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- import sys
- from datetime import datetime, timedelta, timezone
- from typing import List
- import pandas as pd
- import polars as pl
- import pytest
- from selenium.webdriver.common.by import By
- from nicegui import ui
- from nicegui.testing import Screen
- def columns() -> List:
- return [
- {'name': 'name', 'label': 'Name', 'field': 'name', 'required': True},
- {'name': 'age', 'label': 'Age', 'field': 'age', 'sortable': True},
- ]
- def rows() -> List:
- return [
- {'id': 0, 'name': 'Alice', 'age': 18},
- {'id': 1, 'name': 'Bob', 'age': 21},
- {'id': 2, 'name': 'Lionel', 'age': 19},
- ]
- def test_table(screen: Screen):
- ui.table(title='My Team', columns=columns(), rows=rows())
- screen.open('/')
- screen.should_contain('My Team')
- screen.should_contain('Name')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('Lionel')
- def test_pagination_int(screen: Screen):
- ui.table(columns=columns(), rows=rows(), pagination=2)
- screen.open('/')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_not_contain('Lionel')
- screen.should_contain('1-2 of 3')
- def test_pagination_dict(screen: Screen):
- ui.table(columns=columns(), rows=rows(), pagination={'rowsPerPage': 2})
- screen.open('/')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_not_contain('Lionel')
- screen.should_contain('1-2 of 3')
- def test_filter(screen: Screen):
- table = ui.table(columns=columns(), rows=rows())
- ui.input('Search by name').bind_value(table, 'filter')
- screen.open('/')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('Lionel')
- element = screen.selenium.find_element(By.XPATH, '//*[@aria-label="Search by name"]')
- element.send_keys('e')
- screen.should_contain('Alice')
- screen.should_not_contain('Bob')
- screen.should_contain('Lionel')
- def test_add_remove(screen: Screen):
- table = ui.table(columns=columns(), rows=rows())
- ui.button('Add', on_click=lambda: table.add_row({'id': 3, 'name': 'Carol', 'age': 32}))
- ui.button('Remove', on_click=lambda: table.remove_row(table.rows[0]))
- screen.open('/')
- screen.click('Add')
- screen.should_contain('Carol')
- screen.click('Remove')
- screen.wait(0.5)
- screen.should_not_contain('Alice')
- def test_slots(screen: Screen):
- with ui.table(columns=columns(), rows=rows()) as table:
- with table.add_slot('top-row'):
- with table.row():
- with table.cell():
- ui.label('This is the top slot.')
- table.add_slot('body', '''
- <q-tr :props="props">
- <q-td key="name" :props="props">overridden</q-td>
- <q-td key="age" :props="props">
- <q-badge color="green">{{ props.row.age }}</q-badge>
- </q-td>
- </q-tr>
- ''')
- screen.open('/')
- screen.should_contain('This is the top slot.')
- screen.should_not_contain('Alice')
- screen.should_contain('overridden')
- screen.should_contain('21')
- def test_selection(screen: Screen):
- table = ui.table(columns=columns(), rows=rows(), selection='single')
- ui.radio({None: 'none', 'single': 'single', 'multiple': 'multiple'},
- on_change=lambda e: table.set_selection(e.value))
- screen.open('/')
- screen.find('Alice').find_element(By.XPATH, 'preceding-sibling::td').click()
- screen.wait(0.5)
- screen.should_contain('1 record selected.')
- screen.find('Bob').find_element(By.XPATH, 'preceding-sibling::td').click()
- screen.wait(0.5)
- screen.should_contain('1 record selected.')
- screen.click('multiple')
- screen.wait(0.5)
- screen.find('Lionel').find_element(By.XPATH, 'preceding-sibling::td').click()
- screen.wait(0.5)
- screen.should_contain('2 records selected.')
- assert table.selection == 'multiple'
- screen.click('none')
- screen.wait(0.5)
- screen.should_not_contain('1 record selected.')
- assert table.selection is None
- def test_dynamic_column_attributes(screen: Screen):
- ui.table(columns=[{'name': 'age', 'label': 'Age', 'field': 'age', ':format': 'value => value + " years"'}],
- rows=[{'name': 'Alice', 'age': 18}])
- screen.open('/')
- screen.should_contain('18 years')
- def test_remove_selection(screen: Screen):
- t = ui.table(columns=columns(), rows=rows(), selection='single')
- ui.button('Remove first row', on_click=lambda: t.remove_row(t.rows[0]))
- screen.open('/')
- screen.find('Alice').find_element(By.XPATH, 'preceding-sibling::td').click()
- screen.should_contain('1 record selected.')
