Merge branch 'develop' into test/StatusList

.github/workflows/build-and-release-single-package.yml

@@ -156,7 +156,7 @@ jobs:
       - name: Build package
         working-directory: ${{ steps.set-variables.outputs.package_dir }}
         run: |
-          python setup.py build_py && python -m build
+          python -m build
 
       - name: Rename files
         run: |

.github/workflows/build-and-release.yml

@@ -154,7 +154,7 @@ jobs:
       - name: Build package
         working-directory: ${{ steps.set-variables.outputs.package_dir }}
         run: |
-          python setup.py build_py && python -m build
+          python -m build
           for file in ./dist/*; do mv "$file" "${file//_/-}"; done
 
       - name: Create tag and release
@@ -171,7 +171,7 @@ jobs:
 
   build-and-release-taipy:
     runs-on: ubuntu-latest
-    needs: [build-and-release-taipy-packages, fetch-versions ]
+    needs: [build-and-release-taipy-packages, fetch-versions]
     timeout-minutes: 20
     steps:
       - uses: actions/checkout@v4
@@ -204,7 +204,6 @@ jobs:
           python -m pip install --upgrade pip
           pip install build wheel
 
-
       - name: Backup setup.py
         run: |
           mv setup.py setup.old.py
@@ -213,9 +212,13 @@ jobs:
         run: |
           cp -r tools/packages/taipy/. .
 
+      - name: Build Frontend
+        run: |
+          python tools/frontend/bundle_build.py
+
       - name: Build Taipy package
         run: |
-          python setup.py build_py && python -m build
+          python -m build
 
       - name: Create tag and release Taipy
         run: |
@@ -244,7 +247,7 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-      - uses: stefanzweifel/git-auto-commit-action@v4
+      - uses: stefanzweifel/git-auto-commit-action@v5
         with:
           file_pattern: '*/version.json'
           commit_message: Update version to ${{ needs.fetch-versions.outputs.NEW_VERSION }}

.github/workflows/check-config-pyi.yml

@@ -18,6 +18,6 @@ jobs:
           python-version: '3.11'
       - name: Update config.pyi
         run: python taipy/config/stubs/generate_pyi.py
-      - uses: stefanzweifel/git-auto-commit-action@v4
+      - uses: stefanzweifel/git-auto-commit-action@v5
         with:
           commit_message: "Update config.pyi"

.github/workflows/packaging.yml

@@ -12,15 +12,12 @@ on:
         required: false
         default: ""
 
-env:
-  NODE_OPTIONS: --max-old-space-size=4096
-
 jobs:
   standard-packages:
     timeout-minutes: 30
     strategy:
       matrix:
-        python-versions: [ '3.8', '3.9', '3.10', '3.11', '3.12' ]
+        python-versions: [ '3.8', '3.9', '3.10', '3.11', '3.12']
         os: [ubuntu-latest, macos-13, windows-latest]
 
     runs-on: ${{ matrix.os }}
@@ -38,10 +35,7 @@ jobs:
       - name: Install Taipy without dependencies
         run: |
           pip install .
-
-      - name: Remove local folder
-        run: rm -r taipy
-
+          rm -r taipy
       - name: Check Taipy Installation
         run: |
           python tools/validate_taipy_install.py

.github/workflows/trigger-benchmark.yml

@@ -7,7 +7,7 @@ jobs:
   build:
     runs-on: ubuntu-latest
     steps:
-      - name: Trigger taipy-integration-testing
+      - name: Trigger taipy-benchmark computation
         uses: peter-evans/repository-dispatch@v1
         with:
           token: ${{secrets.TAIPY_INTEGRATION_TESTING_ACCESS_TOKEN}}

.gitignore

@@ -95,5 +95,4 @@ demo_*/
 *.dags
 data_sources
 pipelines
-tasks
 pickles

Pipfile

@@ -31,7 +31,7 @@ pytz = "==2021.3"
 simple-websocket = "==0.10.1"
 sqlalchemy = "==2.0.16"
 toml = "==0.10"
-twisted = "==23.8.0"
+twisted = "==24.7.0"
 tzlocal = "==3.0"
 boto3 = "==1.29.1"
 watchdog = "==4.0.0"

README.md

@@ -1,6 +1,3 @@
-[![Taipy Designer banner](https://github.com/Avaiga/taipy/assets/31435778/6378ffd4-438a-498f-9385-10394f7d53fb)](https://links.taipy.io/306TwUH)
-
-
 <div align="center">
   <a href="https://taipy.io?utm_source=github" target="_blank">
   <picture>
@@ -15,7 +12,8 @@ Build Python Data & AI web applications
 </h1>
 
 <div align="center">
-From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability.
+From simple pilots to production-ready web applications in no time. <br />
+No more compromise on performance, customization, and scalability.
 </div>
 
 <br />
@@ -23,28 +21,28 @@ From simple pilots to production-ready web applications in no time. No more comp
 <div align="center">
 
 **Go beyond existing libraries**
-</div>
-
 
+</div>
 
-  <p align="left">
+<p align="left">
     <br />
     <a href="https://docs.taipy.io/en/latest/"><strong>📚 Explore the docs </strong></a>
     <br />
-    <a href="https://discord.com/invite/SJyz2VJGxV">  🫱🏼‍🫲🏼 Discord support</a>
+    <a href="https://discord.com/invite/SJyz2VJGxV"><strong>  🫱🏼‍🫲🏼 Discord support </strong></a>
     <br />
-    <a href="https://docs.taipy.io/en/latest/gallery/"> 👀 Demos & Examples</a>
+    <a href="https://docs.taipy.io/en/latest/gallery/"><strong> 👀 Demos & Examples </strong></a>
   </p>
 
 &nbsp;
 
 ## ⭐️ What's Taipy?
+
 Taipy is designed for data scientists and machine learning engineers to build data & AI web applications.
 &nbsp;
 
 ⭐️ Enables building production-ready web applications. <br />
 ⭐️ No need to learn new languages. Only Python is needed.<br />
-⭐️ Concentrate on Data and AI algorithms without development and deployment complexities.
+⭐️ Concentrate on Data and AI algorithms without development and deployment complexities.<br />
 
 &nbsp;
 
@@ -52,23 +50,25 @@ Taipy is designed for data scientists and machine learning engineers to build da
 Taipy is a Two-in-One Tool for UI Generation and Scenario/Data Management
 </h4>
 
- <br />
+<br />
 
-| User Interface Generation  | Scenario and Data Management |
-| --------  | -------- |
-|<img src="readme_img/taipy_github_GUI_video.gif" alt="Interface Animation"  width="100%" /> | <img src="readme_img/taipy_github_scenarios_video.gif" alt="Back-End Animation"  width="100%"/>
+| User Interface Generation                                                                       | Scenario and Data Management                                                                        |
+| ----------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- |
+| <img src="readme_img/taipy_github_GUI_video.gif" alt="Interface Animation"  width="100%" /> | <img src="readme_img/taipy_github_scenarios_video.gif" alt="Back-End Animation"  width="100%"/> |
 
 &nbsp;
 
-## ✨ Features
+## ✨ Key Features
+
 <img src="readme_img/taipy_github_scenario.png" alt="Scenario Banner"  width="49%" />  <img src="readme_img/taipy-github-optimized.png" alt="Back-End Animation"  width="49.7%"/>
 <img src="readme_img/taipy_github_data_support.png" alt="Back-End Animation"  width="49.7%" />
 
-
 &nbsp;
 
 ## ⚙️ Quickstart
+
 To install Taipy stable release run:
+
 ```bash
 pip install taipy
 ```
@@ -102,11 +102,13 @@ def filter_genre(initial_dataset: pd.DataFrame, selected_genre):
 ```
 
 This is the execution graph of the scenario we are implementing
+
 <p align="center">
 <img src="https://github.com/Avaiga/taipy/raw/develop/readme_img/readme_exec_graph.png" width="600" align="center" />
 </p>
 
 ### Taipy Studio
+
 You can use the Taipy Studio extension in Visual Studio Code to configure your scenario with no code<br />
 Your configuration is automatically saved as a TOML file.<br />
 Check out Taipy Studio [Documentation](https://docs.taipy.io/en/latest/manuals/studio/)
@@ -119,6 +121,7 @@ Check out the movie genre demo scenario creation with this [Demo](https://docs.t
 &nbsp;
 
 ## User Interface Generation and Scenario & Data Management
+
 This simple Taipy application demonstrates how to create a basic film recommendation system using Taipy.<br />
 The application filters a dataset of films based on the user's selected genre and displays the top seven films in that genre by popularity.
 Here is the full code for both the frontend and backend of the application.
@@ -128,7 +131,17 @@ import taipy as tp
 import pandas as pd
 from taipy import Config, Scope, Gui
 
-# Taipy Scenario & Data Management
+# Defining the helper functions
+
+# 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()
+
+## Set initial value to Action
+def on_init(state):
+    on_genre_selected(state)
 
 # Filtering function - task
 def filter_genre(initial_dataset: pd.DataFrame, selected_genre):
@@ -136,42 +149,35 @@ def filter_genre(initial_dataset: pd.DataFrame, 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"]
+# The main script
+if __name__ == "__main__":
+    # Taipy Scenario & Data Management
 
-# Start Taipy Core service
-tp.Core().run()
+    # Load the configuration made with Taipy Studio
+    Config.load("config.toml")
+    scenario_cfg = Config.scenarios["scenario"]
 
-# Create a scenario
-scenario = tp.create_scenario(scenario_cfg)
+    # Start Taipy Orchestrator
+    tp.Orchestrator().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()
+    # Taipy User Interface
+    # Let's add a GUI to our Scenario Management for a full application
 
-# 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"
+    # 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"
+    # 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 = """
+    # User interface definition
+    my_page = """
 # Film recommendation
 
 ## Choose your favorite genre
@@ -179,9 +185,9 @@ my_page = """
 
 ## Here are the top seven picks by popularity
 <|{df}|chart|x=Title|y=Popularity %|type=bar|title=Film Popularity|>
-"""
+    """
 
-Gui(page=my_page).run()
+    Gui(page=my_page).run()
 ```
 
 And the final result:
@@ -190,17 +196,20 @@ And the final result:
 &nbsp;
 
 ## ⚒️ Contributing
-Want to help build Taipy? Check out our [Contributing Guide](https://github.com/Avaiga/taipy/blob/develop/CONTRIBUTING.md).
+
+Want to help build Taipy? Check out our [**Contributing Guide**](https://github.com/Avaiga/taipy/blob/develop/CONTRIBUTING.md).
 
