x))
for x in sales_data.departments_unique
],
trigger=True,
),
ui.slider(
name='n_forecast_weeks',
label='Weeks to predict',
min=0,
max=len(sales_data.prediction_dates) - 1,
step=1,
value=user_inputs.n_forecast_weeks,
trigger=True,
),
ui.button(name='reset',
label='Reset',
primary=True,
tooltip='Click to reset all values to defaults'),
ui.progress(label='', caption='', visible=progress),
]
def render_home(q: Q):
q.page["left_panel"] = ui.form_card(box=config.boxes['left_panel'], items=[
ui.text_xl("Hotel Reviews"),
ui.dropdown(
name="review_choice",
label="Choose a review type",
placeholder=config.column_mapping[q.client.review] if q.client.review else "please select a review type",
choices=[
ui.choice(name=column, label=config.column_mapping[column])
for column in config.dataset[config.review_column_list]
],
trigger=True,
),
])
def add_sidebar_card(box, customer_ids, customer_names, customer_id, endpoint):
id_choices = [
ui.choice(str(id),
str(id) + ": " + name)
for id, name in zip(customer_ids, customer_names)
]
return ui.form_card(box=box,
items=[
ui.text_xl(content='Select Customer'),
ui.dropdown(name='customer_id',
label='Customer',
choices=id_choices,
value=customer_id),
ui.textbox(name='endpoint',
label='MLOps Endpoint',
value=endpoint,
placeholder="URL to MLOps deployment"),
ui.button(name='predict',
label='Generate',
primary=True)
])
async def render(self, q: Q):
"""
Render card in Wave.
Args:
q: Wave server
"""
entity_choices = [
ui.choice(name=str(x), label=str(x)) for x in self.choice_ents
]
card = ui.form_card(box=self.box,
items=[
ui.picker(name='select_ents',
label='Entities',
choices=entity_choices,
values=self.select_ents,
trigger=True)
],
title=self.title,
commands=self.commands)
q.page[self.name] = card
async def serve(q: Q):
if q.args.show_inputs:
q.page['example'].items = [
ui.text(f'selected={q.args.picker}'),
ui.button(name='show_form', label='Back', primary=True),
]
else:
q.page['example'] = ui.form_card(
box='1 1 4 10',
items=[
ui.picker(name='picker',
label='Place an order (try Spam, Eggs or Ham):',
choices=[
ui.choice(name='spam', label='Spam'),
ui.choice(name='eggs', label='Eggs'),
ui.choice(name='ham', label='Ham'),
ui.choice(name='cheese', label='Cheese'),
ui.choice(name='beans', label='Beans'),
ui.choice(name='toast', label='Toast'),
]),
ui.button(name='show_inputs', label='Submit', primary=True),
])
await q.page.save()
async def show_mint_dashboard(q: Q):
q.page['meta'] = ui.meta_card(
box='',
layouts=[
ui.layout(breakpoint='xl',
width='1200px',
zones=[
ui.zone('header'),
ui.zone('main_section'),
ui.zone('overview',
direction=ui.ZoneDirection.ROW,
size='425px'),
ui.zone('tickers',
direction=ui.ZoneDirection.ROW,
size='175px'),
ui.zone('transactions_section'),
ui.zone('transactions',
direction=ui.ZoneDirection.ROW,
size='400px'),
ui.zone('footer'),
])
])
q.page['header'] = ui.header_card(box='header',
title='H2O Wave Demo',
subtitle='Mint Dashboard',
nav=global_nav)
q.page['main_section'] = ui.section_card(
box='main_section',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.tabs(
name='currency',
value='option0',
items=[
ui.tab(name=f'option{i}', label=next(sample_term))
for i in range(4)
],
)
],
)
trend_date = generate_time_series(60)
trend_price = generate_random_walk(2000, 8000, 0.2)
q.page['trends'] = ui.form_card(
box=ui.box('overview', order=1, size=4),
title=next(sample_title),
items=[
ui.inline(inset=True,
items=[
ui.checkbox(name='sent',
label=next(sample_term),
value=True),
ui.checkbox(name='received',
label=next(sample_term)),
ui.dropdown(name='distribution',
label='',
value='option0',
choices=[
ui.choice(name=f'option{i}',
label=next(sample_term))
for i in range(5)
]),
]),
ui.visualization(
plot=ui.plot([
ui.mark(type='line',
x_scale='time',
x='=date',
y='=price',
color='$mint',
curve=ui.MarkCurve.STEP),
]),
data=data(fields=['date', 'price'],
rows=[(next(trend_date), next(trend_price))
for i in range(60)],
pack=True),
height='215px',
),
ui.stats(items=[
ui.stat(label=next(sample_term), value=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_amount)),
ui.stat(label=next(sample_term), value=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
],
justify='between',
inset=True),
])
stock_dates = generate_time_series(300)
stock_prices = generate_random_walk()
q.page['exchange_rate'] = ui.tall_series_stat_card(
box=ui.box('overview', order=2),
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_amount),
plot_type=ui.TallSeriesStatCardPlotType.AREA,
plot_color='$mint',
plot_category='date',
plot_value='price',
plot_curve=ui.TallSeriesStatCardPlotCurve.STEP,
plot_zero_value=0,
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['symbol1'] = ui.tall_series_stat_card(
box=ui.box('tickers', order=1),
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_percent),
plot_type=ui.TallSeriesStatCardPlotType.AREA,
plot_color='$mint',
plot_category='date',
plot_value='price',
plot_curve=ui.TallSeriesStatCardPlotCurve.STEP,
plot_zero_value=0,
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['symbol2'] = ui.tall_series_stat_card(
box=ui.box('tickers', order=2),
title=next(sample_title),
value=next(sample_percent),
aux_value=next(sample_title),
plot_type=ui.TallSeriesStatCardPlotType.AREA,
plot_color='$green',
plot_category='date',
plot_value='price',
plot_curve=ui.TallSeriesStatCardPlotCurve.STEP,
plot_zero_value=0,
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['symbol3'] = ui.tall_series_stat_card(
box=ui.box('tickers', order=3),
