def render_leaderboard(q: Q):
logger.debug("Creating leaderboard")
for c in q.client.cards:
del q.page[c]
# Create columns for our issue table.
columns = [
ui.table_column(name="user", label="User"),
ui.table_column(name="total",
label="Total Count",
sortable=True,
data_type="number"),
] + [
ui.table_column(
name=t.common_name,
label=t.common_name.title(),
sortable=True,
data_type="number",
) for t in q.client.trees.trees
]
rows = []
for filename in os.listdir(q.user.user.user_dir):
trees = Trees(file=os.path.join(q.user.user.user_dir, filename))
rows += [
ui.table_row(
name="row",
cells=[q.user.user.name,
str(trees.get_total_trees())] +
[str(t.count) for t in trees.trees],
)
]
table = ui.table(
name="tree_table",
columns=columns,
rows=rows,
downloadable=True,
)
q.page["leaderboard"] = ui.form_card(box=ui.boxes(ui.box("body"),
ui.box("top"),
ui.box("top")),
items=[table])
q.client.cards.append("leaderboard")
def render_tree_cards(q):
logger.debug("Creating tree cards")
for c in q.client.cards:
del q.page[c]
length = len(q.client.trees.trees)
for i in range(length):
client_tree = q.client.trees.trees[i]
# for xl layouts should the card be on the first or second row
if i < length / 2:
xl_box = "top"
else:
xl_box = "bottom"
# for medium layouts should the card be on the first, second, or third row
if i < length / 3:
m_box = "top"
elif i < (length / 3 * 2):
m_box = "middle"
else:
m_box = "bottom"
q.page[client_tree.common_name] = ui.form_card(
box=ui.boxes(
ui.box("body", width="400px"),
ui.box(m_box, width="400px"),
ui.box(xl_box, width="400px"),
),
items=[
ui.text_xl(
f"{client_tree.common_name.title()}: {client_tree.family}"
),
ui.text_m(f"Sightings this session: {client_tree.count}"),
ui.button(
name="increment_tree_count",
label="Tree spotted!",
value=client_tree.common_name,
),
],
)
q.client.cards.append(client_tree.common_name)
def render_shap_plot(q: Q, shap_rows: List, selected_row_index: Optional[int]):
q.page['shap_plot'] = ui.plot_card(
box=ui.box('top-plot', height='700px'),
title='Shap explanation' if selected_row_index else 'Global Shap',
data=data(['label', 'value'], rows=shap_rows),
plot=ui.plot([
ui.mark(type='interval',
x='=value',
x_title='SHAP value',
y='=label',
color=q.client.secondary_color)
]))
def render_code(q: Q):
local_dir = os.path.dirname(os.path.realpath(__file__))
with open(os.path.join(local_dir, 'app.py')) as f:
contents = f.read()
py_lexer = get_lexer_by_name("python")
html_formatter = HtmlFormatter(full=True, style="xcode")
q.page['code'] = ui.frame_card(box=ui.box('code',
height='calc(100vh - 155px)'),
title='',
content=highlight(contents, py_lexer,
html_formatter))
def render_charges_breakdown(q: Q, selected_row_index: Optional[int]):
labels = [
'Day Charges', 'Evening Charges', 'Night Charges', 'Intl Charges'
]
rows = []
for label in labels:
if selected_row_index is not None:
rows.append((label, df[label][selected_row_index]))
else:
rows.append((label, df[label].mean(axis=0)))
color_range = f'{q.client.primary_color} {q.client.secondary_color} {q.client.tertiary_color} #67dde6'
q.page['bar_chart'] = ui.plot_card(
box=ui.box('top-stats', height='300px'),
title='Total call charges breakdown'
if selected_row_index else 'Average Charges Breakdown',
data=data(['label', 'value'], rows=rows),
plot=ui.plot([
ui.mark(type='interval',
x='=label',
y='=value',
color='=label',
color_range=color_range)
]))
async def show_grey_dashboard(q: Q):
q.page['meta'] = ui.meta_card(box='', layouts=[
ui.layout(
breakpoint='xl',
min_width='800px',
zones=[
ui.zone('header', size='0'),
ui.zone('body', size='1000px', zones=[
ui.zone('title', size='0'),
ui.zone('top', direction=ui.ZoneDirection.ROW, size='25%'),