 ## 🪄 Code of conduct
-Want to be part of the Taipy community? Check out our [Code of Conduct](https://github.com/Avaiga/taipy/blob/develop/CODE_OF_CONDUCT.md)
+
+Want to be part of the Taipy community? Check out our **[Code of Conduct](https://github.com/Avaiga/taipy/blob/develop/CODE_OF_CONDUCT.md)**
 
 ## 🪪 License
+
 Copyright 2021-2024 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](https://www.apache.org/licenses/LICENSE-2.0.txt)
+(Apache License)[http://www.apache.org/licenses/LICENSE-2.0](https://www.apache.org/licenses/LICENSE-2.0.txt)
 
 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

doc/gui/examples/broadcast.py

@@ -31,10 +31,6 @@ counter = 0
 thread = None
 thread_event = Event()
 
-button_texts = ["Start", "Stop"]
-# Text in the start/stop button (initially "Start")
-button_text = button_texts[0]
-
 
 def count(event, gui):
     while not event.is_set():
@@ -58,15 +54,21 @@ def start_or_stop(state: State):
     state.assign("button_text", button_texts[1 if thread else 0])
 
 
-page = """# Broadcasting values
+if __name__ == "__main__":
+    button_texts = ["Start", "Stop"]
+    # Text in the start/stop button (initially "Start")
+    button_text = button_texts[0]
+
+    page = """
+# Broadcasting values
 
 Counter: <|{counter}|>
 
 Timer: <|{button_text}|button|on_action=start_or_stop|>
-"""
+    """
 
-# Declare "button_text" as a shared variable.
-# Assigning a value to a state's 'button_text' property is propagated to all clients
-Gui.add_shared_variable("button_text")
+    # Declare "button_text" as a shared variable.
+    # Assigning a value to a state's 'button_text' property is propagated to all clients
+    Gui.add_shared_variable("button_text")
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/broadcast_callback.py

@@ -23,9 +23,6 @@ from time import sleep
 
 from taipy.gui import Gui
 
-current_time = datetime.now()
-update = False
-
 
 # Update the 'current_time' state variable if 'update' is True
 def update_state(state, updated_time):
@@ -41,17 +38,21 @@ def update_time(gui):
         sleep(1)
 
 
-page = """
+if __name__ == "__main__":
+    current_time = datetime.now()
+    update = False
+
+    page = """
 Current time is: <|{current_time}|format=HH:mm:ss|>
 
 Update: <|{update}|toggle|>
-"""
+    """
 
-gui = Gui(page)
+    gui = Gui(page)
 
-# Run thread that regularly updates the current time
-thread = Thread(target=update_time, args=[gui], name="clock")
-thread.daemon = True
-thread.start()
+    # Run thread that regularly updates the current time
+    thread = Thread(target=update_time, args=[gui], name="clock")
+    thread.daemon = True
+    thread.start()
 
-gui.run()
+    gui.run()

doc/gui/examples/broadcast_change.py

@@ -23,8 +23,6 @@ from time import sleep
 
 from taipy.gui import Gui
 
-current_time = datetime.now()
-
 
 # The function that executes in its own thread.
 # Update the current time every second.
@@ -34,15 +32,18 @@ def update_time(gui):
         sleep(1)
 
 
-page = """
+if __name__ == "__main__":
+    current_time = datetime.now()
+
+    page = """
 Current time is: <|{current_time}|format=HH:mm:ss|>
-"""
+    """
 
-gui = Gui(page)
+    gui = Gui(page)
 
-# Run thread that regularly updates the current time
-thread = Thread(target=update_time, args=[gui], name="clock")
-thread.daemon = True
-thread.start()
+    # Run thread that regularly updates the current time
+    thread = Thread(target=update_time, args=[gui], name="clock")
+    thread.daemon = True
+    thread.start()
 
-gui.run()
+    gui.run()

doc/gui/examples/charts/advanced-annotations.py

@@ -21,31 +21,31 @@ def f(x):
     return x * x * x / 3 - x
 
 
-# x values: [-2.2, ..., 2.2]
-x = [(x - 10) / 4.5 for x in range(0, 21)]
-
-data = {
-    "x": x,
-    # y: [f(-2.2), ..., f(2.2)]
-    "y": [f(x) for x in x],
-}
-
-
-layout = {
-    # Chart title
-    "title": "Local extrema",
-    "annotations": [
-        # Annotation for local maximum (x = -1)
-        {"text": "Local <b>max</b>", "font": {"size": 20}, "x": -1, "y": f(-1)},
-        # Annotation for local minimum (x = 1)
-        {"text": "Local <b>min</b>", "font": {"size": 20}, "x": 1, "y": f(1), "xanchor": "left"},
-    ],
-}
-
-page = """
+if __name__ == "__main__":
+    # x values: [-2.2, ..., 2.2]
+    x = [(x - 10) / 4.5 for x in range(0, 21)]
+
+    data = {
+        "x": x,
+        # y: [f(-2.2), ..., f(2.2)]
+        "y": [f(x) for x in x],
+    }
+
+    layout = {
+        # Chart title
+        "title": "Local extrema",
+        "annotations": [
+            # Annotation for local maximum (x = -1)
+            {"text": "Local <b>max</b>", "font": {"size": 20}, "x": -1, "y": f(-1)},
+            # Annotation for local minimum (x = 1)
+            {"text": "Local <b>min</b>", "font": {"size": 20}, "x": 1, "y": f(1), "xanchor": "left"},
+        ],
+    }
+
+    page = """
 # Advanced - Annotations
 
 <|{data}|chart|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/advanced-python-lib.py

@@ -21,29 +21,34 @@ import plotly.graph_objects as go
 
 from taipy.gui import Gui
 
-# Create the Plotly figure object
-figure = go.Figure()
-
-# Add trace for Normal Distribution
-figure.add_trace(
-    go.Violin(name="Normal", y=np.random.normal(loc=0, scale=1, size=1000), box_visible=True, meanline_visible=True)
-)
-
-# Add trace for Exponential Distribution
-figure.add_trace(
-    go.Violin(name="Exponential", y=np.random.exponential(scale=1, size=1000), box_visible=True, meanline_visible=True)
-)
-
-# Add trace for Uniform Distribution
-figure.add_trace(
-    go.Violin(name="Uniform", y=np.random.uniform(low=0, high=1, size=1000), box_visible=True, meanline_visible=True)
-)
-
-# Updating layout for better visualization
-figure.update_layout(title="Different Probability Distributions")
-
-page = """
+if __name__ == "__main__":
+    # Create the Plotly figure object
+    figure = go.Figure()
+
+    # Add trace for Normal Distribution
+    figure.add_trace(
+        go.Violin(name="Normal", y=np.random.normal(loc=0, scale=1, size=1000), box_visible=True, meanline_visible=True)
+    )
+
+    # Add trace for Exponential Distribution
+    figure.add_trace(
+        go.Violin(
+            name="Exponential", y=np.random.exponential(scale=1, size=1000), box_visible=True, meanline_visible=True
+        )
+    )
+
+    # Add trace for Uniform Distribution
+    figure.add_trace(
+        go.Violin(
+            name="Uniform", y=np.random.uniform(low=0, high=1, size=1000), box_visible=True, meanline_visible=True
+        )
+    )
+
+    # Updating layout for better visualization
+    figure.update_layout(title="Different Probability Distributions")
+
+    page = """
 <|chart|figure={figure}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/advanced-selection.py

@@ -20,43 +20,44 @@ import numpy
 
 from taipy.gui import Gui
 
-# x = [0..20]
-x = list(range(0, 21))
 
-data = {
-    "x": x,
-    # A list of random values within [1, 10]
-    "y": [random.uniform(1, 10) for _ in x],
-}
+def on_change(state, var, val):
+    if var == "selected_indices":
+        state.mean_value = numpy.mean([data["y"][idx] for idx in val]) if len(val) else 0
 
-layout = {
-    # Force the Box select tool
-    "dragmode": "select",
-    # Remove all margins around the plot
-    "margin": {"l": 0, "r": 0, "b": 0, "t": 0},
-}
 
-config = {
-    # Hide Plotly's mode bar
-    "displayModeBar": False
-}
+if __name__ == "__main__":
+    # x = [0..20]
+    x = list(range(0, 21))
 
-selected_indices: List = []
+    data = {
+        "x": x,
+        # A list of random values within [1, 10]
+        "y": [random.uniform(1, 10) for _ in x],
+    }
 
-mean_value = 0.0
+    layout = {
+        # Force the Box select tool
+        "dragmode": "select",
+        # Remove all margins around the plot
+        "margin": {"l": 0, "r": 0, "b": 0, "t": 0},
+    }
 
+    config = {
+        # Hide Plotly's mode bar
+        "displayModeBar": False
+    }
 
-def on_change(state, var, val):
-    if var == "selected_indices":
-        state.mean_value = numpy.mean([data["y"][idx] for idx in val]) if len(val) else 0
+    selected_indices: List = []
 
+    mean_value = 0.0
 
-page = """
+    page = """
 # Advanced - Selection
 
 ## Mean of <|{len(selected_indices)}|raw|> selected points: <|{mean_value}|format=%.2f|raw|>
 
 <|{data}|chart|selected={selected_indices}|layout={layout}|plot_config={config}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/advanced-shapes.py

@@ -21,44 +21,45 @@ def f(x):
     return x * x * x / 3 - x
 
 
-# x values: [-2.2, ..., 2.2]
-x = [(x - 10) / 4.5 for x in range(0, 21)]
+if __name__ == "__main__":
+    # x values: [-2.2, ..., 2.2]
+    x = [(x - 10) / 4.5 for x in range(0, 21)]
 
-data = {
-    "x": x,
-    # y: [f(-2.2), ..., f(2.2)]
-    "y": [f(x) for x in x],
-}
+    data = {
+        "x": x,
+        # y: [f(-2.2), ..., f(2.2)]
+        "y": [f(x) for x in x],
+    }
 