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_percent),
plot_type=ui.TallSeriesStatCardPlotType.AREA,
plot_color='$mint',
plot_category='date',
plot_value='price',
plot_curve=ui.TallSeriesStatCardPlotCurve.STEP,
plot_zero_value=0,
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['transactions_section'] = ui.section_card(
box='transactions_section',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.tabs(
name='time_period',
value='option0',
items=[
ui.tab(name=f'option{i}', label=next(sample_term))
for i in range(6)
],
link=True,
),
],
)
q.page['transactions'] = ui.stat_table_card(
box=ui.box('transactions', order=1, size=2),
title=next(sample_title),
subtitle=next(sample_caption),
columns=[next(sample_term) for i in range(4)],
items=[
ui.stat_table_item(label=next(sample_title),
caption=f'{random.randint(1, 5)} hours ago',
values=[
next(sample_percent),
next(sample_amount),
next(sample_dollars)
],
icon=next(sample_icon),
icon_color='$mint') for i in range(6)
])
q.page['market'] = ui.stat_list_card(
box=ui.box('transactions', order=2),
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.stat_list_item(label=next(sample_term),
caption=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_percent),
value_color=next(sample_color)) for i in range(5)
],
)
q.page['footer'] = ui.footer_card(
box='footer', caption='(c) 2021 H2O.ai. All rights reserved.')
await q.page.save()
async def show_blue_dashboard(q: Q):
q.page['meta'] = ui.meta_card(
box='',
layouts=[
ui.layout(breakpoint='xl',
width='1200px',
zones=[
ui.zone('header', size='80px'),
ui.zone('title', size='0'),
ui.zone('top',
direction=ui.ZoneDirection.ROW,
size='200px'),
ui.zone('middle',
direction=ui.ZoneDirection.ROW,
size='385px'),
ui.zone('bottom',
direction=ui.ZoneDirection.ROW,
size='385px'),
ui.zone('footer', size='50px'),
])
])
q.page['header'] = ui.header_card(box='header',
title='H2O Wave Demo',
subtitle='Blue Dashboard',
nav=global_nav)
q.page['title'] = ui.section_card(
box='title',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.toggle(name='search', label=next(sample_term), value=True),
ui.dropdown(name='distribution',
label='',
value='option0',
choices=[
ui.choice(name=f'option{i}',
label=next(sample_term))
for i in range(5)
]),
ui.date_picker(name='target_date', label='', value='2020-12-25'),
],
)
sales_dates = generate_time_series(1000)
sales_values = generate_random_walk()
q.page['total_quantity'] = ui.tall_series_stat_card(
box=ui.box('top', order=1),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_title),
plot_type='area',
plot_color='$blue',
plot_category='date',
plot_value='quantity',
plot_zero_value=0,
plot_data=data(
fields=['date', 'quantity'],
rows=[(next(sales_dates), next(sales_values)) for i in range(30)],
pack=True,
),
)
q.page['total_cost'] = ui.tall_series_stat_card(
box=ui.box('top', order=2),
title=next(sample_term),
value=next(sample_amount),
aux_value=next(sample_percent),
plot_type='area',
plot_color='$blue',
plot_category='date',
plot_value='cost',
plot_zero_value=0,
plot_data=data(
fields=['date', 'cost'],
rows=[(next(sales_dates), next(sales_values)) for i in range(30)],
pack=True,
),
)
q.page['total_revenue'] = ui.tall_series_stat_card(
box=ui.box('top', order=3),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_title),
plot_type='area',
plot_color='$blue',
plot_category='date',
plot_value='revenue',
plot_zero_value=0,
plot_data=data(
fields=['date', 'revenue'],
rows=[(next(sales_dates), next(sales_values)) for i in range(30)],
pack=True,
),
)
q.page['total_profit'] = ui.tall_series_stat_card(
box=ui.box('top', order=4),
title=next(sample_term),
value=next(sample_amount),
aux_value=next(sample_title),
plot_type='area',
plot_color='$blue',
plot_category='date',
plot_value='profit',
plot_zero_value=0,
plot_data=data(
fields=['date', 'profit'],
rows=[(next(sales_dates), next(sales_values)) for i in range(30)],
pack=True,
),
)
ytd_revenue = generate_random_walk(0, 10000, 0.5)
q.page['revenue_by_customer'] = ui.plot_card(
box='middle',
title=next(sample_title),
data=data(
fields=['channel', 'sessions'],
rows=[(next(sample_term), next(ytd_revenue)) for i in range(10)],
pack=True,
),
plot=ui.plot([
ui.mark(type='interval',
x='=sessions',
y='=channel',
y_min=0,
color='$blue')
]))
months = generate_sequence(['Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'])
q.page['ytd_revenue'] = ui.plot_card(
box=ui.box(zone='middle', width='66%', order=2),
title=next(sample_title),
data=data(fields=['month', 'channel', 'revenue'],
rows=[(next(months), 'Online', next(ytd_revenue))
for i in range(6)] +
[(next(months), 'In-store', next(ytd_revenue))
for i in range(6)],
pack=True),
plot=ui.plot([
ui.mark(type='interval',
x='=month',
y='=revenue',
color='=channel',
dodge='auto',
y_min=0,
color_range='$cyan $blue')
]))
q.page['top_products'] = ui.stat_list_card(
box='bottom',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.stat_list_item(label=next(sample_term),
caption=next(sample_title),
value=next(sample_dollars),
icon=next(sample_icon),
icon_color=next(sample_color)) for i in range(5)
],
)
q.page['recent_earnings'] = ui.stat_table_card(
box=ui.box(zone='bottom', width='66%', order=2),
title=next(sample_title),
subtitle=next(sample_caption),
columns=['Date', 'Sales', 'Earnings', 'Taxes'],
items=[
ui.stat_table_item(label=next(sample_title),
values=[
next(sample_dollars),
next(sample_percent),
next(sample_amount)
]) for i in range(8)
])
q.page['footer'] = ui.footer_card(
box='footer', caption='(c) 2021 H2O.ai. All rights reserved.')