ui.zone('middle', direction=ui.ZoneDirection.ROW, size='25%'),
ui.zone('middle2', direction=ui.ZoneDirection.ROW, size='25%'),
ui.zone('bottom', direction=ui.ZoneDirection.ROW, size='20%'),
]),
ui.zone('footer', size='0'),
]
)
])
q.page['header'] = ui.header_card(box='header', title='H2O Wave Demo', subtitle='Grey Dashboard',
nav=global_nav)
q.page['section'] = ui.section_card(
box='title',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.label(label='Start:'),
ui.date_picker(name='target_date', label='', value='2020-12-20'),
ui.label(label='End:'),
ui.date_picker(name='target_date', label='', value='2020-12-25'),
],
)
stock_dates = generate_time_series(10000)
stock_prices = generate_random_walk()
q.page['small'] = ui.small_stat_card(
box=ui.box('top', order=1),
title=next(sample_term),
value=next(sample_dollars),
)
q.page['small_series'] = ui.small_series_stat_card(
box=ui.box('top', order=2),
title=next(sample_term),
value=next(sample_dollars),
plot_category='date',
plot_value='price',
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['small_series_interval'] = ui.small_series_stat_card(
box=ui.box('top', order=3),
title=next(sample_term),
value=next(sample_dollars),
plot_category='date',
plot_value='price',
plot_type=ui.SmallSeriesStatCardPlotType.INTERVAL,
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['wide_series'] = ui.wide_series_stat_card(
box=ui.box('middle', order=1),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
plot_category='date',
plot_value='price',
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['wide_bar'] = ui.wide_bar_stat_card(
box=ui.box('middle', order=2),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
progress=random.random(),
)
q.page['wide_gauge'] = ui.wide_gauge_stat_card(
box=ui.box('middle', order=3),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
progress=random.random(),
)
q.page['tall_series'] = ui.tall_series_stat_card(
box=ui.box('middle2', order=1),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
plot_category='date',
plot_value='price',
plot_data=data(
fields=['date', 'price'],
rows=[(next(stock_dates), next(stock_prices)) for i in range(30)],
pack=True,
),
)
q.page['tall_gauge'] = ui.tall_gauge_stat_card(
box=ui.box('middle2', order=2),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
progress=random.random(),
)
q.page['large'] = ui.large_stat_card(
box=ui.box('bottom', order=1),
title=next(sample_term),
value=next(sample_dollars),
aux_value=next(sample_percent),
caption=next(sample_caption),
)
q.page['large_bar'] = ui.large_bar_stat_card(
box=ui.box('bottom', order=2),
title=next(sample_term),
value=next(sample_dollars),
value_caption=next(sample_term),
aux_value=next(sample_dollars),
aux_value_caption=next(sample_term),
progress=random.random(),
caption=next(sample_caption),
)
q.page['footer'] = ui.footer_card(box='footer', caption='(c) 2021 H2O.ai. All rights reserved.')
await q.page.save()
ui.nav_item(name='#support', label='Support'),
])
],
)
page['controls'] = ui.markdown_card(
# If the viewport width >= 0, place in content zone.
# If the viewport width >= 768, place in sidebar zone.
# If the viewport width >= 1200, place in sidebar zone.
box=ui.boxes('content', 'sidebar', 'sidebar'),
title='Controls',
content=content,
)
page['chart1'] = ui.markdown_card(
box=ui.boxes(
# If the viewport width >= 0, place as second item in content zone.
ui.box(zone='content', order=2),
# If the viewport width >= 768, place in content zone.
'content',
# If the viewport width >= 1200, place as first item in charts zone, use 2 parts of available space.
ui.box(zone='charts', order=1, size=2),
),
title='Chart 1',
content=content,
)