-shape_size = 0.1
+    shape_size = 0.1
 
-layout = {
-    "shapes": [
-        # Shape for local maximum (x = -1)
-        {
-            "x0": -1 - shape_size,
-            "y0": f(-1) - 2 * shape_size,
-            "x1": -1 + shape_size,
-            "y1": f(-1) + 2 * shape_size,
-            "fillcolor": "green",
-            "opacity": 0.5,
-        },
-        # Shape for local minimum (x = 1)
-        {
-            "x0": 1 - shape_size,
-            "y0": f(1) - 2 * shape_size,
-            "x1": 1 + shape_size,
-            "y1": f(1) + 2 * shape_size,
-            "fillcolor": "red",
-            "opacity": 0.5,
-        },
-    ]
-}
+    layout = {
+        "shapes": [
+            # Shape for local maximum (x = -1)
+            {
+                "x0": -1 - shape_size,
+                "y0": f(-1) - 2 * shape_size,
+                "x1": -1 + shape_size,
+                "y1": f(-1) + 2 * shape_size,
+                "fillcolor": "green",
+                "opacity": 0.5,
+            },
+            # Shape for local minimum (x = 1)
+            {
+                "x0": 1 - shape_size,
+                "y0": f(1) - 2 * shape_size,
+                "x1": 1 + shape_size,
+                "y1": f(1) + 2 * shape_size,
+                "fillcolor": "red",
+                "opacity": 0.5,
+            },
+        ]
+    }
 
-page = """
+    page = """
 # Advanced - Annotations
 
 <|{data}|chart|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/advanced-unbalanced-datasets.py

@@ -15,26 +15,27 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# The first data set uses the x interval [-10..10],
-# with one point at every other unit
-x1_range = [x * 2 for x in range(-5, 6)]
+if __name__ == "__main__":
+    # The first data set uses the x interval [-10..10],
+    # with one point at every other unit
+    x1_range = [x * 2 for x in range(-5, 6)]
 
-# The second data set uses the x interval [-4..4],
-# with ten point between every unit
-x2_range = [x / 10 for x in range(-40, 41)]
+    # The second data set uses the x interval [-4..4],
+    # with ten point between every unit
+    x2_range = [x / 10 for x in range(-40, 41)]
 
-# Definition of the two data sets
-data = [
-    # Coarse data set
-    {"x": x1_range, "Coarse": [x * x for x in x1_range]},
-    # Fine data set
-    {"x": x2_range, "Fine": [x * x for x in x2_range]},
-]
+    # Definition of the two data sets
+    data = [
+        # Coarse data set
+        {"x": x1_range, "Coarse": [x * x for x in x1_range]},
+        # Fine data set
+        {"x": x2_range, "Fine": [x * x for x in x2_range]},
+    ]
 
-page = """
+    page = """
 # Advanced - Unbalanced data sets
 
 <|{data}|chart|x[1]=0/x|y[1]=0/Coarse|x[2]=1/x|y[2]=1/Fine|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bar-facing.py

@@ -18,69 +18,69 @@ import numpy
 
 from taipy.gui import Gui
 
-n_years = 10
+if __name__ == "__main__":
+    n_years = 10
 
-proportions_female = numpy.zeros(n_years)
-proportions_male = numpy.zeros(n_years)
+    proportions_female = numpy.zeros(n_years)
+    proportions_male = numpy.zeros(n_years)
 
-# Prepare the data set with random variations
-proportions_female[0] = 0.4
-proportions_male[0] = proportions_female[0] * (1 + numpy.random.normal(0, 0.1))
+    # Prepare the data set with random variations
+    proportions_female[0] = 0.4
+    proportions_male[0] = proportions_female[0] * (1 + numpy.random.normal(0, 0.1))
 
-for i in range(1, n_years):
-    mean_i = (0.5 - proportions_female[i - 1]) / 5
-    new_value = proportions_female[i - 1] + numpy.random.normal(mean_i, 0.1)
+    for i in range(1, n_years):
+        mean_i = (0.5 - proportions_female[i - 1]) / 5
+        new_value = proportions_female[i - 1] + numpy.random.normal(mean_i, 0.1)
 
-    new_value = min(max(0, new_value), 1)
-    proportions_female[i] = new_value
-    proportions_male[i] = proportions_female[i] * (1 + numpy.random.normal(0, 0.1))
+        new_value = min(max(0, new_value), 1)
+        proportions_female[i] = new_value
+        proportions_male[i] = proportions_female[i] * (1 + numpy.random.normal(0, 0.1))
 
+    data = {
+        "Hobbies": [
+            "Archery",
+            "Tennis",
+            "Football",
+            "Basket",
+            "Volley",
+            "Golf",
+            "Video-Games",
+            "Reading",
+            "Singing",
+            "Music",
+        ],
+        "Female": proportions_female,
+        # Negate these values so they appear to the left side
+        "Male": -proportions_male,
+    }
 
-data = {
-    "Hobbies": [
-        "Archery",
-        "Tennis",
-        "Football",
-        "Basket",
-        "Volley",
-        "Golf",
-        "Video-Games",
-        "Reading",
-        "Singing",
-        "Music",
-    ],
-    "Female": proportions_female,
-    # Negate these values so they appear to the left side
-    "Male": -proportions_male,
-}
+    properties = {
+        # Shared y values
+        "y": "Hobbies",
+        # Bars for the female data set
+        "x[1]": "Female",
+        "color[1]": "#c26391",
+        # Bars for the male data set
+        "x[2]": "Male",
+        "color[2]": "#5c91de",
+        # Both data sets are represented with an horizontal orientation
+        "orientation": "h",
+        #
+        "layout": {
+            # This makes left and right bars aligned on the same y value
+            "barmode": "overlay",
+            # Set a relevant title for the x axis
+            "xaxis": {"title": "Gender"},
+            # Hide the legend
+            "showlegend": False,
+            "margin": {"l": 100},
+        },
+    }
 
-properties = {
-    # Shared y values
-    "y": "Hobbies",
-    # Bars for the female data set
-    "x[1]": "Female",
-    "color[1]": "#c26391",
-    # Bars for the male data set
-    "x[2]": "Male",
-    "color[2]": "#5c91de",
-    # Both data sets are represented with an horizontal orientation
-    "orientation": "h",
-    #
-    "layout": {
-        # This makes left and right bars aligned on the same y value
-        "barmode": "overlay",
-        # Set a relevant title for the x axis
-        "xaxis": {"title": "Gender"},
-        # Hide the legend
-        "showlegend": False,
-        "margin": {"l": 100},
-    },
-}
-
-page = """
+    page = """
 # Bar - Facing
 
 <|{data}|chart|type=bar|properties={properties}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bar-multiple.py

@@ -18,37 +18,38 @@ import pandas
 
 from taipy.gui import Gui
 
-# Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
-percentages = [
-    (1852, 50.83),
-    (1856, 45.29),
-    (1860, 39.65),
-    (1864, 55.03),
-    (1868, 52.66),
-    (1872, 55.58),
-    (1876, 47.92),
-    (1880, 48.31),
-    (1884, 48.85),
-    (1888, 47.80),
-    (1892, 46.02),
-    (1896.0, 51.02),
-    (1900, 51.64),
-    (1904, 56.42),
-    (1908, 51.57),
-    (1912, 41.84),
-    (1916, 49.24),
-    (1920, 60.32),
-    (1924, 54.04),
-    (1928, 58.21),
-]
-data = pandas.DataFrame(percentages, columns=["Year", "Won"])
-lost = [100 - t[1] for t in percentages]
-data["Lost"] = lost
+if __name__ == "__main__":
+    # Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
+    percentages = [
+        (1852, 50.83),
+        (1856, 45.29),
+        (1860, 39.65),
+        (1864, 55.03),
+        (1868, 52.66),
+        (1872, 55.58),
+        (1876, 47.92),
+        (1880, 48.31),
+        (1884, 48.85),
+        (1888, 47.80),
+        (1892, 46.02),
+        (1896.0, 51.02),
+        (1900, 51.64),
+        (1904, 56.42),
+        (1908, 51.57),
+        (1912, 41.84),
+        (1916, 49.24),
+        (1920, 60.32),
+        (1924, 54.04),
+        (1928, 58.21),
+    ]
+    data = pandas.DataFrame(percentages, columns=["Year", "Won"])
+    lost = [100 - t[1] for t in percentages]
+    data["Lost"] = lost
 
-page = """
+    page = """
 # Bar - Multiple
 
 <|{data}|chart|type=bar|x=Year|y[1]=Won|y[2]=Lost|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bar-simple.py

@@ -17,58 +17,59 @@ import pandas
 
 from taipy.gui import Gui
 
-# Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
-percentages = [
-    (1852, 50.83),
-    (1856, 45.29),
-    (1860, 39.65),
-    (1864, 55.03),
-    (1868, 52.66),
-    (1872, 55.58),
-    (1876, 47.92),
-    (1880, 48.31),
-    (1884, 48.85),
-    (1888, 47.80),
-    (1892, 46.02),
-    (1896.0, 51.02),
-    (1900, 51.64),
-    (1904, 56.42),
-    (1908, 51.57),
-    (1912, 41.84),
-    (1916, 49.24),
-    (1920, 60.32),
-    (1924, 54.04),
-    (1928, 58.21),
-    (1932, 57.41),
-    (1936, 60.80),
-    (1940, 54.74),
-    (1944, 53.39),
-    (1948, 49.55),
-    (1952, 55.18),
-    (1956, 57.37),
-    (1960, 49.72),
-    (1964, 61.05),
-    (1968, 43.42),
-    (1972, 60.67),
-    (1976, 50.08),
-    (1980, 50.75),
-    (1984, 58.77),
-    (1988, 53.37),
-    (1992, 43.01),
-    (1996, 49.23),
-    (2000, 47.87),
-    (2004, 50.73),
-    (2008, 52.93),
-    (2012, 51.06),
-    (2016, 46.09),
-    (2020, 51.31),
-]
-data = pandas.DataFrame(percentages, columns=["Year", "%"])
+if __name__ == "__main__":
+    # Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
+    percentages = [
+        (1852, 50.83),
+        (1856, 45.29),
+        (1860, 39.65),
+        (1864, 55.03),
+        (1868, 52.66),
+        (1872, 55.58),
+        (1876, 47.92),
+        (1880, 48.31),
+        (1884, 48.85),
+        (1888, 47.80),
+        (1892, 46.02),
+        (1896.0, 51.02),
+        (1900, 51.64),
+        (1904, 56.42),
+        (1908, 51.57),
+        (1912, 41.84),
+        (1916, 49.24),
+        (1920, 60.32),
+        (1924, 54.04),
+        (1928, 58.21),
+        (1932, 57.41),
+        (1936, 60.80),
+        (1940, 54.74),
+        (1944, 53.39),
+        (1948, 49.55),
+        (1952, 55.18),
+        (1956, 57.37),
+        (1960, 49.72),
+        (1964, 61.05),
+        (1968, 43.42),
+        (1972, 60.67),
+        (1976, 50.08),
+        (1980, 50.75),
+        (1984, 58.77),
+        (1988, 53.37),
+        (1992, 43.01),
+        (1996, 49.23),
+        (2000, 47.87),
+        (2004, 50.73),
+        (2008, 52.93),
+        (2012, 51.06),
+        (2016, 46.09),
+        (2020, 51.31),
+    ]
+    data = pandas.DataFrame(percentages, columns=["Year", "%"])
 