- screen.click('Remove first row')
- screen.wait(0.5)
- screen.should_not_contain('Alice')
- screen.should_not_contain('1 record selected.')
- def test_replace_rows(screen: Screen):
- t = ui.table(columns=columns(), rows=rows())
- def replace_rows_with_carol():
- t.rows = [{'id': 3, 'name': 'Carol', 'age': 32}]
- def replace_rows_with_daniel():
- t.update_rows([{'id': 4, 'name': 'Daniel', 'age': 33}])
- ui.button('Replace rows with C.', on_click=replace_rows_with_carol)
- ui.button('Replace rows with D.', on_click=replace_rows_with_daniel)
- screen.open('/')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('Lionel')
- screen.click('Replace rows with C.')
- screen.wait(0.5)
- screen.should_not_contain('Alice')
- screen.should_not_contain('Bob')
- screen.should_not_contain('Lionel')
- screen.should_contain('Carol')
- screen.click('Replace rows with D.')
- screen.wait(0.5)
- screen.should_not_contain('Carol')
- screen.should_contain('Daniel')
- @pytest.mark.parametrize('df_type', ['pandas', 'polars'])
- def test_create_and_update_from_df(screen: Screen, df_type: str):
- if df_type == 'pandas':
- DataFrame = pd.DataFrame
- df = DataFrame({'name': ['Alice', 'Bob'], 'age': [18, 21]})
- table = ui.table.from_pandas(df)
- update_from_df = table.update_from_pandas
- else:
- DataFrame = pl.DataFrame
- df = DataFrame({'name': ['Alice', 'Bob'], 'age': [18, 21]})
- table = ui.table.from_polars(df)
- update_from_df = table.update_from_polars
- ui.button('Update', on_click=lambda: update_from_df(DataFrame({'name': ['Lionel'], 'age': [19]})))
- screen.open('/')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('18')
- screen.should_contain('21')
- screen.click('Update')
- screen.should_contain('Lionel')
- screen.should_contain('19')
- @pytest.mark.parametrize('df_type', ['pandas', 'polars'])
- @pytest.mark.skipif(sys.version_info[:2] == (3, 8), reason='Skipping test for Python 3.8')
- def test_problematic_datatypes(screen: Screen, df_type: str):
- if df_type == 'pandas':
- df = pd.DataFrame({
- 'Datetime_col': [datetime(2020, 1, 1)],
- 'Datetime_col_tz': [datetime(2020, 1, 2, tzinfo=timezone.utc)],
- 'Timedelta_col': [timedelta(days=5)],
- 'Complex_col': [1 + 2j],
- 'Period_col': pd.Series([pd.Period('2021-01')]),
- })
- ui.table.from_pandas(df)
- else:
- df = pl.DataFrame({
- 'Datetime_col': [datetime(2020, 1, 1)],
- 'Datetime_col_tz': [datetime(2020, 1, 2, tzinfo=timezone.utc)],
- })
- ui.table.from_polars(df)
- screen.open('/')
- screen.should_contain('Datetime_col')
- screen.should_contain('2020-01-01')
- screen.should_contain('Datetime_col_tz')
- screen.should_contain('2020-01-02')
- if df_type == 'pandas':
- screen.should_contain('Timedelta_col')
- screen.should_contain('5 days')
- screen.should_contain('Complex_col')
- screen.should_contain('(1+2j)')
- screen.should_contain('Period_col')
- screen.should_contain('2021-01')
- def test_table_computed_props(screen: Screen):
- all_rows = rows()
- filtered_rows = [row for row in all_rows if 'e' in row['name']]
- filtered_sorted_rows = sorted(filtered_rows, key=lambda row: row['age'], reverse=True)
- @ui.page('/')
- async def page():
- table = ui.table(
- columns=columns(),
- rows=all_rows,
- row_key='id',
- selection='multiple',
- pagination={'rowsPerPage': 1, 'sortBy': 'age', 'descending': True})
- table.filter = 'e'
- await ui.context.client.connected()
- assert filtered_sorted_rows == await table.get_filtered_sorted_rows()
- assert filtered_sorted_rows[:1] == await table.get_computed_rows()
- assert len(filtered_sorted_rows) == await table.get_computed_rows_number()
- screen.open('/')