page['chart2'] = ui.markdown_card(
box=ui.boxes(
# If the viewport width >= 0, place as third item in content zone.
ui.box(zone='content', order=3),
# If the viewport width >= 768, place as second item in content zone.
ui.box(zone='content', order=2),
# If the viewport width >= 1200, place as second item in charts zone, use 1 part of available space.
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 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()
async def serve(q: Q):
if not q.client.initialized:
q.page['meta'] = ui.meta_card(
box='',
layouts=[
ui.layout(breakpoint='xs',
zones=[
ui.zone(name='title'),
ui.zone(name='plots',
direction=ui.ZoneDirection.ROW,
wrap='start',
justify='center'),
]),
ui.layout(breakpoint='m',
zones=[
ui.zone(name='title'),
ui.zone(name='plots',
direction=ui.ZoneDirection.ROW,
wrap='start',
justify='center'),
]),
ui.layout(breakpoint='xl',
zones=[
ui.zone(name='title'),
ui.zone(name='plots',
direction=ui.ZoneDirection.ROW,
wrap='start',
justify='center'),
]),
])
q.client.active_theme = 'default'
q.page['title'] = ui.section_card(
box='title',
title='Plot theme demo',
subtitle='Toggle theme to see default plot colors change!',
items=[
ui.toggle(name='toggle_theme',
label='Dark theme',
trigger=True)
],
)
v = q.page.add(
'point-sized',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Point, sized',
data=data('price performance discount', n),
plot=ui.plot([
ui.mark(type='point',
x='=price',
y='=performance',
size='=discount')
])))
v.data = [(x, y, random.randint(1, 10))
for x, y in [f_scat.next() for _ in range(n)]]
v = q.page.add(
'point-shapes',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Point, shapes',
data=data('product price performance', n * 2),
plot=ui.plot([
ui.mark(type='point',
x='=price',
y='=performance',
shape='=product',
shape_range='circle square')
])))
v.data = [
('G1', x, y) for x, y in [f_scat.next() for _ in range(n)]
] + [('G2', x, y) for x, y in [f_scat.next() for _ in range(n)]]
k1, k2 = 20, 10
v = q.page.add(
'poit-size',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Points, size-encoded',
data=data('country product profit', k1 * k2),
plot=ui.plot([
ui.mark(type='point',
x='=country',
y='=product',
size='=profit',
shape='circle')
])))
rows = []
for i in range(k1):
for j in range(k2):
x = f.next()
rows.append((f'A{i + 1}', f'B{j + 1}', x))
v.data = rows
v = q.page.add(
'area',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
y_min=0)
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'area-line',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area + Line',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
y_min=0),
ui.mark(type='line', x='=date', y='=price')
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'area-line-smooth',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area + Line, smooth',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
curve='smooth',
y_min=0),
ui.mark(type='line',
x='=date',
y='=price',
curve='smooth')
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'area-line-groups',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area + Line, groups',
data=data('product date price', n * 5),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
color='=product',
y_min=0),
ui.mark(type='line',
x='=date',
y='=price',
color='=product')
])))
v.data = [(g, t, x) for x in [f_multi.next() for _ in range(n)]
for g, t, x, dx in x]
v = q.page.add(
'area-groups',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area, groups',
data=data('product date price', n * 5),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
color='=product',
y_min=0)
])))
v.data = [(g, t, x) for x in [f_multi.next() for _ in range(n)]
for g, t, x, dx in x]
v = q.page.add(
'area-stacked',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area, stacked',
data=data('product date price', n * 5),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
color='=product',
stack='auto',
y_min=0)
])))
v.data = [(g, t, x) for x in [f_multi.next() for _ in range(n)]
for g, t, x, dx in x]
f_negative = FakeTimeSeries(min=-50, max=50, start=0)
v = q.page.add(
'area-negative-values',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area, negative values',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price')
])))
v.data = [(t, x) for t, x, dx in [f_negative.next() for _ in range(n)]]