-page = """
+    page = """
 # Bar - Simple
 
 <|{data}|chart|type=bar|x=Year|y=%|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bar-stacked.py

@@ -17,41 +17,42 @@ import pandas
 
 from taipy.gui import Gui
 
-# Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
-percentages = [
-    (1852, 50.83),
-    (1856, 45.29),
-    (1860, 39.65),
-    (1864, 55.03),
-    (1868, 52.66),
-    (1872, 55.58),
-    (1876, 47.92),
-    (1880, 48.31),
-    (1884, 48.85),
-    (1888, 47.80),
-    (1892, 46.02),
-    (1896.0, 51.02),
-    (1900, 51.64),
-    (1904, 56.42),
-    (1908, 51.57),
-    (1912, 41.84),
-    (1916, 49.24),
-    (1920, 60.32),
-    (1924, 54.04),
-    (1928, 58.21),
-]
-
-# Lost percentage = 100-Won percentage
-full = [(t[0], t[1], 100 - t[1]) for t in percentages]
-
-data = pandas.DataFrame(full, columns=["Year", "Won", "Lost"])
-
-layout = {"barmode": "stack"}
-
-page = """
+if __name__ == "__main__":
+    # Source https://en.wikipedia.org/wiki/List_of_United_States_presidential_elections_by_popular_vote_margin
+    percentages = [
+        (1852, 50.83),
+        (1856, 45.29),
+        (1860, 39.65),
+        (1864, 55.03),
+        (1868, 52.66),
+        (1872, 55.58),
+        (1876, 47.92),
+        (1880, 48.31),
+        (1884, 48.85),
+        (1888, 47.80),
+        (1892, 46.02),
+        (1896.0, 51.02),
+        (1900, 51.64),
+        (1904, 56.42),
+        (1908, 51.57),
+        (1912, 41.84),
+        (1916, 49.24),
+        (1920, 60.32),
+        (1924, 54.04),
+        (1928, 58.21),
+    ]
+
+    # Lost percentage = 100-Won percentage
+    full = [(t[0], t[1], 100 - t[1]) for t in percentages]
+
+    data = pandas.DataFrame(full, columns=["Year", "Won", "Lost"])
+
+    layout = {"barmode": "stack"}
+
+    page = """
 # Bar - Stacked
 
 <|{data}|chart|type=bar|x=Year|y[1]=Won|y[2]=Lost|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-multiple.py

@@ -15,22 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# x values are [-10..10]
-x_range = range(-10, 11)
+if __name__ == "__main__":
+    # x values are [-10..10]
+    x_range = range(-10, 11)
 
-# The data set holds the _x_ series and two distinct series for _y_
-data = {
-    "x": x_range,
-    # y1 = x*x
-    "y1": [x * x for x in x_range],
-    # y2 = 100-x*x
-    "y2": [100 - x * x for x in x_range],
-}
+    # The data set holds the _x_ series and two distinct series for _y_
+    data = {
+        "x": x_range,
+        # y1 = x*x
+        "y1": [x * x for x in x_range],
+        # y2 = 100-x*x
+        "y2": [100 - x * x for x in x_range],
+    }
 
-page = """
+    page = """
 # Basics - Multiple traces
 
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-simple.py

@@ -15,12 +15,13 @@
 # -----------------------------------------------------------------------------------------
 from taipy import Gui
 
-# The chart control's data is defined as inline
-# code.
-page = """
+if __name__ == "__main__":
+    # The chart control's data is defined as inline
+    # code.
+    page = """
 # Basics - Simple line
 
 <|{[x*x for x in range(0, 11)]}|chart|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-timeline.py

@@ -18,13 +18,17 @@ import pandas
 
 from taipy.gui import Gui
 
-# Generate a random value for every hour on a given day
-data = {"Date": pandas.date_range("2023-01-04", periods=24, freq="H"), "Value": pandas.Series(numpy.random.randn(24))}
+if __name__ == "__main__":
+    # Generate a random value for every hour on a given day
+    data = {
+        "Date": pandas.date_range("2023-01-04", periods=24, freq="H"),
+        "Value": pandas.Series(numpy.random.randn(24)),
+    }
 
-page = """
+    page = """
 # Basics - Timeline
 
 <|{data}|chart|x=Date|y=Value|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-title.py

@@ -15,17 +15,18 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-layout = {
-    "xaxis": {
-        # Force the title of the x axis
-        "title": "Values for x"
+if __name__ == "__main__":
+    layout = {
+        "xaxis": {
+            # Force the title of the x axis
+            "title": "Values for x"
+        }
     }
-}
 
-page = """
+    page = """
 # Basics - Title
 
 <|{[x*x for x in range(0, 11)]}|chart|title=Plotting x squared|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-two-y-axis.py

@@ -15,34 +15,35 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# x values are [-10..10]
-x_range = range(-10, 11)
-
-# The data set holds the _x_ series and two distinct series for _y_
-data = {
-    "x": x_range,
-    # y1 = x*x
-    "y1": [x * x for x in x_range],
-    # y2 = 2-x*x/50
-    "y2": [(100 - x * x) / 50 for x in x_range],
-}
-
-layout = {
-    "yaxis2": {
-        # Second axis overlays with the first y axis
-        "overlaying": "y",
-        # Place the second axis on the right
-        "side": "right",
-        # and give it a title
-        "title": "Second y axis",
-    },
-    "legend": {
-        # Place the legend above chart
-        "yanchor": "bottom"
-    },
-}
-
-page = """
+if __name__ == "__main__":
+    # x values are [-10..10]
+    x_range = range(-10, 11)
+
+    # The data set holds the _x_ series and two distinct series for _y_
+    data = {
+        "x": x_range,
+        # y1 = x*x
+        "y1": [x * x for x in x_range],
+        # y2 = 2-x*x/50
+        "y2": [(100 - x * x) / 50 for x in x_range],
+    }
+
+    layout = {
+        "yaxis2": {
+            # Second axis overlays with the first y axis
+            "overlaying": "y",
+            # Place the second axis on the right
+            "side": "right",
+            # and give it a title
+            "title": "Second y axis",
+        },
+        "legend": {
+            # Place the legend above chart
+            "yanchor": "bottom"
+        },
+    }
+
+    page = """
 # Basics - Multiple axis
 
 Shared axis:
@@ -50,7 +51,6 @@ Shared axis:
 
 With two axis:
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|yaxis[2]=y2|layout={layout}|height=300px|>
+    """
 
-"""
-
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/basics-xrange.py

@@ -15,16 +15,17 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# x values are [-10..10]
-x_range = range(-10, 11)
+if __name__ == "__main__":
+    # x values are [-10..10]
+    x_range = range(-10, 11)
 
-# The data set that holds both the x and the y values
-data = {"X": x_range, "Y": [x * x for x in x_range]}
+    # The data set that holds both the x and the y values
+    data = {"X": x_range, "Y": [x * x for x in x_range]}
 
-page = """
+    page = """
 # Basics - X range
 
 <|{data}|chart|x=X|y=Y|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bubble-hover.py

@@ -15,24 +15,25 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "x": [1, 2, 3],
-    "y": [1, 2, 3],
-    "Texts": ["Blue<br>Small", "Green<br>Medium", "Red<br>Large"],
-    "Sizes": [60, 80, 100],
-    "Colors": [
-        "rgb(93, 164, 214)",
-        "rgb(44, 160, 101)",
-        "rgb(255, 65, 54)",
-    ],
-}
+if __name__ == "__main__":
+    data = {
+        "x": [1, 2, 3],
+        "y": [1, 2, 3],
+        "Texts": ["Blue<br>Small", "Green<br>Medium", "Red<br>Large"],
+        "Sizes": [60, 80, 100],
+        "Colors": [
+            "rgb(93, 164, 214)",
+            "rgb(44, 160, 101)",
+            "rgb(255, 65, 54)",
+        ],
+    }
 
-marker = {"size": "Sizes", "color": "Colors"}
+    marker = {"size": "Sizes", "color": "Colors"}
 
-page = """
+    page = """
 # Bubble - Hover text
 
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|text=Texts|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bubble-simple.py

@@ -16,20 +16,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "x": [1, 2, 3],
-    "y": [1, 2, 3],
-    "Colors": ["blue", "green", "red"],
-    "Sizes": [20, 40, 30],
-    "Opacities": [1, 0.4, 1],
-}
+if __name__ == "__main__":
+    data = {
+        "x": [1, 2, 3],
+        "y": [1, 2, 3],
+        "Colors": ["blue", "green", "red"],
+        "Sizes": [20, 40, 30],
+        "Opacities": [1, 0.4, 1],
+    }
 
-marker = {"color": "Colors", "size": "Sizes", "opacity": "Opacities"}
+    marker = {"color": "Colors", "size": "Sizes", "opacity": "Opacities"}
 
-page = """
+    page = """
 # Bubble - Simple
 
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/bubble-symbols.py

@@ -16,23 +16,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "x": [1, 2, 3, 4, 5],
-    "y": [10, 7, 4, 1, 5],
-    "Sizes": [20, 30, 40, 50, 30],
-    "Symbols": ["circle-open", "triangle-up", "hexagram", "star-diamond", "circle-cross"],
-}
+if __name__ == "__main__":
+    data = {
+        "x": [1, 2, 3, 4, 5],
+        "y": [10, 7, 4, 1, 5],
+        "Sizes": [20, 30, 40, 50, 30],
+        "Symbols": ["circle-open", "triangle-up", "hexagram", "star-diamond", "circle-cross"],
+    }
 