await q.page.save()
async def serve(q: Q):
if 'H2O_CLOUD_ENVIRONMENT' not in os.environ:
# show appropriate message if app is not running on cloud
q.page['example'] = ui.form_card(box='1 1 -1 -1',
items=form_unsupported())
elif q.args.train:
# get DAI instance name
copy_expando(q.args, q.client)
for dai_instance in q.client.dai_instances:
if dai_instance['id'] == int(q.client.dai_instance_id):
q.client.dai_instance_name = dai_instance['name']
# set DAI model details
q.client.model_details = dai_experiment_url(q.client.dai_instance_id,
q.client.dai_instance_name)
# show training progress and details
q.page['example'].items = form_training_progress(q)
await q.page.save()
# train WaveML Model using Driverless AI
q.client.wave_model = await q.run(
func=build_model,
train_df=q.client.train_df,
target_column='target',
model_type=ModelType.DAI,
refresh_token=q.auth.refresh_token,
_steam_dai_instance_name=q.client.dai_instance_name,
_dai_accuracy=1,
_dai_time=1,
_dai_interpretability=10)
# update DAI model details
q.client.project_id = q.client.wave_model.project_id
q.client.model_details += f'<br />{mlops_deployment_url(q.client.project_id)}'
# download AutoDoc
path_autodoc = save_autodoc(project_id=q.client.project_id,
output_dir_path='.',
refresh_token=q.auth.refresh_token)
q.client.path_autodoc, *_ = await q.site.upload([path_autodoc])
# show model outputs
q.page['example'].items = form_training_completed(q)
else:
# prepare sample train and test dataframes
data = load_wine(as_frame=True)['frame']
q.client.train_df, q.client.test_df = train_test_split(data,
train_size=0.8)
# DAI instances
q.client.dai_instances = list_dai_instances(
refresh_token=q.auth.refresh_token)
q.client.choices_dai_instances = [
ui.choice(name=str(x['id']),
label=f'{x["name"]} ({x["status"].capitalize()})',
disabled=x['status'] != 'running')
for x in q.client.dai_instances
]
running_dai_instances = [
x['id'] for x in q.client.dai_instances if x['status'] == 'running'
]
q.client.disable_training = False if running_dai_instances else True
q.client.dai_instance_id = str(
running_dai_instances[0]) if running_dai_instances else ''
# display ui
q.page['example'] = ui.form_card(box='1 1 -1 -1',
items=form_default(q))
await q.page.save()
# Form / Choice Group
# Use #choice groups to let users select one option from two or more choices.
# #form #choice_group
# ---
from h2o_wave import main, app, Q, ui
choices = [
ui.choice('A', 'Option A'),
ui.choice('B', 'Option B'),
ui.choice('C', 'Option C', disabled=True),
ui.choice('D', 'Option D'),
]
@app('/demo')
async def serve(q: Q):
if q.args.show_inputs:
q.page['example'].items = [
ui.text(f'selected={q.args.choice_group}'),
ui.button(name='show_form', label='Back', primary=True),
]
else:
q.page['example'] = ui.form_card(box='1 1 4 10', items=[
ui.choice_group(name='choice_group', label='Pick one', value='B', required=True, choices=choices),
ui.button(name='show_inputs', label='Submit', primary=True),
])
await q.page.save()
async def showProducts(q: Q):
global filter_product
global filter_manufacturer
global filter_supplier
global unit_measure
global gqty
items = [ui.tabs(name='menu', value=q.args.menu, items=tabs)]
print('---------------------------')
print('== PRODUCT TAB == ')
print('q.args.show_tables: ' + str(q.args.show_tables) +
', q.args.show_inputs: ' + str(q.args.show_inputs))
## the user have clicked 'Add' button but haven't clicked 'Submit' button yet
if (q.args.show_tables == None or q.args.show_tables == False) and (
q.args.show_inputs or q.args.product or q.args.manufacturer
or q.args.supplier or q.args.qty):
## need to get manufacturer data first (later used for the dropdown when adding new supplier)
df_m = pd.DataFrame(l_manufacturers,
columns=['manufacturer', 'product'])
df_s = pd.DataFrame(l_suppliers,
columns=['supplier', 'manufacturer', 'product'])
## if there is no manufacturer data
if len(df_m) == 0:
items.extend([
ui.message_bar(type='info',
text='Try adding manufacturer first'),
ui.button(name='goto_manufacturer',
label='Close',
primary=True)
])
## if there is no supplier data
elif len(df_s) == 0:
items.extend([
ui.message_bar(type='info', text='Try adding supplier first'),
ui.button(name='goto_supplier', label='Close', primary=True)
])
## if there is data on manufacturer and supplier, when the user click 'Add Product' button
else:
items.append(ui.text_xl(content='Add Product'))
print('q.args.product: ' + str(q.args.product) +
', q.args.manufacturer: ' + str(q.args.manufacturer) +
', q.args.supplier: ' + str(q.args.supplier))
if q.args.product and (filter_product == None
or q.args.product != filter_product):