v = q.page.add(
'area-range',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area, range',
data=data('date low high', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y0='=low',
y='=high')
])))
v.data = [(t, x - random.randint(3, 8), x + random.randint(3, 8))
for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'area-smooth',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Area, smooth',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=price',
curve='smooth',
y_min=0)
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'example',
ui.plot_card(
box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Label Customization',
data=data('product price', n),
plot=ui.plot([
ui.mark(
type='interval',
x='=product',
y=
'=${{intl price minimum_fraction_digits=2 maximum_fraction_digits=2}}',
y_min=0,
label=
'=${{intl price minimum_fraction_digits=2 maximum_fraction_digits=2}}',
label_offset=0,
label_position='middle',
label_rotation='-90',
label_fill_color='#fff',
label_font_weight='bold')
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(n)]]
v = q.page.add(
'interval',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Interval',
data=data('product price', n),
plot=ui.plot([
ui.mark(type='interval',
x='=product',
y='=price',
y_min=0)
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(n)]]
v = q.page.add(
'interval-annotation',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Categorical-Numeric',
data=data('product price', n),
plot=ui.plot([
ui.mark(type='interval',
x='=product',
y='=price',
y_min=0,
y_max=100),
ui.mark(x='C20', y=80, label='point'),
ui.mark(x='C23', label='vertical line'),
ui.mark(y=40, label='horizontal line'),
ui.mark(x='C26',
x0='C23',
label='vertical region'),
ui.mark(y=70, y0=60, label='horizontal region')
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(n)]]
v = q.page.add(
'histogram',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Histogram',
data=data('lo hi price', n),
plot=ui.plot([
ui.mark(type='interval',
y='=price',
x1='=lo',
x2='=hi',
y_min=0)
])))
v.data = [(i * 10, i * 10 + 10, x)
for i, (c, x,
dx) in enumerate([f_cat.next() for _ in range(n)])]
v = q.page.add(
'interval-range',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Histogram',
data=data('lo hi price', n),
plot=ui.plot([
ui.mark(type='interval',
y='=price',
x1='=lo',
x2='=hi',
y_min=0)
])))
v.data = [(i * 10, i * 10 + 10, x)
for i, (c, x,
dx) in enumerate([f_cat.next() for _ in range(n)])]
v = q.page.add(
'interval-range',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='35%'),
),
title='Interval, range',
data=data('product low high', 3),
plot=ui.plot([
ui.mark(type='interval',
x='=product',
y0='=low',
y='=high')
])))
v.data = [(c, x - random.randint(3, 10), x + random.randint(3, 10))
for c, x, _ in [f.next() for _ in range(3)]]
v = q.page.add(
'interval-transpose',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='29%'),
),
title='Categorical-Numeric',
data=data('product price', 20),
plot=ui.plot([
ui.mark(type='interval',
y='=product',
x='=price',
x_min=0,
x_max=100),
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(20)]]
v = q.page.add(
'intervals-theta-stacked',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Intervals, theta, stacked',
data=data('country product price', n * k),
plot=ui.plot([
ui.mark(coord='theta',
type='interval',
x='=product',
y='=price',
color='=country',
stack='auto',
y_min=0)
])))
v.data = [(g, t, x) for x in [f_cat_multi.next() for _ in range(n)]
for g, t, x, dx in x]
v = q.page.add(
'interval-helix',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Interval, helix',
data=data('product price', 60),
plot=ui.plot([
ui.mark(coord='helix',
type='interval',
x='=product',
y='=price',
y_min=0)
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(60)]]
v = q.page.add(
'interval-polar',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Interval, polar',
data=data('product price', n),
plot=ui.plot([
ui.mark(coord='polar',
type='interval',
x='=product',
y='=price',
y_min=0)
])))
v.data = [(c, x) for c, x, dx in [f_cat.next() for _ in range(n)]]
v = q.page.add(
'intervals-groups',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Intervals, groups',
data=data('country product price', n * k),
plot=ui.plot([
ui.mark(type='interval',