-marker = {
-    "color": "#77A",
-    "size": "Sizes",
-    "symbol": "Symbols",
-}
+    marker = {
+        "color": "#77A",
+        "size": "Sizes",
+        "symbol": "Symbols",
+    }
 
-page = """
+    page = """
 # Bubble - Symbols
 
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/candlestick-simple.py

@@ -18,18 +18,19 @@ import yfinance
 
 from taipy import Gui
 
-# Extraction of a month of stock data for AAPL using the
-# yfinance package (see https://pypi.org/project/yfinance/).
-ticker = yfinance.Ticker("AAPL")
-# The returned value is a Pandas DataFrame.
-stock = ticker.history(interval="1d", start="2018-08-01", end="2018-08-31")
-# Copy the DataFrame's index to a new column
-stock["Date"] = stock.index
+if __name__ == "__main__":
+    # Extraction of a month of stock data for AAPL using the
+    # yfinance package (see https://pypi.org/project/yfinance/).
+    ticker = yfinance.Ticker("AAPL")
+    # The returned value is a Pandas DataFrame.
+    stock = ticker.history(interval="1d", start="2018-08-01", end="2018-08-31")
+    # Copy the DataFrame's index to a new column
+    stock["Date"] = stock.index
 
-page = """
+    page = """
 # Candlestick - Simple
 
 <|{stock}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/candlestick-styling.py

@@ -18,32 +18,33 @@ import yfinance
 
 from taipy.gui import Gui
 
-# Extraction of a few days of stock historical data for AAPL using
-# the yfinance package (see https://pypi.org/project/yfinance/).
-# The returned value is a Pandas DataFrame.
-ticker = yfinance.Ticker("AAPL")
-stock = ticker.history(interval="1d", start="2018-08-18", end="2018-09-10")
-# Copy the DataFrame index to a new column
-stock["Date"] = stock.index
+if __name__ == "__main__":
+    # Extraction of a few days of stock historical data for AAPL using
+    # the yfinance package (see https://pypi.org/project/yfinance/).
+    # The returned value is a Pandas DataFrame.
+    ticker = yfinance.Ticker("AAPL")
+    stock = ticker.history(interval="1d", start="2018-08-18", end="2018-09-10")
+    # Copy the DataFrame index to a new column
+    stock["Date"] = stock.index
 
-options = {
-    # Candlesticks that show decreasing values are orange
-    "decreasing": {"line": {"color": "orange"}},
-    # Candlesticks that show decreasing values are blue
-    "increasing": {"line": {"color": "blue"}},
-}
+    options = {
+        # Candlesticks that show decreasing values are orange
+        "decreasing": {"line": {"color": "orange"}},
+        # Candlesticks that show decreasing values are blue
+        "increasing": {"line": {"color": "blue"}},
+    }
 
-layout = {
-    "xaxis": {
-        # Hide the range slider
-        "rangeslider": {"visible": False}
+    layout = {
+        "xaxis": {
+            # Hide the range slider
+            "rangeslider": {"visible": False}
+        }
     }
-}
 
-page = """
+    page = """
 # Candlestick - Styling
 
 <|{stock}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/candlestick-timeseries.py

@@ -17,46 +17,47 @@ import datetime
 
 from taipy.gui import Gui
 
-# Retrieved history:
-# (Open, Close, Low, High)
-stock_history = [
-    (311.05, 311.00, 310.75, 311.33),
-    (308.53, 308.31, 307.72, 309.00),
-    (307.35, 306.24, 306.12, 307.46),
-    (306.35, 304.90, 304.34, 310.10),
-    (304.90, 302.99, 302.27, 307.00),
-    (303.03, 301.66, 301.20, 303.25),
-    (301.61, 299.58, 299.50, 301.89),
-    (299.58, 297.95, 297.80, 300.06),
-    (297.95, 299.03, 297.14, 299.67),
-    (299.03, 301.87, 296.71, 301.89),
-    (301.89, 299.40, 298.73, 302.93),
-    (299.50, 299.35, 298.83, 299.50),
-    (299.35, 299.20, 299.19, 299.68),
-    (299.42, 300.50, 299.42, 300.50),
-    (300.70, 300.65, 300.32, 300.75),
-    (300.65, 299.91, 299.91, 300.76),
-]
-start_date = datetime.datetime(year=2022, month=10, day=21)
-period = datetime.timedelta(seconds=4 * 60 * 60)  # 4 hours
+if __name__ == "__main__":
+    # Retrieved history:
+    # (Open, Close, Low, High)
+    stock_history = [
+        (311.05, 311.00, 310.75, 311.33),
+        (308.53, 308.31, 307.72, 309.00),
+        (307.35, 306.24, 306.12, 307.46),
+        (306.35, 304.90, 304.34, 310.10),
+        (304.90, 302.99, 302.27, 307.00),
+        (303.03, 301.66, 301.20, 303.25),
+        (301.61, 299.58, 299.50, 301.89),
+        (299.58, 297.95, 297.80, 300.06),
+        (297.95, 299.03, 297.14, 299.67),
+        (299.03, 301.87, 296.71, 301.89),
+        (301.89, 299.40, 298.73, 302.93),
+        (299.50, 299.35, 298.83, 299.50),
+        (299.35, 299.20, 299.19, 299.68),
+        (299.42, 300.50, 299.42, 300.50),
+        (300.70, 300.65, 300.32, 300.75),
+        (300.65, 299.91, 299.91, 300.76),
+    ]
+    start_date = datetime.datetime(year=2022, month=10, day=21)
+    period = datetime.timedelta(seconds=4 * 60 * 60)  # 4 hours
 
-data = {
-    # Compute date series
-    "Date": [start_date + n * period for n in range(0, len(stock_history))],
-    # Extract open values
-    "Open": [v[0] for v in stock_history],
-    # Extract close values
-    "Close": [v[1] for v in stock_history],
-    # Extract low values
-    "Low": [v[2] for v in stock_history],
-    # Extract high values
-    "High": [v[3] for v in stock_history],
-}
+    data = {
+        # Compute date series
+        "Date": [start_date + n * period for n in range(0, len(stock_history))],
+        # Extract open values
+        "Open": [v[0] for v in stock_history],
+        # Extract close values
+        "Close": [v[1] for v in stock_history],
+        # Extract low values
+        "Low": [v[2] for v in stock_history],
+        # Extract high values
+        "High": [v[3] for v in stock_history],
+    }
 
-md = """
+    md = """
 # Candlestick - Timeline
 
 <|{data}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|>
-"""
+    """
 
-Gui(md).run()
+    Gui(md).run()

doc/gui/examples/charts/continuous-error-multiple.py

@@ -20,97 +20,98 @@ import dateutil.relativedelta
 
 from taipy.gui import Gui
 
-# Data is collected from January 1st, 2010, every month
-start_date = datetime.datetime(year=2010, month=1, day=1)
-period = dateutil.relativedelta.relativedelta(months=1)
+if __name__ == "__main__":
+    # Data is collected from January 1st, 2010, every month
+    start_date = datetime.datetime(year=2010, month=1, day=1)
+    period = dateutil.relativedelta.relativedelta(months=1)
 
-# Data
-# All arrays have the same size (the number of months to track)
-prices: Dict[str, List] = {
-    # Data for apples
-    "apples": [2.48, 2.47, 2.5, 2.47, 2.46, 2.38, 2.31, 2.25, 2.39, 2.41, 2.59, 2.61],
-    "apples_low": [1.58, 1.58, 1.59, 1.64, 1.79, 1.54, 1.53, 1.61, 1.65, 2.02, 1.92, 1.54],
-    "apples_high": [3.38, 3.32, 2.63, 2.82, 2.58, 2.53, 3.27, 3.15, 3.44, 3.42, 3.08, 2.86],
-    "bananas": [2.94, 2.50, 2.39, 2.77, 2.43, 2.32, 2.37, 1.90, 2.31, 2.71, 3.38, 1.92],
-    "bananas_low": [2.12, 1.90, 1.69, 2.44, 1.58, 1.81, 1.44, 1.00, 1.59, 1.74, 2.78, 0.96],
-    "bananas_high": [3.32, 2.70, 3.12, 3.25, 3.00, 2.63, 2.54, 2.37, 2.97, 3.69, 4.36, 2.95],
-    "cherries": [6.18, None, None, None, 3.69, 2.46, 2.31, 2.57, None, None, 6.50, 4.38],
-    "cherries_high": [7.00, None, None, None, 8.50, 6.27, 5.61, 4.36, None, None, 8.00, 7.23],
-    "cherries_low": [3.55, None, None, None, 1.20, 0.87, 1.08, 1.50, None, None, 5.00, 4.20],
-}
+    # Data
+    # All arrays have the same size (the number of months to track)
+    prices: Dict[str, List] = {
+        # Data for apples
+        "apples": [2.48, 2.47, 2.5, 2.47, 2.46, 2.38, 2.31, 2.25, 2.39, 2.41, 2.59, 2.61],
+        "apples_low": [1.58, 1.58, 1.59, 1.64, 1.79, 1.54, 1.53, 1.61, 1.65, 2.02, 1.92, 1.54],
+        "apples_high": [3.38, 3.32, 2.63, 2.82, 2.58, 2.53, 3.27, 3.15, 3.44, 3.42, 3.08, 2.86],
+        "bananas": [2.94, 2.50, 2.39, 2.77, 2.43, 2.32, 2.37, 1.90, 2.31, 2.71, 3.38, 1.92],
+        "bananas_low": [2.12, 1.90, 1.69, 2.44, 1.58, 1.81, 1.44, 1.00, 1.59, 1.74, 2.78, 0.96],
+        "bananas_high": [3.32, 2.70, 3.12, 3.25, 3.00, 2.63, 2.54, 2.37, 2.97, 3.69, 4.36, 2.95],
+        "cherries": [6.18, None, None, None, 3.69, 2.46, 2.31, 2.57, None, None, 6.50, 4.38],
+        "cherries_high": [7.00, None, None, None, 8.50, 6.27, 5.61, 4.36, None, None, 8.00, 7.23],
+        "cherries_low": [3.55, None, None, None, 1.20, 0.87, 1.08, 1.50, None, None, 5.00, 4.20],
+    }
 
-# Create monthly time series
-months = [start_date + n * period for n in range(0, len(prices["apples"]))]
+    # Create monthly time series
+    months = [start_date + n * period for n in range(0, len(prices["apples"]))]
 