filter_product = q.args.product
filter_manufacturer = None
filter_supplier = None
unit_measure = None
# selling_price = None
gqty = None
elif q.args.manufacturer and (
filter_manufacturer == None
or q.args.manufacturer != filter_manufacturer):
filter_manufacturer = q.args.manufacturer
filter_supplier = None
unit_measure = None
# selling_price = None
gqty = None
elif q.args.supplier and (filter_supplier == None
or q.args.supplier != filter_supplier):
filter_supplier = q.args.supplier
unit_measure = None
# selling_price = None
gqty = None
if q.args.qty:
gqty = q.args.qty
print(filter_product, filter_manufacturer, filter_supplier)
## PRODUCT
if filter_product != None:
items.append(
ui.dropdown(name='product',
label='Product',
choices=[
ui.choice(name=x, label=x)
for x in df_m['product'].unique()
],
trigger=True,
value=filter_product))
tmp_m = df_m[df_m['product'] ==
q.args.product]['manufacturer'].unique()
else:
items.append(
ui.dropdown(name='product',
label='Product',
choices=[
ui.choice(name=x, label=x)
for x in df_m['product'].unique()
],
trigger=True))
tmp_m = df_m['manufacturer'].unique()
## MANUFACTURER
if filter_manufacturer != None:
items.append(
ui.dropdown(
name='manufacturer',
label='Manufacturer',
choices=[ui.choice(name=x, label=x) for x in tmp_m],
trigger=True,
value=filter_manufacturer))
tmp_s = df_s[(df_s['product'] == filter_product)
& (df_s['manufacturer'] == filter_manufacturer
)]['supplier'].unique()
else:
items.append(
ui.dropdown(
name='manufacturer',
label='Manufacturer',
choices=[ui.choice(name=x, label=x) for x in tmp_m],
trigger=True))
tmp_s = df_s['supplier'].unique()
## SUPPLIER
if filter_supplier != None:
items.append(
ui.dropdown(
name='supplier',
label='Supplier',
choices=[ui.choice(name=x, label=x) for x in tmp_s],
trigger=True,
value=filter_supplier))
# selling_price = df_s[(df_s['product']==filter_product)&(df_s['manufacturer']==filter_manufacturer)
# &(df_s['supplier']==filter_supplier)]['selling_price'].values[0]
# unit_measure = df_s[(df_s['product']==filter_product)&(df_s['manufacturer']==filter_manufacturer)
# &(df_s['supplier']==filter_supplier)]['uom'].values[0]
else:
items.append(
ui.dropdown(
name='supplier',
label='Supplier',
choices=[ui.choice(name=x, label=x) for x in tmp_s],
trigger=True))
# selling_price = None
# items.append(ui.date_picker(name='purchase_date', label='Purchase Date'))
# items.append(ui.textbox(name='qty', label='Qty'))
# ## SELLING PRICE
# if selling_price!=None:
# items.append(ui.textbox(name='selling_price', label='Selling Price', value = str(selling_price)))
# else:
# items.append(ui.textbox(name='selling_price', label='Selling Price'))
# ## UOM
# if unit_measure!=None:
# items.append(ui.textbox(name='uom', label='Unit of Measurement', value = unit_measure, readonly = True))
# else:
# items.append(ui.dropdown(name='uom', label='Unit of Measurement', choices=[
# ui.choice(name=x, label=x) for x in uom
# ]))
# items.extend([
# # ui.date_picker(name='mfg_date', label='Mfg Date'),
# # ui.date_picker(name='exp_date', label='Exp Date'),
# ui.textbox(name='selling_price', label='Selling Price'),
# # ui.textbox(name='operational_cost', label='Operational Cost'),
# # ui.textbox(name='lvl', label='Order Point by level(%)'),
# # ui.textbox(name='schedule', label='Order Point Schedule (days)'),
# # ui.textbox(name='schedule_qty', label='Scheduled Qty'),
# # ui.textbox(name='rate', label='Avg. Consumption'),
# # ui.dropdown(name='freq', label='Consumption Frequency', choices=[
# # ui.choice(name=x, label=x, value='daily', readonly=True) for x in consumption
# # ]),
# ui.button(name='show_tables', label='Submit', primary=True)])
items.extend([
# ui.textbox(name='selling_price', label='Selling Price'),
ui.button(name='show_tables', label='Submit', primary=True)
])
else: ## first iteration goes here
filter_product = None
filter_manufacturer = None
filter_supplier = None
unit_measure = None
selling_price = None
gqty = None
## if q.args.show_tables == True
if q.args.show_tables:
# l_products.append([q.args.product, q.args.manufacturer, q.args.supplier, q.args.purchase_date, q.args.qty,
# q.args.uom, q.args.selling_price, q.args.mfg_date, q.args.exp_date, q.args.selling_price,
# q.args.operational_cost, q.args.lvl, q.args.schedule, q.args.schedule_qty, q.args.rate])
# p = Products(q.args.product, q.args.manufacturer, q.args.supplier, q.args.purchase_date, q.args.qty,
# q.args.uom, q.args.selling_price, q.args.mfg_date, q.args.exp_date, q.args.selling_price,
# q.args.operational_cost, q.args.lvl, q.args.schedule, q.args.schedule_qty, q.args.rate)
# l_products.append([q.args.product, q.args.manufacturer, q.args.supplier,
# q.args.uom])
l_products.append(
