async def serve(q: Q):
if not q.client.initialized:
q.page['meta'] = ui.meta_card(box='')
q.page['example'] = ui.form_card(box='1 1 11 10', items=[
ui.button(name='show_side_panel', label='Order donuts', primary=True)
])
q.client.initialized = True
else:
if q.args.show_side_panel:
q.page['meta'].side_panel = ui.side_panel(title='Welcome to store', items=[
ui.text('Donuts cost $1.99. Proceed?'),
ui.buttons([ui.button(name='next_step', label='Next', primary=True)])
])
elif q.args.next_step:
q.page['meta'].side_panel.items = [
ui.text('You will be charged $1.99. Proceed?'),
ui.buttons([
ui.button(name='cancel', label='Back to safety'),
ui.button(name='submit', label='Place order', primary=True),
])
]
elif q.args.submit:
q.page['example'].items = [ui.message_bar('success', 'Order placed!')]
q.page['meta'].side_panel = None
elif q.args.cancel:
q.page['example'].items = [ui.message_bar('info', 'Order canceled!')]
q.page['meta'].side_panel = None
await q.page.save()
async def start_new_game(q: Q):
q.client.game = Game(q.user.player.player_id)
q.user.player.games[q.client.game.game_id] = q.client.game
q.page['starting_game'] = ui.form_card(
box='4 4 3 3',
items=[
ui.text_l('I am thinking of a number between 1 and 100'),
ui.text_m('can you guess what it is?'),
ui.text_xs('Рађ'),
ui.slider(
name='guess',
label='your guess',
min=1,
max=100,
value=100,
trigger=True,
),
ui.text_xs('Рађ'),
ui.buttons(
items=[
ui.button(name='quit_game', label='Quit', primary=True)
],
justify='center',
),
],
)
await q.page.save()
async def show_issue(q: Q, issue_id: str):
issue = issue_lookup[issue_id]
issue.views += 1
q.client.active_issue_id = issue_id
q.page['form'] = ui.form_card(
box='1 1 4 -1',
items=[
ui.text_xl(f'Issue {issue.id}'),
ui.text(issue.text),
ui.text_xs(f'({issue.views} views)'),
ui.buttons([
ui.button(
name='close_issue'
if issue.status == 'Open' else 'reopen_issue',
label="Close Issue"
if issue.status == 'Open' else "Reopen Issue",
primary=True,
),
ui.button(name='back', label='Back'),
]),
])
await q.page.save()
def render_content_changes(q: Q):
q.page['sidebar'] = ui.form_card(
box='1 2 2 8',
items=[
ui.separator('Button Counting'),
ui.text(
f'This button has been **clicked in this browser session {q.client.count}** times!'
),
ui.text(
f'This button has been **clicked by you {q.user.count}** times!'
),
ui.text(f'This button has been **clicked {q.app.count}** times!'),
ui.buttons([ui.button(name='button', label='Click Me!')],
justify='center')
])
q.page['content'] = ui.form_card(
box='3 2 9 8',
items=[
ui.tabs(name='header_tabs',
value=q.client.tab,
items=[
ui.tab(name=t.lower(), label=t)
for t in ['Home', 'Learn More', 'Contact Us']
]),
ui.frame(
content=
f'This is the {q.client.tab} section, it is still in development.'
)
])
def card_place_order(q: Q) -> ui.FormCard:
item_list = []
for i, item in enumerate(q.client.items.keys()):
text = ui.text_xl(f'{item}')
gpo_order = ui.slider(name=f'gpo_order_{i}',
label='How many to order from GPO?',
min=0,
max=q.client.items[item].max_storage,
value=random.randint(0, q.client.max_storage))
alt_order = ui.slider(name=f'alt_order_{i}',
label='How many to order from alt?',
min=0,
max=q.client.items[item].max_storage,
value=random.randint(0, q.client.max_storage))
item_list.extend([text, gpo_order, alt_order])
buttons = ui.buttons([
ui.button(name='make_order', label='Place Order', primary=True),
ui.button(name='go_home', label='Back', primary=True)
])
item_list.append(buttons)
card = ui.FormCard(
box=box_sidebar,
items=item_list,
)
return card
async def serve(q: Q):
if not q.client.initialized:
q.client.initialized = True
q.page['nav'] = ui.markdown_card(
box='1 1 4 2',
title='Menu',
content=
'[Spam](#menu/spam) / [Ham](#menu/ham) / [Eggs](#menu/eggs) / [About](#about)',
)
q.page['blurb'] = ui.markdown_card(
box='1 3 4 2',
title='Description',
content='Welcome to our store!',
)
q.page['cart'] = ui.form_card(
box='1 5 4 2',
title='Cart',
items=[
ui.text('Your cart is empty!'),
ui.buttons([
ui.button(name=buy_now.__name__,
label='Buy Now!',
primary=True),
ui.button(name='empty_cart', label='Clear cart'),
])
],
)
await q.page.save()
else:
await handle_on(q)
async def serve(q: Q):
if q.args.tall_article:
q.page['example'] = ui.form_card(box='1 1 4 6',
items=[
ui.button(name='back',
label='Go back',
primary=True),
])
else:
q.page['example'] = ui.tall_article_preview_card(
box='1 1 4 6',