-data = [
-    # Raw data
-    {"Months": months, "apples": prices["apples"], "bananas": prices["bananas"], "cherries": prices["cherries"]},
-    # Range data (twice as many values)
-    {
-        "Months2": months + list(reversed(months)),
-        "apples": prices["apples_high"] + list(reversed(prices["apples_low"])),
-        "bananas": prices["bananas_high"] + list(reversed(prices["bananas_low"])),
-        "cherries": prices["cherries_high"] + list(reversed(prices["cherries_low"])),
-    },
-]
+    data = [
+        # Raw data
+        {"Months": months, "apples": prices["apples"], "bananas": prices["bananas"], "cherries": prices["cherries"]},
+        # Range data (twice as many values)
+        {
+            "Months2": months + list(reversed(months)),
+            "apples": prices["apples_high"] + list(reversed(prices["apples_low"])),
+            "bananas": prices["bananas_high"] + list(reversed(prices["bananas_low"])),
+            "cherries": prices["cherries_high"] + list(reversed(prices["cherries_low"])),
+        },
+    ]
 
-properties = {
-    # First trace: reference for Apples
-    "x[1]": "0/Months",
-    "y[1]": "0/apples",
-    "color[1]": "rgb(0,200,80)",
-    #     Hide line
-    "mode[1]": "markers",
-    #     Show in the legend
-    "name[1]": "Apples",
-    # Second trace: reference for Bananas
-    "x[2]": "0/Months",
-    "y[2]": "0/bananas",
-    "color[2]": "rgb(0,100,240)",
-    #     Hide line
-    "mode[2]": "markers",
-    #     Show in the legend
-    "name[2]": "Bananas",
-    # Third trace: reference for Cherries
-    "x[3]": "0/Months",
-    "y[3]": "0/cherries",
-    "color[3]": "rgb(240,60,60)",
-    #     Hide line
-    "mode[3]": "markers",
-    #     Show in the legend
-    "name[3]": "Cherries",
-    # Fourth trace: range for Apples
-    "x[4]": "1/Months2",
-    "y[4]": "1/apples",
-    "options[4]": {
-        "fill": "tozerox",
-        "showlegend": False,
-        "fillcolor": "rgba(0,100,80,0.4)",
-    },
-    #      No surrounding stroke
-    "color[4]": "transparent",
-    # Fifth trace: range for Bananas
-    "x[5]": "1/Months2",
-    "y[5]": "1/bananas",
-    "options[5]": {"fill": "tozerox", "showlegend": False, "fillcolor": "rgba(0,180,250,0.4)"},
-    #      No surrounding stroke
-    "color[5]": "transparent",
-    # Sixth trace: range for Cherries
-    "x[6]": "1/Months2",
-    "y[6]": "1/cherries",
-    "options[6]": {
-        "fill": "tozerox",
-        "showlegend": False,
-        "fillcolor": "rgba(230,100,120,0.4)",
-    },
-    #      No surrounding stroke
-    "color[6]": "transparent",
-}
+    properties = {
+        # First trace: reference for Apples
+        "x[1]": "0/Months",
+        "y[1]": "0/apples",
+        "color[1]": "rgb(0,200,80)",
+        #     Hide line
+        "mode[1]": "markers",
+        #     Show in the legend
+        "name[1]": "Apples",
+        # Second trace: reference for Bananas
+        "x[2]": "0/Months",
+        "y[2]": "0/bananas",
+        "color[2]": "rgb(0,100,240)",
+        #     Hide line
+        "mode[2]": "markers",
+        #     Show in the legend
+        "name[2]": "Bananas",
+        # Third trace: reference for Cherries
+        "x[3]": "0/Months",
+        "y[3]": "0/cherries",
+        "color[3]": "rgb(240,60,60)",
+        #     Hide line
+        "mode[3]": "markers",
+        #     Show in the legend
+        "name[3]": "Cherries",
+        # Fourth trace: range for Apples
+        "x[4]": "1/Months2",
+        "y[4]": "1/apples",
+        "options[4]": {
+            "fill": "tozerox",
+            "showlegend": False,
+            "fillcolor": "rgba(0,100,80,0.4)",
+        },
+        #      No surrounding stroke
+        "color[4]": "transparent",
+        # Fifth trace: range for Bananas
+        "x[5]": "1/Months2",
+        "y[5]": "1/bananas",
+        "options[5]": {"fill": "tozerox", "showlegend": False, "fillcolor": "rgba(0,180,250,0.4)"},
+        #      No surrounding stroke
+        "color[5]": "transparent",
+        # Sixth trace: range for Cherries
+        "x[6]": "1/Months2",
+        "y[6]": "1/cherries",
+        "options[6]": {
+            "fill": "tozerox",
+            "showlegend": False,
+            "fillcolor": "rgba(230,100,120,0.4)",
+        },
+        #      No surrounding stroke
+        "color[6]": "transparent",
+    }
 
-page = """
+    page = """
 # Continuous Error - Multiple traces
 
 <|{data}|chart|properties={properties}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/continuous-error-simple.py

@@ -17,58 +17,59 @@ import random
 
 from taipy.gui import Gui
 
-# Common axis for all data: [1..10]
-x = list(range(1, 11))
-# Sample data
-samples = [5, 7, 8, 4, 5, 9, 8, 8, 6, 5]
+if __name__ == "__main__":
+    # Common axis for all data: [1..10]
+    x = list(range(1, 11))
+    # Sample data
+    samples = [5, 7, 8, 4, 5, 9, 8, 8, 6, 5]
 
-# Generate error data
-# Error that adds to the input data
-error_plus = [3 * random.random() + 0.5 for _ in x]
-# Error subtracted from to the input data
-error_minus = [3 * random.random() + 0.5 for _ in x]
+    # Generate error data
+    # Error that adds to the input data
+    error_plus = [3 * random.random() + 0.5 for _ in x]
+    # Error subtracted from to the input data
+    error_minus = [3 * random.random() + 0.5 for _ in x]
 
-# Upper bound (y + error_plus)
-error_upper = [y + e for (y, e) in zip(samples, error_plus)]
-# Lower bound (y - error_minus)
-error_lower = [y - e for (y, e) in zip(samples, error_minus)]
+    # Upper bound (y + error_plus)
+    error_upper = [y + e for (y, e) in zip(samples, error_plus)]
+    # Lower bound (y - error_minus)
+    error_lower = [y - e for (y, e) in zip(samples, error_minus)]
 
-data = [
-    # Trace for samples
-    {"x": x, "y": samples},
-    # Trace for error range
-    {
-        # Roundtrip around the error bounds: onward then return
-        "x": x + list(reversed(x)),
-        # The two error bounds, with lower bound reversed
-        "y": error_upper + list(reversed(error_lower)),
-    },
-]
+    data = [
+        # Trace for samples
+        {"x": x, "y": samples},
+        # Trace for error range
+        {
+            # Roundtrip around the error bounds: onward then return
+            "x": x + list(reversed(x)),
+            # The two error bounds, with lower bound reversed
+            "y": error_upper + list(reversed(error_lower)),
+        },
+    ]
 
-properties = {
-    # Error data
-    "x[1]": "1/x",
-    "y[1]": "1/y",
-    "options[1]": {
-        # Shows as filled area
-        "fill": "toself",
-        "fillcolor": "rgba(70,70,240,0.6)",
-        "showlegend": False,
-    },
-    # Don't show surrounding stroke
-    "color[1]": "transparent",
-    # Raw data (displayed on top of the error band)
-    "x[2]": "0/x",
-    "y[2]": "0/y",
-    "color[2]": "rgb(140,50,50)",
-    # Shown in the legend
-    "name[2]": "Input",
-}
+    properties = {
+        # Error data
+        "x[1]": "1/x",
+        "y[1]": "1/y",
+        "options[1]": {
+            # Shows as filled area
+            "fill": "toself",
+            "fillcolor": "rgba(70,70,240,0.6)",
+            "showlegend": False,
+        },
+        # Don't show surrounding stroke
+        "color[1]": "transparent",
+        # Raw data (displayed on top of the error band)
+        "x[2]": "0/x",
+        "y[2]": "0/y",
+        "color[2]": "rgb(140,50,50)",
+        # Shown in the legend
+        "name[2]": "Input",
+    }
 
-page = """
+    page = """
 # Continuous Error - Simple
 
 <|{data}|chart|properties={properties}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/error-bars-asymmetric.py

@@ -17,35 +17,36 @@ import random
 
 from taipy.gui import Gui
 
-# Number of samples
-n_samples = 10
-# y values: [0..n_samples-1]
-y = range(0, n_samples)
+if __name__ == "__main__":
+    # Number of samples
+    n_samples = 10
+    # y values: [0..n_samples-1]
+    y = range(0, n_samples)
 
-data = {
-    # The x series is made of random numbers between 1 and 10
-    "x": [random.uniform(1, 10) for _ in y],
-    "y": y,
-}
+    data = {
+        # The x series is made of random numbers between 1 and 10
+        "x": [random.uniform(1, 10) for _ in y],
+        "y": y,
+    }
 
-options = {
-    "error_x": {
-        "type": "data",
-        # Allows for a 'plus' and a 'minus' error data
-        "symmetric": False,
-        # The 'plus' error data is a series of random numbers
-        "array": [random.uniform(0, 5) for _ in y],
-        # The 'minus' error data is a series of random numbers
-        "arrayminus": [random.uniform(0, 2) for _ in y],
-        # Color of the error bar
-        "color": "red",
+    options = {
+        "error_x": {
+            "type": "data",
+            # Allows for a 'plus' and a 'minus' error data
+            "symmetric": False,
+            # The 'plus' error data is a series of random numbers
+            "array": [random.uniform(0, 5) for _ in y],
+            # The 'minus' error data is a series of random numbers
+            "arrayminus": [random.uniform(0, 2) for _ in y],
+            # Color of the error bar
+            "color": "red",
+        }
     }
-}
 
-page = """
+    page = """
 # Error bars - Asymmetric
 
 <|{data}|chart|type=bar|x=x|y=y|orientation=h|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/error-bars-simple.py