x='=product',
y='=price',
color='=country',
dodge='auto',
y_min=0)
])))
v.data = [(g, t, x) for x in [f_cat_multi.next() for _ in range(n)]
for g, t, x, dx in x]
v = q.page.add(
'intervals-stacked',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Intervals, stacked',
data=data('country product price', n * k),
plot=ui.plot([
ui.mark(type='interval',
x='=product',
y='=price',
color='=country',
stack='auto',
y_min=0)
])))
v.data = [(g, t, x) for x in [f_cat_multi.next() for _ in range(n)]
for g, t, x, dx in x]
v = q.page.add(
'point-annotation',
ui.plot_card(
box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Numeric-Numeric',
data=data('price performance', n),
plot=ui.plot([
ui.mark(type='point',
x='=price',
y='=performance',
x_min=0,
x_max=100,
y_min=0,
y_max=100), # the plot
ui.mark(x=50, y=50,
label='point'), # A single reference point
ui.mark(x=40, label='vertical line'),
ui.mark(y=40, label='horizontal line'),
ui.mark(x=70, x0=60, label='vertical region'),
ui.mark(y=70, y0=60, label='horizontal region'),
ui.mark(x=30,
x0=20,
y=30,
y0=20,
label='rectangular region')
])))
v.data = [f_scat.next() for _ in range(n)]
v = q.page.add(
'path',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Path',
data=data('profit sales', n),
plot=ui.plot(
[ui.mark(type='path', x='=profit', y='=sales')])))
v.data = [(x, y) for x, y in [f_scat.next() for _ in range(n)]]
v = q.page.add(
'step',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Line, step',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='line',
x_scale='time',
x='=date',
y='=price',
curve='step',
y_min=0)
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
v = q.page.add(
'line-annotation',
ui.plot_card(box=ui.boxes(
ui.box('plots', width='100%'),
ui.box('plots', width='48%'),
ui.box('plots', width='32%'),
),
title='Time-Numeric',
data=data('date price', n),
plot=ui.plot([
ui.mark(type='line',
x_scale='time',
x='=date',
y='=price',
y_min=0,
y_max=100),
ui.mark(x=50, y=50, label='point'),
ui.mark(x='2010-05-15T19:59:21.000000Z',
label='vertical line'),
ui.mark(y=40, label='horizontal line'),
ui.mark(x='2010-05-24T19:59:21.000000Z',
x0='2010-05-20T19:59:21.000000Z',
label='vertical region'),
ui.mark(y=70, y0=60, label='horizontal region'),
ui.mark(x='2010-05-10T19:59:21.000000Z',
x0='2010-05-05T19:59:21.000000Z',
y=30,
y0=20,
label='rectangular region')
])))
v.data = [(t, x) for t, x, dx in [f.next() for _ in range(n)]]
q.client.initialized = True
if q.args.toggle_theme is not None:
q.client.active_theme = 'neon' if q.args.toggle_theme else 'default'
q.page['meta'].theme = q.client.active_theme
q.page['title'].items[0].toggle.value = q.client.active_theme == 'neon'
await q.page.save()
async def show_purple_dashboard(q: Q):
q.page['meta'] = ui.meta_card(
box='',
layouts=[
ui.layout(
breakpoint='xs',
zones=[
ui.zone('header', size='80px'),
ui.zone('title', size='0'),
ui.zone('body'),
ui.zone('footer', size='50px'),
],
),
ui.layout(
breakpoint='m',
zones=[
ui.zone('header', size='80px'),
ui.zone('title', size='0'),
ui.zone('body',
direction=ui.ZoneDirection.ROW,
zones=[
ui.zone(
'main',
zones=[
ui.zone('overview', size='0'),
ui.zone('stats1',
direction=ui.ZoneDirection.ROW,
size='150px'),
ui.zone('stats2',
direction=ui.ZoneDirection.ROW,
size='150px'),
ui.zone('others'),
]),
ui.zone('sidebar', size='30%'),
]),
ui.zone('footer', size='50px'),
],
),
ui.layout(
breakpoint='xl',
width='1200px',
zones=[
ui.zone('header', size='80px'),
ui.zone('title', size='0'),
ui.zone('body',
direction=ui.ZoneDirection.ROW,
zones=[
ui.zone('main',
size='3',
zones=[
ui.zone(
'overview',
direction=ui.ZoneDirection.ROW,
size='200px'),
ui.zone(
'stats',
direction=ui.ZoneDirection.ROW,
size='150px'),
ui.zone(
'details',
direction=ui.ZoneDirection.ROW,
size='400px'),
ui.zone(
'reports',
direction=ui.ZoneDirection.ROW,
size='400px'),
]),
ui.zone('sidebar', size='30%'),
]),
ui.zone('footer', size='50px'),
])
])
q.page['header'] = ui.header_card(box='header',
title='H2O Wave Demo',
subtitle='Purple Dashboard',
nav=global_nav)
q.page['title'] = ui.section_card(
box='title',
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.date_picker(name='target_date', label='', value='2020-12-25'),
],
)
customers_overview_dates = generate_time_series(30)
customers_overview_counts = generate_random_walk()