[q.args.product, q.args.manufacturer, q.args.supplier])
# p = Products(q.args.product, q.args.manufacturer, q.args.supplier,
# q.args.uom)
p = Products(q.args.product, q.args.manufacturer, q.args.supplier)
products.append(p)
items.append(
ui.message_bar(type='success',
text='You have successfully added a product'))
## if there is a product data
if len(products) > 0:
items.append(
ui.table(
name='products',
columns=column_product_table,
rows=[
ui.table_row(
name=product.id,
# cells=[product.product, product.manufacturer, product.supplier, product.selling_price,
# product.uom]
cells=[
product.product, product.manufacturer,
product.supplier
]) for product in products
],
groupable=True,
downloadable=True,
resettable=True,
height='500px'))
else: ## if there is no product data
items.append(ui.text_l(content='No Product found'))
# items.append(ui.button(name='show_inputs', label='Add Product', primary=True))
items.append(
ui.buttons([
ui.button(name='show_inputs',
label='Add Product',
primary=True),
ui.button(name='delete_button', label='Delete Product'),
ui.button(name='edit_button', label='Edit Product'),
]))
q.page['example'] = ui.form_card(box='1 2 -1 -1', items=items)
await q.page.save()
def init_ui(q: Q):
q.page['meta'] = ui.meta_card(
title='Shopping Cart Recomendations',
box='',
layouts=[
ui.layout(breakpoint='xs',
zones=[
ui.zone('header', size='80px'),
ui.zone('cart', size='250px'),
ui.zone('trending'),
ui.zone('suggestions'),
]),
ui.layout(
breakpoint='m',
zones=[
ui.zone('header', size='80px'),
ui.zone('body',
size='1000px',
direction=ui.ZoneDirection.ROW,
zones=[
ui.zone('cart', size='300px'),
ui.zone('right-pane',
direction=ui.ZoneDirection.COLUMN,
zones=[
ui.zone('trending', size='600px'),
ui.zone('suggestions'),
]),
]),
]),
ui.layout(breakpoint='xl',
width='1600px',
zones=[
ui.zone('header', size='80px'),
ui.zone('body',
size='750px',
direction=ui.ZoneDirection.ROW,
zones=[
ui.zone('cart', size='300px'),
ui.zone('trending'),
ui.zone('suggestions'),
])
])
])
q.page.add(
'header',
ui.header_card(
box='header',
title=config.title,
subtitle=config.subtitle,
icon=config.icon,
icon_color=config.icon_color,
))
q.page['suggestions'] = ui.form_card(box='suggestions', items=[])
q.page['trending'] = ui.form_card(box='trending', items=[])
q.page['cart'] = ui.form_card(
box='cart',
items=[
ui.separator('Cart'),
ui.text('Search and add products to the cart'),
ui.picker(
name='cart_products',
choices=[
ui.choice(name=str(x), label=str(x))
for x in get_products_list()
],
values=q.client.cart_products,
trigger=True,
),
ui.button(name='toggle_theme', label='Toggle Theme', primary=True)
])
q.client.theme = 'default'
convert_plot_to_html,
generate_figure_pie_of_target_percent,
get_image_from_matplotlib,
tall_stat_card_dollars,
wide_stat_card_dollars,
)
from .utils import python_code_content
config = Configuration()
churn_predictor = ChurnPredictor()
df = pd.read_csv(config.testing_data_url).head(40)
df.fillna(config.def_column_values, inplace=True)
df.dropna(subset=config.mandatory_columns, inplace=True)
phone_choices = [
ui.choice(name=str(phone), label=str(phone))
for phone in df[config.id_column]
]
def render_header(q: Q):
q.page["title"] = ui.header_card(box=config.boxes["banner"],
title=config.title,
subtitle=config.subtitle,
icon=config.icon,
icon_color=config.color,
nav=config.global_nav)
def show_profile(q: Q):
del q.page["content"]
async def show_cyan_dashboard(q: Q):
q.page['meta'] = ui.meta_card(box='', layouts=[
ui.layout(
breakpoint='xl',
width='1200px',
zones=[
ui.zone('header', size='0'),
ui.zone('body', direction=ui.ZoneDirection.ROW, zones=[
ui.zone('content', size='75%', zones=[
ui.zone('top', size='600px'),
ui.zone('middle', size='300px', direction=ui.ZoneDirection.ROW, zones=[
ui.zone('middle_left'),
ui.zone('middle_right'),
]),
ui.zone('bottom', size='500px'),
]),
ui.zone('sidebar', size='25%'),
]),
ui.zone('footer', size='0'),
]
)
])
q.page['header'] = ui.header_card(box='header', title='H2O Wave Demo', subtitle='Cyan Dashboard',
nav=global_nav)
q.page['section'] = ui.section_card(
box=ui.box('top', order=1, size=0),
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.toggle(name='when', label=next(sample_term), value=False),
ui.toggle(name='what', label=next(sample_term), value=True),
]
)
trend_date = generate_time_series(300)
trend_price = generate_random_walk(2000, 8000, 0.2)
q.page['sales_overview'] = ui.form_card(
box=ui.box('top', order=2),
title=next(sample_title),
items=[
ui.stats(items=[