@@ -18,34 +18,35 @@ import random
 
 from taipy.gui import Gui
 
-# Number of samples
-max_x = 20
-# x values: [0..max_x-1]
-x = range(0, max_x)
-# Generate random sampling error margins
-error_ranges = [random.uniform(0, 5) for _ in x]
-# Compute a perfect sine wave
-perfect_y = [10 * math.sin(4 * math.pi * i / max_x) for i in x]
-# Compute a sine wave impacted by the sampling error
-# The error is between ±error_ranges[x]/2
-y = [perfect_y[i] + random.uniform(-error_ranges[i] / 2, error_ranges[i] / 2) for i in x]
+if __name__ == "__main__":
+    # Number of samples
+    max_x = 20
+    # x values: [0..max_x-1]
+    x = range(0, max_x)
+    # Generate random sampling error margins
+    error_ranges = [random.uniform(0, 5) for _ in x]
+    # Compute a perfect sine wave
+    perfect_y = [10 * math.sin(4 * math.pi * i / max_x) for i in x]
+    # Compute a sine wave impacted by the sampling error
+    # The error is between ±error_ranges[x]/2
+    y = [perfect_y[i] + random.uniform(-error_ranges[i] / 2, error_ranges[i] / 2) for i in x]
 
-# The chart data is made of the three series
-data = {
-    "x": x,
-    "y1": y,
-    "y2": perfect_y,
-}
+    # The chart data is made of the three series
+    data = {
+        "x": x,
+        "y1": y,
+        "y2": perfect_y,
+    }
 
-options = {
-    # Create the error bar information:
-    "error_y": {"type": "data", "array": error_ranges}
-}
+    options = {
+        # Create the error bar information:
+        "error_y": {"type": "data", "array": error_ranges}
+    }
 
-page = """
+    page = """
 # Error bars - Simple
 
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|options[1]={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/example-rebuild.py

@@ -17,17 +17,18 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# x values: [-10..10]
-x_range = range(-10, 11)
-data = {"X": x_range, "Y": [x * x for x in x_range]}
+if __name__ == "__main__":
+    # x values: [-10..10]
+    x_range = range(-10, 11)
+    data = {"X": x_range, "Y": [x * x for x in x_range]}
 
-types = [("bar", "Bar"), ("line", "Line")]
-selected_type = types[0]
+    types = [("bar", "Bar"), ("line", "Line")]
+    selected_type = types[0]
 
-page = """
+    page = """
 <|{data}|chart|type={selected_type[0]}|x=X|y=Y|rebuild|>
 
 <|{selected_type}|toggle|lov={types}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/filled-area-normalized.py

@@ -15,47 +15,48 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Products": [
-        "Nail polish",
-        "Eyebrow pencil",
-        "Rouge",
-        "Lipstick",
-        "Eyeshadows",
-        "Eyeliner",
-        "Foundation",
-        "Lip gloss",
-        "Mascara",
-    ],
-    "USA": [12814, 13012, 11624, 8814, 12998, 12321, 10342, 22998, 11261],
-    "China": [3054, 5067, 7004, 9054, 12043, 15067, 10119, 12043, 10419],
-    "EU": [4376, 3987, 3574, 4376, 4572, 3417, 5231, 4572, 6134],
-    "Africa": [4229, 3932, 5221, 9256, 3308, 5432, 13701, 4008, 18712],
-}
+if __name__ == "__main__":
+    data = {
+        "Products": [
+            "Nail polish",
+            "Eyebrow pencil",
+            "Rouge",
+            "Lipstick",
+            "Eyeshadows",
+            "Eyeliner",
+            "Foundation",
+            "Lip gloss",
+            "Mascara",
+        ],
+        "USA": [12814, 13012, 11624, 8814, 12998, 12321, 10342, 22998, 11261],
+        "China": [3054, 5067, 7004, 9054, 12043, 15067, 10119, 12043, 10419],
+        "EU": [4376, 3987, 3574, 4376, 4572, 3417, 5231, 4572, 6134],
+        "Africa": [4229, 3932, 5221, 9256, 3308, 5432, 13701, 4008, 18712],
+    }
 
-# Order the different traces
-ys = ["USA", "China", "EU", "Africa"]
+    # Order the different traces
+    ys = ["USA", "China", "EU", "Africa"]
 
-options = [
-    # For the USA
-    {"stackgroup": "one", "groupnorm": "percent"},
-    # For China
-    {"stackgroup": "one"},
-    # For the EU
-    {"stackgroup": "one"},
-    # For Africa
-    {"stackgroup": "one"},
-]
+    options = [
+        # For the USA
+        {"stackgroup": "one", "groupnorm": "percent"},
+        # For China
+        {"stackgroup": "one"},
+        # For the EU
+        {"stackgroup": "one"},
+        # For Africa
+        {"stackgroup": "one"},
+    ]
 
-layout = {
-    # Show all values when hovering on a data point
-    "hovermode": "x unified"
-}
+    layout = {
+        # Show all values when hovering on a data point
+        "hovermode": "x unified"
+    }
 
-page = """
+    page = """
 # Filled Area - Stacked Normalized
 
 <|{data}|chart|mode=none|x=Products|y={ys}|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/filled-area-overlay.py

@@ -15,24 +15,25 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
-    "Items": [32, 25, 86, 60, 70],
-    "Price": [80, 50, 140, 10, 70],
-}
+if __name__ == "__main__":
+    data = {
+        "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+        "Items": [32, 25, 86, 60, 70],
+        "Price": [80, 50, 140, 10, 70],
+    }
 
-options = [
-    # For items
-    {"fill": "tozeroy"},
-    # For price
-    # Using "tonexty" not to cover the first trace
-    {"fill": "tonexty"},
-]
+    options = [
+        # For items
+        {"fill": "tozeroy"},
+        # For price
+        # Using "tonexty" not to cover the first trace
+        {"fill": "tonexty"},
+    ]
 
-page = """
+    page = """
 # Filled Area - Overlay
 
 <|{data}|chart|mode=none|x=Day|y[1]=Items|y[2]=Price|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/filled-area-simple.py

@@ -15,20 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
-    "Items": [32, 25, 86, 60, 70],
-}
+if __name__ == "__main__":
+    data = {
+        "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+        "Items": [32, 25, 86, 60, 70],
+    }
 
-options = {
-    # Fill to x axis
-    "fill": "tozeroy"
-}
+    options = {
+        # Fill to x axis
+        "fill": "tozeroy"
+    }
 
-page = """
+    page = """
 # Filled Area - Simple
 
 <|{data}|chart|x=Day|y=Items|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/filled-area-stacked.py

@@ -15,25 +15,26 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"],
-    "Milk": [80, 85, 95, 120, 140, 130, 145, 150, 120, 100, 90, 110],
-    "Bread": [100, 90, 85, 90, 100, 110, 105, 95, 100, 110, 120, 125],
-    "Apples": [50, 65, 70, 65, 70, 75, 85, 70, 60, 65, 70, 80],
-}
+if __name__ == "__main__":
+    data = {
+        "Month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"],
+        "Milk": [80, 85, 95, 120, 140, 130, 145, 150, 120, 100, 90, 110],
+        "Bread": [100, 90, 85, 90, 100, 110, 105, 95, 100, 110, 120, 125],
+        "Apples": [50, 65, 70, 65, 70, 75, 85, 70, 60, 65, 70, 80],
+    }
 
-# Name of the three sets to trace
-items = ["Milk", "Bread", "Apples"]
+    # Name of the three sets to trace
+    items = ["Milk", "Bread", "Apples"]
 
-options = {
-    # Group all traces in the same stack group
-    "stackgroup": "first_group"
-}
+    options = {
+        # Group all traces in the same stack group
+        "stackgroup": "first_group"
+    }
 
-page = """
+    page = """
 # Filled Area - Stacked
 
 <|{data}|chart|mode=none|x=Month|y={items}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/funnel-area-multiple.py

@@ -15,79 +15,80 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "John_us": [500, 450, 340, 230, 220, 110],
-    "John_eu": [600, 500, 400, 300, 200, 100],
-    "Robert_us": [510, 480, 440, 330, 220, 100],
-    "Robert_eu": [360, 250, 240, 130, 120, 60],
-}
+if __name__ == "__main__":
+    data = {
+        "John_us": [500, 450, 340, 230, 220, 110],
+        "John_eu": [600, 500, 400, 300, 200, 100],
+        "Robert_us": [510, 480, 440, 330, 220, 100],
+        "Robert_eu": [360, 250, 240, 130, 120, 60],
+    }
 
-# Values for each trace
-values = ["John_us", "John_eu", "Robert_us", "Robert_eu"]
+    # Values for each trace
+    values = ["John_us", "John_eu", "Robert_us", "Robert_eu"]
 
-options = [
-    # For John/US
-    {
-        "scalegroup": "first",
-        "textinfo": "value",
-        "title": {
-            # "position": "top",
-            "text": "John in the U.S."
+    options = [
+        # For John/US
+        {
+            "scalegroup": "first",
+            "textinfo": "value",
+            "title": {
+                # "position": "top",
+                "text": "John in the U.S."
+            },
+            # Lower-left corner
+            "domain": {"x": [0, 0.5], "y": [0, 0.5]},
         },
-        # Lower-left corner
-        "domain": {"x": [0, 0.5], "y": [0, 0.5]},
-    },
-    # For John/EU
-    {
-        "scalegroup": "first",
-        "textinfo": "value",
-        "title": {
-            # "position": "top",
-            "text": "John in the E.U."
+        # For John/EU
+        {
+            "scalegroup": "first",
+            "textinfo": "value",
+            "title": {
+                # "position": "top",
+                "text": "John in the E.U."
+            },
+            # Upper-left corner
+            "domain": {"x": [0, 0.5], "y": [0.55, 1]},
         },
-        # Upper-left corner
-        "domain": {"x": [0, 0.5], "y": [0.55, 1]},
-    },
-    # For Robert/US
-    {
-        "scalegroup": "second",
-        "textinfo": "value",
-        "title": {
-            # "position": "top",
-            "text": "Robert in the U.S."
+        # For Robert/US
+        {
+            "scalegroup": "second",
+            "textinfo": "value",
+            "title": {
+                # "position": "top",
+                "text": "Robert in the U.S."
+            },
+            # Lower-right corner
+            "domain": {"x": [0.51, 1], "y": [0, 0.5]},
         },
-        # Lower-right corner
-        "domain": {"x": [0.51, 1], "y": [0, 0.5]},
-    },
-    # For Robert/EU
-    {
-        "scalegroup": "second",
-        "textinfo": "value",
-        "title": {
-            # "position": "top",
-            "text": "Robert in the E.U."
+        # For Robert/EU
+        {
+            "scalegroup": "second",
+            "textinfo": "value",
+            "title": {
+                # "position": "top",
+                "text": "Robert in the E.U."
+            },
+            # Upper-right corner
+            "domain": {"x": [0.51, 1], "y": [0.51, 1]},
         },
-        # Upper-right corner
-        "domain": {"x": [0.51, 1], "y": [0.51, 1]},
-    },
-]
+    ]
 