q.page['customers_overview'] = ui.tall_series_stat_card(
box=ui.boxes(
ui.box('body', height='200px', order=1),
ui.box('overview', height='200px', order=1),
ui.box('overview', order=1),
),
title=next(sample_title),
value=next(sample_dollars),
aux_value=next(sample_title),
plot_type='area',
plot_color='$red',
plot_category='date',
plot_value='customer_count',
plot_zero_value=0,
plot_data=data(
fields=['date', 'customer_count'],
rows=[(next(customers_overview_dates),
next(customers_overview_counts)) for i in range(30)],
pack=True,
),
)
conversions_overview_dates = generate_time_series(30)
conversions_overview_counts = generate_random_walk()
q.page['conversions_overview'] = ui.tall_series_stat_card(
box=ui.boxes(
ui.box('body', height='200px', order=2),
ui.box('overview', height='200px', order=2),
ui.box('overview', order=2),
),
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_dollars),
plot_type='interval',
plot_color='$pink',
plot_category='date',
plot_value='conversions',
plot_zero_value=0,
plot_data=data(
fields=['date', 'conversions'],
rows=[(next(conversions_overview_dates),
next(conversions_overview_counts)) for i in range(30)],
pack=True,
),
)
revenue_overview_dates = generate_time_series(30)
revenue_overview_counts = generate_random_walk()
q.page['revenue_overview'] = ui.tall_series_stat_card(
box=ui.boxes(
ui.box('body', height='200px', order=3),
ui.box('overview', height='200px', order=3),
ui.box('overview', order=3),
),
title=next(sample_title),
value=next(sample_amount),
aux_value=next(sample_dollars),
plot_type='area',
plot_color='$purple',
plot_category='date',
plot_value='revenue',
plot_zero_value=0,
plot_data=data(
fields=['date', 'revenue'],
rows=[(next(revenue_overview_dates), next(revenue_overview_counts))
for i in range(30)],
pack=True,
),
)
metric_dates = generate_time_series(30)
metric_values = generate_random_walk()
q.page['conversion_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=4),
ui.box('stats1', order=1),
ui.box('stats', order=1),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='area',
plot_color='$red',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
q.page['revenue_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=5),
ui.box('stats1', order=2),
ui.box('stats', order=2),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='interval',
plot_color='$pink',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
q.page['purchases_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=6),
ui.box('stats1', order=3),
ui.box('stats', order=3),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='area',
plot_color='$purple',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
q.page['transactions_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=7),
ui.box('stats2', order=1),
ui.box('stats', order=4),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='area',
plot_color='$red',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
q.page['order_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=8),
ui.box('stats2', order=2),
ui.box('stats', order=5),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='interval',
plot_color='$pink',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
q.page['quantity_stats'] = ui.small_series_stat_card(
box=ui.boxes(
ui.box('body', height='150px', order=6),
ui.box('stats2', order=3),
ui.box('stats', order=6),
),
title=next(sample_term),
value=next(sample_percent),
plot_type='area',
plot_color='$purple',
plot_category='date',
plot_value='metric',
plot_zero_value=0,
plot_data=data(
fields=['date', 'metric'],
rows=[(next(metric_dates), next(metric_values))
for i in range(30)],
pack=True,
),
)
sales_days_1 = generate_time_series(15)
sales_days_2 = generate_time_series(15)
sales_amounts_1 = generate_random_walk(8000, 15000)
sales_amounts_2 = generate_random_walk(8000, 15000)
q.page['sales_details'] = ui.form_card(
box=ui.boxes(
ui.box('body', height='400px', order=9),
ui.box('others', height='400px', order=1),
ui.box('details', order=1),
),
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_dollars)),
]),
ui.visualization(
plot=ui.plot([
ui.mark(type='interval',
x_scale='time',
x='=date',
y='=sales',
color='=site',
y_min=0,
color_range='$purple $red')
]),
data=data(
fields=['site', 'date', 'sales'],
rows=[('Online', next(sales_days_1), next(sales_amounts_1))