- screen.should_contain('Lionel')
- screen.should_not_contain('Alice')
- screen.should_not_contain('Bob')
- def test_infer_columns(screen: Screen):
- ui.table(rows=[
- {'name': 'Alice', 'age': 18},
- {'name': 'Bob', 'age': 21},
- ])
- screen.open('/')
- screen.should_contain('NAME')
- screen.should_contain('AGE')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('18')
- screen.should_contain('21')
- def test_default_column_parameters(screen: Screen):
- ui.table(rows=[
- {'name': 'Alice', 'age': 18, 'city': 'London'},
- {'name': 'Bob', 'age': 21, 'city': 'Paris'},
- ], columns=[
- {'name': 'name', 'label': 'Name', 'field': 'name'},
- {'name': 'age', 'label': 'Age', 'field': 'age'},
- {'name': 'city', 'label': 'City', 'field': 'city', 'sortable': False},
- ], column_defaults={'sortable': True})
- screen.open('/')
- screen.should_contain('Name')
- screen.should_contain('Age')
- screen.should_contain('Alice')
- screen.should_contain('Bob')
- screen.should_contain('18')
- screen.should_contain('21')
- screen.should_contain('London')
- screen.should_contain('Paris')
- assert len(screen.find_all_by_class('sortable')) == 2
- @pytest.mark.parametrize('df_type', ['pandas', 'polars'])
- def test_columns_from_df(screen: Screen, df_type: str):
- if df_type == 'pandas':
- persons = ui.table.from_pandas(pd.DataFrame({'name': ['Alice', 'Bob'], 'age': [18, 21]}))
- cars = ui.table.from_pandas(pd.DataFrame({'make': ['Ford', 'Toyota'], 'model': ['Focus', 'Corolla']}),
- columns=[{'name': 'make', 'label': 'make', 'field': 'make'}])
- DataFrame = pd.DataFrame
- update_persons_from_df = persons.update_from_pandas
- update_cars_from_df = cars.update_from_pandas
- else:
- persons = ui.table.from_polars(pl.DataFrame({'name': ['Alice', 'Bob'], 'age': [18, 21]}))
- cars = ui.table.from_polars(pl.DataFrame({'make': ['Ford', 'Toyota'], 'model': ['Focus', 'Corolla']}),
- columns=[{'name': 'make', 'label': 'make', 'field': 'make'}])
- DataFrame = pl.DataFrame
- update_persons_from_df = persons.update_from_polars
- update_cars_from_df = cars.update_from_polars
- ui.button('Update persons without columns',
- on_click=lambda: update_persons_from_df(DataFrame({'name': ['Dan'], 'age': [5], 'sex': ['male']})))
- ui.button('Update persons with columns',
- on_click=lambda: update_persons_from_df(DataFrame({'name': ['Stephen'], 'age': [33]}),
- columns=[{'name': 'name', 'label': 'Name', 'field': 'name'}]))
- ui.button('Update cars without columns',
- on_click=lambda: update_cars_from_df(DataFrame({'make': ['Honda'], 'model': ['Civic']})))
- ui.button('Update cars with columns',
- on_click=lambda: update_cars_from_df(DataFrame({'make': ['Hyundai'], 'model': ['i30']}),
- columns=[{'name': 'make', 'label': 'make', 'field': 'make'},
- {'name': 'model', 'label': 'model', 'field': 'model'}]))
- screen.open('/')
- screen.should_contain('name')
- screen.should_contain('age')
- screen.should_contain('make')
- screen.should_not_contain('model')
- screen.click('Update persons without columns') # infer columns (like during instantiation)
- screen.should_contain('Dan')
- screen.should_contain('5')
- screen.should_contain('male')
- screen.click('Update persons with columns') # updated columns via parameter
- screen.should_contain('Stephen')
- screen.should_not_contain('32')
- screen.click('Update cars without columns') # don't change columns
- screen.should_contain('Honda')
- screen.should_not_contain('Civic')
- screen.click('Update cars with columns') # updated columns via parameter
- screen.should_contain('Hyundai')
- screen.should_contain('i30')
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