title='Tall article preview',
subtitle='Click the card',
value='$19',
name='tall_article',
image=
'https://images.pexels.com/photos/3225517/pexels-photo-3225517.jpeg?auto=compress&cs=tinysrgb&dpr=2&h=750&w=1260', # noqa
content=content,
items=[
ui.buttons(items=[
ui.button(name='like', label='Like'),
ui.button(name='comment', label='Comment'),
ui.button(name='share', label='Share'),
]),
])
await q.page.save()
async def get_inputs(q: Q):
q.page['main'] = ui.form_card(
box="1 2 8 5",
items=[
ui.text_xl('Enter your text input for generation:'),
ui.textbox(name="input_text",
label='',
value=q.app.input_text,
multiline=True),
ui.separator(),
ui.slider(
name="num_words_to_generate",
label=
"Maximum number of words to generate (including input text)",
min=5,
max=50,
step=1,
value=q.app.num_words_to_generate
if q.app.num_words_to_generate else 12,
),
ui.separator(),
ui.buttons([
ui.button(name="generate_text", label='Generate',
primary=True),
])
])
async def show_issues(q: Q):
q.page['form'] = ui.form_card(
box='1 1 4 -1',
items=[
make_issue_table(),
ui.buttons([ui.button(name='edit_multiple', label='Edit Multiple...', primary=True)]),
]
)
await q.page.save()
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()
async def serve(q: Q):
if (not q.client.initialized
): # First visit, create an empty form card for our wizard
q.page['wizard'] = ui.form_card(box='1 1 2 4', items=[])
q.client.initialized = True
wizard = q.page['wizard'] # Get a reference to the wizard form
if q.args.step1:
wizard.items = [
ui.text_xl('Wizard - Step 1'),
ui.text('What is your name?', name='text'),
ui.textbox(name='nickname', label='My name is...',
value='Gandalf'),
ui.buttons([ui.button(name='step2', label='Next', primary=True)]),
]
elif q.args.step2:
q.client.nickname = q.args.nickname
wizard.items = [
ui.text_xl('Wizard - Step 2'),
ui.text(f'Hi {q.args.nickname}! How do you feel right now?',
name='text'),
ui.textbox(name='feeling', label='I feel...', value='magical'),
ui.buttons([ui.button(name='step3', label='Next', primary=True)]),
]
elif q.args.step3:
wizard.items = [
ui.text_xl('Wizard - Done'),
ui.text(
f'What a coincidence, {q.client.nickname}! I feel {q.args.feeling} too!',
name='text',
),
ui.buttons(
[ui.button(name='step1', label='Try Again', primary=True)]),
]
else:
wizard.items = [
ui.text_xl('Wizard Example'),
ui.text("Let's have a conversation, shall we?"),
ui.buttons(
[ui.button(name='step1', label='Of course!', primary=True)]),
]
await q.page.save()
def card_sim_missing() -> ui.FormCard:
text = ui.text('Please enter simulations details before beginning')
buttons = ui.buttons(
[ui.button(name='go_home', label='Back', primary=True)])
item_list = [text, buttons]
card = ui.FormCard(
box=box_sidebar,
items=item_list,
)
return card
def card_sim_saved() -> ui.FormCard:
text = ui.text('Details Saved')
buttons = ui.buttons([
ui.button(name='go_home', label='Return', primary=True),
])
item_list = [text, buttons]
card = ui.FormCard(
box=box_sidebar,
items=item_list,
)
return card
def make_blurb(example: Example):
buttons = []
if example.previous_example:
buttons.append(ui.button(name=f'#{example.previous_example.name}', label='Previous'))
if example.next_example:
buttons.append(ui.button(name=f'#{example.next_example.name}', label='Next', primary=True))
return [
ui.text(example.title, size='l'),
ui.text(example.description),
ui.buttons(buttons),
]
def form_default(q: Q):
# display when app is initialized
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.text(content=STEAM_TEXT, visible=q.client.disable_training),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True, disabled=q.client.disable_training),
ui.button(name='predict', label='Predict', primary=True, disabled=True),
])
]
async def serve(q: Q):
if not q.client.initialized:
q.page['example'] = ui.form_card(
box='1 1 4 10',
items=[
ui.text_xl(content='First text'),
ui.text_l(content='Second text'),
ui.text_m(content='Third text'),
ui.text_s(content='Fourth text'),
ui.inline([
ui.button(name='left1', label='Left1'),
ui.button(name='left2', label='Left2'),
ui.button(name='left3', label='Left3'),
]),
ui.buttons(justify='end',
items=[
ui.button(name='right1', label='Right1'),
ui.button(name='right2', label='Right2'),
ui.button(name='right3', label='Right3'),
]),
ui.buttons(items=[
ui.button(name='show', label='Show'),
ui.button(name='hide', label='Hide')
])
])