for i in range(15)] +
[('In-store', next(sales_days_2), next(sales_amounts_2))
for i in range(15)],
pack=True),
height='210px',
)
],
)
audience_days1 = generate_time_series(60)
audience_days2 = generate_time_series(60)
audience_hits1 = generate_random_walk(10000, 20000, 0.2)
audience_hits2 = generate_random_walk(8000, 15000)
q.page['visitor_details'] = ui.form_card(
box=ui.boxes(
ui.box('body', height='400px', order=10),
ui.box('others', height='400px', order=2),
ui.box('details', order=2),
),
title=next(sample_title),
items=[
ui.stats(items=[
ui.stat(label=next(sample_term), value=next(sample_amount)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
ui.stat(label=next(sample_term), value=next(sample_percent)),
ui.stat(label=next(sample_term), value=next(sample_dollars)),
]),
ui.visualization(
plot=ui.plot([
ui.mark(type='area',
x_scale='time',
x='=date',
y='=visitors',
color='=site',
color_range='$purple $pink'),
ui.mark(type='line',
x_scale='time',
x='=date',
y='=visitors',
color='=site',
color_range='$purple $pink'),
]),
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='210px',
)
],
)
q.page['earnings_reports'] = ui.stat_table_card(
box=ui.boxes(
ui.box('body', order=11),
ui.box('others', order=3),
ui.box('reports', order=1, size=3),
),
title=next(sample_title),
subtitle=next(sample_caption),
columns=[
next(sample_term),
next(sample_term),
next(sample_term),
next(sample_term)
],
items=[
ui.stat_table_item(label=next(sample_title),
values=[
next(sample_dollars),
next(sample_percent),
next(sample_percent)
]) for i in range(8)
])
q.page['products_reports'] = ui.stat_list_card(
box=ui.boxes(
ui.box('body', order=12),
ui.box('others', order=4),
ui.box('reports', 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),
icon=next(sample_icon),
icon_color=next(sample_color)) for i in range(5)
],
)
q.page['activity'] = ui.stat_list_card(
box=ui.boxes(
ui.box('body', order=13),
ui.box('sidebar', size='0'),
ui.box('sidebar', size='0'),
),
title=next(sample_title),
subtitle=next(sample_caption),
items=[
ui.stat_list_item(label=next(sample_term),
caption=f'Order #{random.randint(1111, 9999)}',
aux_value=f'{random.randint(1, 9)}hr',
icon=next(sample_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()
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 responsive_layout(q: Q):
if not q.user.columns:
q.user.columns = [
ui.table_column(name='Index',
label='Index',
searchable=True,
sortable=True,
data_type='number'),
ui.table_column(name='Started', label='Started', searchable=True),
ui.table_column(name='Ended', label='Ended', searchable=True),
ui.table_column(name='Duration',
label='Duration (mins)',
data_type='number'),
ui.table_column(name='Scores', label='Scores', data_type='number'),
]
if not q.client.LB_columns:
q.client.LB_columns = [
ui.table_column(name='User',
label='User',
searchable=True,
max_width='100px'),
ui.table_column(name='Scores',
label='Scores',
searchable=True,
max_width='100px',
sortable=True),
]
q.page['meta'] = ui.meta_card(
box='',
title='Streak Counter',
layouts=[
ui.layout(
# If the viewport width >= 0:
breakpoint='xs',
zones=[
# 80px high header
ui.zone('header', size='80px'),
# Use remaining space for content
ui.zone('content')
]),
ui.layout(
# If the viewport width >= 768:
breakpoint='m',
zones=[
# 80px high header
ui.zone('header', size='80px'),
# Use remaining space for body
ui.zone(
'body',
direction=ui.ZoneDirection.ROW,
zones=[
# 250px wide sidebar
ui.zone('sidebar', size='250px'),
# Use remaining space for content
ui.zone('content'),
]),
ui.zone('footer'),
]),
ui.layout(
# If the viewport width >= 1200:
breakpoint='xl',
width='1200px',
zones=[
# 80px high header
ui.zone('header', size='80px'),
# Use remaining space for body
ui.zone(
'body',
direction=ui.ZoneDirection.ROW,
zones=[
# 300px wide sidebar
ui.zone('sidebar', size='300px'),
# Use remaining space for other widgets
ui.zone(
'other',
zones=[
# Use one half for charts
ui.zone('charts',
direction=ui.ZoneDirection.ROW),
# Use other half for content
ui.zone('content', size='500px'),
]),
]),
ui.zone('footer'),
])
])
q.page['header'] = ui.header_card(
# Place card in the header zone, regardless of viewport size.
box='header',
title='Code Streak Counter',
subtitle='Count your programming Streak while staying healthy !!!',
)
