from datetime import datetime, timedelta, timezone from typing import List import pandas as pd 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', ''' overridden {{ props.row.age }} ''') 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_single_selection(screen: Screen): ui.table(columns=columns(), rows=rows(), selection='single') 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.') 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') def test_create_and_update_from_pandas(screen: Screen): df = pd.DataFrame({'name': ['Alice', 'Bob'], 'age': [18, 21]}) table = ui.table.from_pandas(df) def update(): df.loc[2] = ['Lionel', 19] table.update_from_pandas(df) ui.button('Update', on_click=update) 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') def test_problematic_datatypes(screen: Screen): df = pd.DataFrame({ 'Datetime_col': [datetime(2020, 1, 1)], 'Datetime_col_tz': [datetime(2020, 1, 1, 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) screen.open('/') screen.should_contain('Datetime_col') screen.should_contain('Datetime_col_tz') screen.should_contain('Timedelta_col') screen.should_contain('Complex_col') screen.should_contain('Period_col') screen.should_contain('2020-01-01') screen.should_contain('5 days') screen.should_contain('(1+2j)') 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 def test_columns_from_df(screen: Screen): 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'}]) ui.button('Update persons without columns', on_click=lambda: persons.update_from_pandas(pd.DataFrame({'name': ['Dan'], 'age': [5], 'sex': ['male']}))) ui.button('Update persons with columns', on_click=lambda: persons.update_from_pandas(pd.DataFrame({'name': ['Stephen'], 'age': [33]}), columns=[{'name': 'name', 'label': 'Name', 'field': 'name'}])) ui.button('Update cars without columns', on_click=lambda: cars.update_from_pandas(pd.DataFrame({'make': ['Honda'], 'model': ['Civic']}))) ui.button('Update cars with columns', on_click=lambda: cars.update_from_pandas(pd.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')