ui.stat(label=next(sample_term), value=next(sample_percent), caption=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_dollars), caption=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_amount), caption=next(sample_percent)),
ui.stat(label=next(sample_term), caption=next(sample_caption)),
], inset=True),
ui.visualization(
plot=ui.plot([
ui.mark(type='area', x_scale='time', x='=date', y='=price', color='$cyan'),
]),
data=data(
fields=['date', 'price'],
rows=[(next(trend_date), next(trend_price)) for i in range(120)],
pack=True
),
height='350px',
),
],
)
q.page['ticket_sales'] = ui.form_card(
box=ui.box('middle_left'),
title=next(sample_title),
items=[
ui.visualization(
plot=ui.plot([
ui.mark(type='interval', x_scale='time', x='=date', y='=price', color='$cyan'),
]),
data=data(
fields=['date', 'price'],
rows=[(next(trend_date), next(trend_price)) for i in range(120)],
pack=True
),
height='150px',
),
ui.stats(items=[
ui.stat(label=next(sample_term), value=next(sample_percent)) for i in range(4)
], justify='between', inset=True),
],
)
q.page['events_hosted'] = ui.wide_bar_stat_card(
box=ui.box('middle_right', order=1),
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_percent),
progress=random.random(),
plot_color='$cyan',
)
q.page['points_earned'] = ui.wide_bar_stat_card(
box=ui.box('middle_right', order=2),
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_percent),
progress=random.random(),
plot_color='$cyan',
)
q.page['points_given'] = ui.wide_bar_stat_card(
box=ui.box('middle_right', order=3),
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_percent),
progress=random.random(),
plot_color='$cyan',
)
session_count = generate_random_walk(1000, 8000)
q.page['event_poll'] = ui.form_card(
box='bottom',
title=next(sample_title),
items=[
ui.inline(items=[
ui.dropdown(name='region', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
ui.dropdown(name='age', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
ui.dropdown(name='response', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
]),
ui.visualization(
plot=ui.plot([
ui.mark(type='interval', x='=sessions', y='=channel', y_min=0, color='$cyan')
]),
data=data(
fields=['channel', 'sessions'],
rows=[(next(sample_term), next(session_count)) for i in range(10)],
pack=True,
),
height='350px',
),
],
)
q.page['sidebar_section'] = ui.section_card(
box=ui.box('sidebar', order=1, size='0'),
title=next(sample_title),
subtitle=next(sample_caption),
)
q.page['filter'] = ui.form_card(
box=ui.box('sidebar', height='335px', order=2),
title=next(sample_title),
items=[
ui.dropdown(name='region', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
ui.dropdown(name='age', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
ui.dropdown(name='response', label=next(sample_term), value='option0', choices=[
ui.choice(name=f'option{i}', label=next(sample_term)) for i in range(5)
]),
ui.checkbox(name='plural', label=next(sample_title), value=True),
ui.checkbox(name='annual', label=next(sample_title), value=True),
],
)
event_icon = generate_random_choice(['MusicInCollection', 'Video', 'TVMonitor'])
q.page['upcoming_events'] = ui.stat_list_card(
box=ui.box('sidebar', order=3),
title=next(sample_title),
subtitle=next(sample_caption),
items=[ui.stat_list_item(label=next(sample_title), caption=next(sample_caption),
aux_value=f'{random.randint(1, 59)}m',
icon=next(event_icon)) for i in range(10)],
)
q.page['footer'] = ui.footer_card(box='footer', caption='(c) 2021 H2O.ai. All rights reserved.')
await q.page.save()
# Form / Choice Group / Inline
# Use #choice groups to let users select one option from two or more choices and inline to present the choices horizontally.
# #form #choice_group #inline
# ---
from h2o_wave import main, app, Q, ui
choices = [
ui.choice('A', 'Option A'),
ui.choice('B', 'Option B'),
ui.choice('C', 'Option C', disabled=True),
ui.choice('D', 'Option D'),
ui.choice('E', 'Option E'),
ui.choice('F', 'Option F'),
ui.choice('G', 'Option H'),
ui.choice('I', 'Option I'),
]
@app('/demo')
async def serve(q: Q):
if q.args.show_inputs:
q.page['example'].items = [
ui.text(f'selected={q.args.choice_group}'),
ui.button(name='show_form', label='Back', primary=True),
]
else:
q.page['example'] = ui.form_card(box='1 1 4 10',
items=[
ui.choice_group(
name='choice_group',
inline=True,
def get_tab_content(category: str):
# Return a checklist of dummy items.
items = [f'{category.title()} {i}' for i in range(1, 11)]
return ui.checklist(name='items', choices=[ui.choice(name=item, label=item) for item in items])
def choices_from_list(ls: list) -> list:
"""
List of values as list of Q ui.choice.
