| User Interface Generation | Scenario and Data Management |
|---|---|
 |
 |
Open a terminal and run:
$ pip install taipyYou're all set! All aboard the Taipy journey 🚂
Join our Discord to give us feedback, share your creations or just to have a chat with us.
from taipy import Gui
excitement_page = """
# Welcome to Taipy
### How excited are you to try Taipy?
<|{excitement}|slider|min=1|max=100|>
My excitement level: <|{excitement}|>
"""
excitement = 100
Gui(page=excitement_page).run()RUN🏃🏽♀️
Here is our filter function: a standard Python function that is used by the unique task in the scenario
def filter_genre(initial_dataset: pd.DataFrame, selected_genre):
filtered_dataset = initial_dataset[initial_dataset['genres'].str.contains(selected_genre)]
filtered_data = filtered_dataset.nlargest(7, 'Popularity %')
return filtered_dataThis is the execution graph of the scenario we are implementing
You can use the Taipy Studio extension in Visual Studio Code to configure your scenario with no code
Your configuration is automatically saved as a TOML file
Now, let's load this configuration and add a user interface on top for a 🎉FULL APPLICATION🎉
import taipy as tp
import pandas as pd
from taipy import Config, Scope, Gui
# Taipy Scenario & Data Management
# Filtering function - task
def filter_genre(initial_dataset: pd.DataFrame, selected_genre):
filtered_dataset = initial_dataset[initial_dataset["genres"].str.contains(selected_genre)]
filtered_data = filtered_dataset.nlargest(7, "Popularity %")
return filtered_data
# Load the configuration made with Taipy Studio
Config.load("config.toml")
scenario_cfg = Config.scenarios["scenario"]
# Start Taipy Core service
tp.Core().run()
# Create a scenario
scenario = tp.create_scenario(scenario_cfg)
# Taipy User Interface
# Let's add a GUI to our Scenario Management for a full application
# Callback definition - submits scenario with genre selection
def on_genre_selected(state):
scenario.selected_genre_node.write(state.selected_genre)
tp.submit(scenario)
state.df = scenario.filtered_data.read()
# Get list of genres
genres = [
"Action", "Adventure", "Animation", "Children", "Comedy", "Fantasy", "IMAX"
"Romance","Sci-FI", "Western", "Crime", "Mystery", "Drama", "Horror", "Thriller", "Film-Noir","War", "Musical", "Documentary"
]
# Initialization of variables
df = pd.DataFrame(columns=["Title", "Popularity %"])
selected_genre = "Action"
## Set initial value to Action
def on_init(state):
on_genre_selected(state)
# User interface definition
my_page = """
# Film recommendation
## Choose your favorite genre
<|{selected_genre}|selector|lov={genres}|on_change=on_genre_selected|dropdown|>
## Here are the top seven picks by popularity
<|{df}|chart|x=Title|y=Popularity %|type=bar|title=Film Popularity|>
"""
Gui(page=my_page).run()RUN🏃🏽♀️
With Taipy Cloud, you can deploy your Taipy applications in a few clicks and for free!
Want to help build Taipy? Check out our CONTRIBUTING.md file.
Want to be part of the Taipy community? Check out our CODE_OF_CONDUCT.md file.
Copyright 2023 Avaiga Private Limited
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.