q.client.initialized = True
items = q.page['example'].items
items_to_hide = [
items[0].text_xl,
items[2].text_m,
items[4].inline.items[0].button,
items[5].buttons.items[2].button,
]
if q.args.hide:
for i in items_to_hide:
i.visible = False
if q.args.show:
for i in items_to_hide:
i.visible = True
await q.page.save()
async def edit_multiple(q: Q):
q.page['form'] = ui.form_card(
box='1 1 4 -1',
items=[
make_issue_table(allow_multiple_selection=True), # This time, allow multiple selections
ui.buttons([
ui.button(name='reopen_issues', label='Reopen Selected', primary=True),
ui.button(name='close_issues', label='Close Selected', primary=True),
ui.button(name='back', label='Back to safety')
]),
]
)
await q.page.save()
def form_training_progress(q: Q):
# display when model training is in progress
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True, disabled=True),
ui.button(name='predict', label='Predict', primary=True, disabled=True)
]),
ui.progress(label='Training in progress...', caption='This can take a few minutes...'),
ui.text(content=q.client.model_details)
]
def form_training_completed(q: Q):
# display when model training is completed
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True),
ui.button(name='predict', label='Predict', primary=True)
]),
ui.message_bar(type='success', text='Training successfully completed!'),
ui.text(content=q.client.model_details)
]
def form_default(q: Q):
# display when app is initialized
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.text(content=STEAM_TEXT, visible=q.client.disable_training),
ui.slider(name='dai_interpretability', label='Interpretability', min=1, max=10, step=1, value=7),
ui.toggle(name='dai_reproducible', label='Reproducible', value=False),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True, disabled=q.client.disable_training),
ui.button(name='predict', label='Predict', primary=True, disabled=True),
])
]
def form_prediction_completed(q: Q):
# display when model prediction is completed
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.dropdown(name='categorical_columns', label='Select categorical columns',
choices=q.client.column_choices, values=q.client.categorical_columns),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True),
ui.button(name='predict', label='Predict', primary=True)
]),
ui.message_bar(type='success', text='Prediction successfully completed!'),
ui.text(content=q.client.model_details),
ui.text(content=f'''**Example predictions:** <br />
{q.client.preds[0]} <br /> {q.client.preds[1]} <br /> {q.client.preds[2]}''')
]
async def serve(q: Q):
if 'standard_button' in q.args:
q.page['example'].items = [
ui.text(f'primary_button={q.args.primary_button}'),
ui.text(f'standard_button={q.args.standard_button}'),
ui.text(f'standard_disabled_button={q.args.standard_disabled_button}'),
ui.button(name='show_form', label='Back', primary=True),
]
else:
q.page['example'] = ui.form_card(box='1 1 4 10', items=[
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),
]),
])
await q.page.save()
def capture_credentials(q: Q):
q.page['header'] = ui.header_card(
box=config.boxes['banner'],
title=config.title,
subtitle=config.subtitle,
icon=config.icon,
icon_color=config.color,
)
q.page['twitter_app'] = ui.meta_card(box='')
q.page['twitter_app'].dialog = ui.dialog(title='Twitter Credentials', primary=True, items=[
ui.markup(name="request_access", visible=True, content=config.ask_for_access_text),
ui.textbox(name='consumer_key', label='Consumer Key', required=True, password=True),
ui.textbox(name='consumer_secret', label='Consumer Secret', required=True, password=True),
ui.textbox(name='access_token', label='Access Token', required=True, password=True),
ui.textbox(name='access_token_secret', label='Access Token Secret', required=True, password=True),
ui.buttons([ui.button(name='submit', label='Configure', primary=True, tooltip="")])
])
async def new_todo(q: Q):
# Display an input form
q.page['form'] = ui.form_card(box='1 1 4 10',
items=[
ui.text_l('Add To Do'),
ui.textbox(
name='label',
label='What needs to be done?',
multiline=True),
ui.buttons([
ui.button(name='add_todo',
label='Add',
primary=True),
ui.button(name='show_todos',
label='Back'),
]),
])
await q.page.save()
def form_prediction_completed(q: Q):
# display when model prediction is completed
return [
ui.text(content=DATASET_TEXT),
ui.dropdown(name='dai_instance_id', label='Select Driverless AI instance', value=q.client.dai_instance_id,