"""
return [ui.choice(name=str(x), label=str(x)) for x in ls]
async def show_orange_dashboard(q: Q):
q.page['meta'] = ui.meta_card(
box='',
layouts=[
ui.layout(breakpoint='xl',
width='1200px',
zones=[
ui.zone('header'),
ui.zone('control'),
ui.zone('top',
direction=ui.ZoneDirection.ROW,
size='385px',
zones=[
ui.zone('top_left',
direction=ui.ZoneDirection.ROW,
size='66%'),
ui.zone('top_right'),
]),
ui.zone('middle',
direction=ui.ZoneDirection.ROW,
size='400px'),
ui.zone('bottom',
direction=ui.ZoneDirection.ROW,
size='200px'),
ui.zone('footer'),
])
])
q.page['header'] = ui.header_card(box='header',
title='H2O Wave Demo',
subtitle='Orange Dashboard',
nav=global_nav)
q.page['section'] = ui.section_card(
box='control',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.checkbox(name='search', label=next(sample_title), value=True),
ui.dropdown(name='distribution',
label='',
value='option0',
choices=[
ui.choice(name=f'option{i}',
label=next(sample_term))
for i in range(5)
]),
ui.dropdown(name='source',
label='',
value='option0',
choices=[
ui.choice(name=f'option{i}',
label=next(sample_term))
for i in range(5)
]),
ui.dropdown(name='range',
label='',
value='option0',
choices=[
ui.choice(name=f'option{i}',
label=next(sample_term))
for i in range(5)
]),
],
)
user_days = generate_time_series(30)
user_counts = generate_random_walk()
q.page['unique_impressions'] = ui.tall_series_stat_card(
box='top_left',
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_percent),
plot_type='interval',
plot_color='$orange',
plot_category='date',
plot_value='users',
plot_zero_value=0,
plot_data=data(
fields=['date', 'users'],
rows=[(next(user_days), next(user_counts)) for i in range(60)],
pack=True,
),
)
q.page['unique_clicks'] = ui.tall_series_stat_card(
box='top_left',
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_title),
plot_type='interval',
plot_color='$amber',
plot_category='date',
plot_value='users',
plot_zero_value=0,
plot_data=data(
fields=['date', 'users'],
rows=[(next(user_days), next(user_counts)) for i in range(60)],
pack=True,
),
)
q.page['popularity'] = ui.wide_series_stat_card(
box='top_right',
title=next(sample_term),
value=next(sample_percent),
aux_value=next(sample_amount),
plot_type='area',
plot_color='$tangerine',
plot_category='date',
plot_value='users',
plot_zero_value=0,
plot_data=data(
fields=['date', 'users'],
rows=[(next(user_days), next(user_counts)) for i in range(60)],
pack=True,
),
)
q.page['search_traffic'] = ui.wide_series_stat_card(
box='top_right',
title=next(sample_term),
value=next(sample_percent),
aux_value=next(sample_dollars),
plot_type='interval',
plot_color='$tangerine',
plot_category='date',
plot_value='users',
plot_zero_value=0,
plot_data=data(
fields=['date', 'users'],
rows=[(next(user_days), next(user_counts)) for i in range(60)],
pack=True,
),
)
q.page['social_media_traffic'] = ui.wide_series_stat_card(
box='top_right',
title=next(sample_title),
value='68K',
aux_value='Down 6%',
plot_type='area',
plot_color='$tangerine',
plot_category='date',
plot_value='users',
plot_zero_value=0,
plot_data=data(
fields=['date', 'users'],
rows=[(next(user_days), next(user_counts)) for i in range(60)],
pack=True,
),
)
audience_days1 = generate_time_series(60)
audience_days2 = generate_time_series(60)
audience_hits1 = generate_random_walk(10000, 20000, 0.2)
audience_hits2 = generate_random_walk(8000, 15000)
q.page['stats'] = ui.form_card(
box='middle',
title=next(sample_title),
items=[
ui.stats(items=[
ui.stat(label=next(sample_term), value=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_amount)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_amount)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_percent)),
],
justify=ui.StatsJustify.BETWEEN,
inset=True),
ui.visualization(
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=visitors',
color='=site',
color_range='$orange $amber',
curve=ui.MarkCurve.SMOOTH),
ui.mark(type='line',
x_scale='time',
x='=date',
y='=visitors',
color='=site',
color_range='$orange $amber',
curve=ui.MarkCurve.SMOOTH),
]),
data=data(
fields=['site', 'date', 'visitors'],
rows=[
('Online', next(audience_days1), next(audience_hits1))
for i in range(60)
] +
[('In-store', next(audience_days2), next(audience_hits2))
for i in range(60)],
pack=True),
height='240px',
)
],
)
q.page['click_through'] = ui.large_stat_card(
box='bottom',
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_dollars),
caption=' '.join([next(sample_caption) for i in range(3)]),
)
q.page['view_through'] = ui.large_stat_card(
box='bottom',
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_dollars),
caption=' '.join([next(sample_caption) for i in range(3)]),
)
q.page['total_conversions'] = ui.large_stat_card(
box='bottom',
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_dollars),
caption=' '.join([next(sample_caption) for i in range(3)]),
)
q.page['footer'] = ui.footer_card(
box='footer', caption='(c) 2021 H2O.ai. All rights reserved.')