q.page['LeaderBoard'] = ui.form_card(
# If the viewport width >= 0, place in content zone.
# If the viewport width >= 768, place in sidebar zone.
# If the viewport width >= 1200, place in sidebar zone.
box=ui.boxes('content', 'sidebar', 'sidebar'),
# title='Leader Board',
items=[
ui.text_l(content=f"Hi {q.auth.username.capitalize()}..!"),
ui.text_xl(
content=
f"Your Total Score: {q.user.stop_watch.df['Scores'].sum()}"),
ui.table(
name='leaderboard',
columns=q.client.LB_columns,
rows=[
ui.table_row(name=user, cells=[user, str(score)])
for user, score in q.app.lb_dict.items()
],
groupable=False,
downloadable=True,
resettable=False,
height='425px',
),
ui.link(name='logout',
label='Log Out',
button=True,
path=f'/_logout',
target='_current')
],
)
q.page['stopwatch'] = ui.form_card(
box=ui.boxes(
# If the viewport width >= 0, place as second item in content zone.
ui.box(zone='content', order=2),
# If the viewport width >= 768, place in content zone.
'content',
# If the viewport width >= 1200, place as first item in charts zone, use 2 parts of available space.
ui.box(zone='charts', order=1, size=2),
),
items=[
ui.text_xl(
content=
f"<h1><center>{str(q.user.stop_watch.minutes).zfill(2)} : {str(q.user.stop_watch.seconds).zfill(2)}</center></h1>"
),
ui.text_l(content=f"<center>Lets crack some code!</center>"),
ui.buttons([
ui.button(name='start', label='Start', primary=True),
ui.button(name='stop', label='Stop', primary=False)
],
justify='center')
],
)
q.page['UserStreaks'] = ui.markdown_card(
box=ui.boxes(
# If the viewport width >= 0, place as third item in content zone.
ui.box(zone='content', order=3),
# If the viewport width >= 768, place as second item in content zone.
ui.box(zone='content', order=2),
# If the viewport width >= 1200, place as second item in charts zone, use 1 part of available space.
ui.box(zone='charts', order=2, size=1),
),
title='User Streaks',
content="""=Last Streak Started: {{streak_start}}
<p data-test='UserStreaks_Last_Ended'>Last Streak Ended: {{streak_end}}</p>
<p data-test='UserStreaks_Total_Streaks'>Total Streaks: {{total_streaks}}</p>
Total Coding Time: {{total_time}}
""",
data=dict(streak_start=q.user.stop_watch.last_start,
streak_end=q.user.stop_watch.last_stop,
total_streaks=q.user.stop_watch.total_streaks,
total_time=f"{str(q.user.stop_watch.total_hours).zfill(2)} :\
{str(q.user.stop_watch.total_minutes).zfill(2)} : \
{str(q.user.stop_watch.total_seconds).zfill(2)}"))
q.page['history'] = ui.form_card(
box=ui.boxes(
# If the viewport width >= 0, place as fourth item in content zone.
ui.box(zone='content', order=4),
# If the viewport width >= 768, place as third item in content zone.
ui.box(zone='content', order=3),
# If the viewport width >= 1200, place in content zone.
'content'),
items=[
ui.table(name='streaks_table',
columns=q.user.columns,
rows=[
ui.table_row(name=str(row.Index + 1),
cells=[
str(row.Index + 1), row.Started,
row.Ended,
str(row.Duration),
str(row.Scores)
])
for row in q.user.stop_watch.df.itertuples()
],
groupable=False,
downloadable=True,
resettable=False,
height='425px')
],
title='History',
)
q.page['footer'] = ui.footer_card(box='footer', caption='(c) 2021 H2O.ai ')