choices=q.client.choices_dai_instances, required=True),
ui.slider(name='dai_interpretability', label='Interpretability', min=1, max=10, step=1,
value=q.client.dai_interpretability),
ui.toggle(name='dai_reproducible', label='Reproducible', value=q.client.dai_reproducible),
ui.buttons(items=[
ui.button(name='train', label='Train', primary=True),
ui.button(name='predict', label='Predict', primary=True)
]),
ui.message_bar(type='success', text='Prediction successfully completed!'),
ui.text(content=q.client.model_details),
ui.text(content=f'''**Example predictions:** <br />
{q.client.preds[0]} <br /> {q.client.preds[1]} <br /> {q.client.preds[2]}''')
]
def render_customer_page(q: Q):
init(q)
selected_row = int(q.args.risk_table[0])
training_df = predictor.get_testing_data_as_pd_frame()
predictions_df = predictor.predicted_df.as_data_frame()
contributions_df = predictor.contributions_df.as_data_frame()
del contributions_df['BiasTerm']
q.client.selected_customer_id = training_df.loc[selected_row]["ID"]
print("selected id : ", q.client.selected_customer_id)
score = predictions_df.loc[selected_row]["predict"]
approve = bool(score < config.approval_threshold)
drop_column_from_df(training_df, 'default.payment.next.month')
add_column_to_df(training_df, predictions_df, 'Default Prediction Rate',
'predict')
training_df = round_df_column(training_df, 'Default Prediction Rate', 4)
render_customer_details_table(q, training_df, selected_row)
shap_plot = predictor.get_shap_explanation(selected_row)
q.page["shap_plot"] = ui.image_card(
box='shap_plot',
title="Effectiveness of each attribute on defaulting next payment",
type="png",
image=get_image_from_matplotlib(shap_plot, dpi=85),
)
render_customer_summary(q, training_df, contributions_df, selected_row,
approve)
q.page["buttons"] = ui.form_card(box='button_group',
items=[
ui.buttons([
ui.button(name='reject_btn',
label='Reject',
primary=not approve),
ui.button(name='approve_btn',
label='Approve',
primary=approve),
])
])
async def make_welcome_card(q):
q.page['hello'] = ui.form_card(
box='4 4 3 3',
items=[
ui.text_l(f'Hello {q.user.player.first.title()},'),
ui.text_xs('Рађ'),
ui.text_m('Do you want to play a guessing game?'),
ui.text_xs('Рађ'),
ui.buttons(
items=[
ui.button('start_game', label='Play', primary=True),
ui.button('leaderboard',
label='View Scores',
primary=False),
],
justify='center',
),
],
)
await q.page.save()
async def show_results(q: Q):
q.page['main'] = ui.form_card(box="1 2 4 5",
items=[
ui.text_xl("Input Text:"),
ui.separator(),
ui.text(q.app.input_text),
ui.separator(),
ui.buttons([
ui.button(name="get_inputs",
label='Try Again!',
primary=True),
])
])
result = q.app.model(q.app.input_text,
max_length=q.app.num_words_to_generate,
do_sample=False)[0]
q.app.generated_text = result["generated_text"]
q.page['visualization'] = ui.form_card(box="5 2 4 5",
items=[
ui.text_xl("Generated Text:"),
ui.separator(''),
ui.text(q.app.generated_text)
])
async def serve(q: Q):
if q.args.train:
# train WaveML Model using H2O-3 AutoML
wave_model = build_model(train_df=q.client.train_df,
target_column='target',
model_type=ModelType.H2O3,
_h2o3_max_runtime_secs=5,
_h2o3_nfolds=2)
model_id = wave_model.model.model_id
accuracy = round(100 - wave_model.model.mean_per_class_error() * 100,
2)
# save model to local folder
q.client.path_model = save_model(model=wave_model,
output_dir_path='./mymodelfolder')
# show training details and prediction option
q.page['example'].items[1].buttons.items[1].button.disabled = False
q.page['example'].items[2].message_bar.type = 'success'
q.page['example'].items[
2].message_bar.text = 'Training successfully completed!'
q.page['example'].items[
3].text.content = f'''**H2O AutoML model id:** {model_id} <br />
**Accuracy:** {accuracy}%'''
q.page['example'].items[4].text.content = ''
elif q.args.predict:
# load model from local path
wave_model = load_model(file_path=q.client.path_model)
# predict on test data
preds = wave_model.predict(test_df=q.client.test_df)
# show predictions
q.page['example'].items[
2].message_bar.text = 'Prediction successfully completed!'
q.page['example'].items[
4].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)
# 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.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()
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()