await q.page.save()
async def serve(q: Q):
q.page['example'] = ui.form_card(box='1 1 4 10', items=[
ui.text_xl(content='Extra-large text, for headings.'),
ui.text_l(content='Large text, for sub-headings.'),
ui.text_m(content='Body text, for paragraphs and other content.'),
ui.text_s(content='Small text, for small print.'),
ui.text_xs(content='Extra-small text, for really small print.'),
ui.separator(label='A separator sections forms'),
ui.progress(label='A progress bar'),
ui.progress(label='A progress bar'),
ui.message_bar(type='success', text='Message bar'),
ui.textbox(name='textbox', label='Textbox'),
ui.label(label='Checkboxes'),
ui.checkbox(name='checkbox1', label='A checkbox'),
ui.checkbox(name='checkbox1', label='Another checkbox'),
ui.checkbox(name='checkbox1', label='Yet another checkbox'),
ui.toggle(name='toggle', label='Toggle'),
ui.choice_group(name='choice_group', label='Choice group', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.checklist(name='checklist', label='Checklist', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.dropdown(name='dropdown', label='Dropdown', choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.dropdown(name='dropdown', label='Multi-valued Dropdown', values=[], choices=[
ui.choice(name=x, label=x) for x in ['Egg', 'Bacon', 'Spam']
]),
ui.combobox(name='combobox', label='Combobox', choices=['Choice 1', 'Choice 2', 'Choice 3']),
ui.slider(name='slider', label='Slider'),
ui.range_slider(name='range_slider', label='Range slider', max=99),
ui.spinbox(name='spinbox', label='Spinbox'),
ui.date_picker(name='date_picker', label='Date picker'),
ui.color_picker(name='color_picker', label='Color picker'),
ui.buttons([
ui.button(name='primary_button', label='Primary', primary=True),
ui.button(name='standard_button', label='Standard'),
ui.button(name='standard_disabled_button', label='Standard', disabled=True),
]),
ui.file_upload(name='file_upload', label='File upload'),
ui.table(name='table', columns=[
ui.table_column(name='col1', label='Column 1'),
ui.table_column(name='col2', label='Column 2'),
], rows=[
ui.table_row(name='row1', cells=['Text A', 'Text B']),
ui.table_row(name='row2', cells=['Text C', 'Text D']),
ui.table_row(name='row3', cells=['Text E', 'Text F']),
]),
ui.link(label='Link'),
ui.tabs(name='tabs', items=[
ui.tab(name='email', label='Mail', icon='Mail'),
ui.tab(name='events', label='Events', icon='Calendar'),
ui.tab(name='spam', label='Spam'),
]),
ui.expander(name='expander', label='Expander'),
ui.frame(path='https://example.com'),
ui.markup(content=html),
ui.template(
content=menu,
data=pack(dict(dishes=[
dict(name='Spam', price='$2.00'),
dict(name='Ham', price='$3.45'),
dict(name='Eggs', price='$1.75'),
]))
),
ui.picker(name='picker', label='Picker', choices=[
ui.choice('choice1', label='Choice 1'),
ui.choice('choice2', label='Choice 2'),
ui.choice('choice3', label='Choice 3'),
]),
ui.stepper(name='stepper', items=[
ui.step(label='Step 1', icon='MailLowImportance'),
ui.step(label='Step 2', icon='TaskManagerMirrored'),
ui.step(label='Step 3', icon='Cafe'),
]),
ui.visualization(
plot=ui.plot([ui.mark(type='interval', x='=product', y='=price', y_min=0)]),
data=data(fields='product price', rows=[(c, x) for c, x, _ in [f.next() for _ in range(n)]], pack=True),
),
ui.vega_visualization(
specification=spec,
data=data(fields=["a", "b"], rows=[
["A", rnd()], ["B", rnd()], ["C", rnd()],
["D", rnd()], ["E", rnd()], ["F", rnd()],
["G", rnd()], ["H", rnd()], ["I", rnd()]
], pack=True),
),
ui.button(name='show_inputs', label='Submit', primary=True),
])
await q.page.save()
async def showSuppliers(q: Q):
items = [ui.tabs(name='menu', value=q.args.menu, items=tabs)]
print('items in supplier: ' + str(items))
## if user clicks 'Add Supplier'
if q.args.show_inputs:
## need to get manufacturer data first (later used for the dropdown when addiing new supplier)
df_m = pd.DataFrame(l_manufacturers,
columns=['manufacturer', 'product'])
## if there is no Manufacter data, then the user should add manufacturer data first
if len(df_m) == 0:
items.extend([
ui.message_bar(type='info',
text='Try adding manufacturer first'),
ui.button(name='goto_manufacturer',
label='Close',
primary=True)
])
## there's a manufacturer data, then go here
else:
items.extend([
ui.text_xl(content='Add Supplier'),
ui.textbox(name='supplier', label='Supplier'),
ui.dropdown(
name='manufacturer',
label='Manufacturer',
choices=[ ## dropdown existing manufacturers
ui.choice(name=x, label=x)
for x in df_m['manufacturer'].unique()
]),
ui.dropdown(
name='product',
label='Product',
choices=[ ## dropdown existing items
ui.choice(name=x, label=x)
for x in df_m['product'].unique()
]), ## product should based on the what manufacturer have
# ui.dropdown(name='uom', label='Unit of Measurement', choices=[ ## dropdown unit of measurement based on UOM variable above
# ui.choice(name=x, label=x) for x in uom
# ]),
# ui.textbox(name='selling_price', label='Price'),
# ui.textbox(name='lead_time', label='Lead Time(days)'),
# ui.textbox(name='delivery_time', label='Delivery Time(days)'),
ui.button(name='show_tables', label='Submit',
primary=True) ## submit button
])
## user hasn't clicked 'Add suppliers' button
else:
## user have click has clicked 'Submit' button after adding supplier
if q.args.show_tables:
l_suppliers.append(
[q.args.supplier, q.args.manufacturer, q.args.product]) ## !!!
s = Suppliers(q.args.supplier, q.args.manufacturer, q.args.product)
suppliers.append(s)
items.append(
ui.message_bar(type='success',
text='You have successfully added a supplier'))
## default view (if there's suppliers data)
if len(suppliers) > 0:
items.append(
ui.table(name='suppliers',
columns=column_supplier_table,
rows=[
ui.table_row(name=supplier.id,
cells=[
supplier.supplier,
supplier.manufacturer,
supplier.product
]) for supplier in suppliers
],
groupable=True,
downloadable=True,
resettable=True,
height='500px'))
## default view (if there's a supplier data)
else:
items.append(ui.text_l(content='No Supplier found'))
# items.append(ui.button(name='show_inputs', label='Add Supplier', primary=True))
items.append(
ui.buttons([
ui.button(name='show_inputs',
label='Add Supplier',
primary=True),
ui.button(name='delete_button', label='Delete Supplier'),
ui.button(name='edit_button', label='Edit Supplier'),
]))
q.page['example'] = ui.form_card(box='1 2 -1 -1', items=items)
await q.page.save()
def column_choices_from_df(df: pd.DataFrame) -> list:
"""
List of dataframe columns as list of Q ui.choice.
"""
return [ui.choice(name=str(x), label=str(x)) for x in df.columns.values]