-layout = {
-    "title": "Sales per Salesman per Region",
-    "showlegend": False,
-    # Draw frames around each trace
-    "shapes": [
-        {"x0": 0, "x1": 0.5, "y0": 0, "y1": 0.5},
-        {"x0": 0, "x1": 0.5, "y0": 0.52, "y1": 1},
-        {"x0": 0.52, "x1": 1, "y0": 0, "y1": 0.5},
-        {"x0": 0.52, "x1": 1, "y0": 0.52, "y1": 1},
-    ],
-}
+    layout = {
+        "title": "Sales per Salesman per Region",
+        "showlegend": False,
+        # Draw frames around each trace
+        "shapes": [
+            {"x0": 0, "x1": 0.5, "y0": 0, "y1": 0.5},
+            {"x0": 0, "x1": 0.5, "y0": 0.52, "y1": 1},
+            {"x0": 0.52, "x1": 1, "y0": 0, "y1": 0.5},
+            {"x0": 0.52, "x1": 1, "y0": 0.52, "y1": 1},
+        ],
+    }
 
-page = """
+    page = """
 # Funnel Area - Multiple Charts
 
 <|{data}|chart|type=funnelarea|values={values}|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/funnel-area.py

@@ -15,19 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {"Types": ["Visits", "Downloads", "Prospects", "Invoiced", "Closed"], "Visits": [13873, 10533, 5443, 2703, 908]}
+if __name__ == "__main__":
+    data = {
+        "Types": ["Visits", "Downloads", "Prospects", "Invoiced", "Closed"],
+        "Visits": [13873, 10533, 5443, 2703, 908],
+    }
 
-layout = {
-    # Stack the areas
-    "funnelmode": "stack",
-    # Hide the legend
-    "showlegend": False,
-}
+    layout = {
+        # Stack the areas
+        "funnelmode": "stack",
+        # Hide the legend
+        "showlegend": False,
+    }
 
-page = """
+    page = """
 # Funnel - Area
 
 <|{data}|chart|type=funnelarea|values=Visits|text=Types|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/funnel-multiple.py

@@ -15,23 +15,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Types": ["Website visit", "Downloads", "Prospects", "Invoice sent", "Closed"],
-    "Visits_us": [13873, 10533, 5443, 2703, 908],
-    "Visits_eu": [7063, 4533, 3443, 1003, 1208],
-    "Visits_ap": [6873, 2533, 3443, 1703, 508],
-}
+if __name__ == "__main__":
+    data = {
+        "Types": ["Website visit", "Downloads", "Prospects", "Invoice sent", "Closed"],
+        "Visits_us": [13873, 10533, 5443, 2703, 908],
+        "Visits_eu": [7063, 4533, 3443, 1003, 1208],
+        "Visits_ap": [6873, 2533, 3443, 1703, 508],
+    }
 
-# Columns for each trace
-x = ["Visits_us", "Visits_eu", "Visits_ap"]
+    # Columns for each trace
+    x = ["Visits_us", "Visits_eu", "Visits_ap"]
 
-# Legend text for each trace
-names = ["US", "EU", "AP"]
+    # Legend text for each trace
+    names = ["US", "EU", "AP"]
 
-page = """
+    page = """
 # Funnel - Multiple traces
 
 <|{data}|chart|type=funnel|x={x}|y=Types|name={names}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/funnel-simple.py

@@ -15,13 +15,14 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Data set
-data = {"Opps": ["Hot leads", "Doc sent", "Quote", "Closed Won"], "Visits": [316, 238, 125, 83]}
+if __name__ == "__main__":
+    # Data set
+    data = {"Opps": ["Hot leads", "Doc sent", "Quote", "Closed Won"], "Visits": [316, 238, 125, 83]}
 
-page = """
+    page = """
 # Funnel Chart - Simple
 
 <|{data}|chart|type=funnel|x=Visits|y=Opps|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/funnel-styling.py

@@ -15,27 +15,28 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Types": ["Website visit", "Downloads", "Prospects", "Invoice sent", "Closed"],
-    "Visits": [13873, 10533, 5443, 2703, 908],
-}
+if __name__ == "__main__":
+    data = {
+        "Types": ["Website visit", "Downloads", "Prospects", "Invoice sent", "Closed"],
+        "Visits": [13873, 10533, 5443, 2703, 908],
+    }
 
-marker = {
-    # Boxes are filled with a blue gradient color
-    "color": ["hsl(210,50%,50%)", "hsl(210,60%,60%)", "hsl(210,70%,70%)", "hsl(210,80%,80%)", "hsl(210,90%,90%)"],
-    # Lines get thicker, with an orange-to-green gradient color
-    "line": {"width": [1, 1, 2, 3, 4], "color": ["f5720a", "f39c1d", "f0cc3d", "aadb12", "8cb709"]},
-}
+    marker = {
+        # Boxes are filled with a blue gradient color
+        "color": ["hsl(210,50%,50%)", "hsl(210,60%,60%)", "hsl(210,70%,70%)", "hsl(210,80%,80%)", "hsl(210,90%,90%)"],
+        # Lines get thicker, with an orange-to-green gradient color
+        "line": {"width": [1, 1, 2, 3, 4], "color": ["f5720a", "f39c1d", "f0cc3d", "aadb12", "8cb709"]},
+    }
 
-options = {
-    # Lines connecting boxes are thick, dotted and green
-    "connector": {"line": {"color": "green", "dash": "dot", "width": 4}}
-}
+    options = {
+        # Lines connecting boxes are thick, dotted and green
+        "connector": {"line": {"color": "green", "dash": "dot", "width": 4}}
+    }
 
-page = """
+    page = """
 # Funnel Chart - Custom markers
 
 <|{data}|chart|type=funnel|x=Visits|y=Types|marker={marker}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/gantt-simple.py

@@ -17,42 +17,43 @@ import datetime
 
 from taipy.gui import Gui
 
-# Tasks definitions
-tasks = ["Plan", "Research", "Design", "Implement", "Test", "Deliver"]
-# Task durations, in days
-durations = [50, 30, 30, 40, 15, 10]
-# Planned start dates of tasks
-start_dates = [
-    datetime.date(2022, 10, 15),  # Plan
-    datetime.date(2022, 11, 7),  # Research
-    datetime.date(2022, 12, 1),  # Design
-    datetime.date(2022, 12, 20),  # Implement
-    datetime.date(2023, 1, 15),  # Test
-    datetime.date(2023, 2, 1),  # Deliver
-]
-
-epoch = datetime.date(1970, 1, 1)
-
-data = {
-    "start": start_dates,
-    "Task": tasks,
-    # Compute the time span as adatetime (relative to January 1st, 1970)
-    "Date": [epoch + datetime.timedelta(days=duration) for duration in durations],
-}
-
-layout = {
-    "yaxis": {
-        # Sort tasks from top to bottom
-        "autorange": "reversed",
-        # Remove title
-        "title": {"text": ""},
-    },
-}
-
-page = """
+if __name__ == "__main__":
+    # Tasks definitions
+    tasks = ["Plan", "Research", "Design", "Implement", "Test", "Deliver"]
+    # Task durations, in days
+    durations = [50, 30, 30, 40, 15, 10]
+    # Planned start dates of tasks
+    start_dates = [
+        datetime.date(2022, 10, 15),  # Plan
+        datetime.date(2022, 11, 7),  # Research
+        datetime.date(2022, 12, 1),  # Design
+        datetime.date(2022, 12, 20),  # Implement
+        datetime.date(2023, 1, 15),  # Test
+        datetime.date(2023, 2, 1),  # Deliver
+    ]
+
+    epoch = datetime.date(1970, 1, 1)
+
+    data = {
+        "start": start_dates,
+        "Task": tasks,
+        # Compute the time span as adatetime (relative to January 1st, 1970)
+        "Date": [epoch + datetime.timedelta(days=duration) for duration in durations],
+    }
+
+    layout = {
+        "yaxis": {
+            # Sort tasks from top to bottom
+            "autorange": "reversed",
+            # Remove title
+            "title": {"text": ""},
+        },
+    }
+
+    page = """
 # Gantt - Simple
 
 <|{data}|chart|type=bar|orientation=h|y=Task|x=Date|base=start|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-annotated.py

@@ -17,56 +17,57 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-data: Dict[str, List] = {
-    "Temperatures": [
-        [17.2, 27.4, 28.6, 21.5],
-        [5.6, 15.1, 20.2, 8.1],
-        [26.6, 22.8, 21.8, 24.0],
-        [22.3, 15.5, 13.4, 19.6],
-    ],
-    "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
-    "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
-}
+if __name__ == "__main__":
+    data: Dict[str, List] = {
+        "Temperatures": [
+            [17.2, 27.4, 28.6, 21.5],
+            [5.6, 15.1, 20.2, 8.1],
+            [26.6, 22.8, 21.8, 24.0],
+            [22.3, 15.5, 13.4, 19.6],
+        ],
+        "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
+        "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
+    }
 
-layout = {
-    # This array contains the information we want to display in the cells
-    # These are filled later
-    "annotations": [],
-    # No ticks on the x axis, show labels on top the of the chart
-    "xaxis": {"ticks": "", "side": "top"},
-    # No ticks on the y axis
-    # Add a space character for a small margin with the text
-    "yaxis": {"ticks": "", "ticksuffix": " "},
-}
+    layout = {
+        # This array contains the information we want to display in the cells
+        # These are filled later
+        "annotations": [],
+        # No ticks on the x axis, show labels on top the of the chart
+        "xaxis": {"ticks": "", "side": "top"},
+        # No ticks on the y axis
+        # Add a space character for a small margin with the text
+        "yaxis": {"ticks": "", "ticksuffix": " "},
+    }
 
-seasons = data["Seasons"]
-cities = data["Cities"]
-# Iterate over all cities
-for city in range(len(cities)):
-    # Iterate over all seasons
-    for season in range(len(seasons)):
-        temperature = data["Temperatures"][city][season]
-        # Create the annotation
-        annotation = {
-            # The name of the season
-            "x": seasons[season],
-            # The name of the city
-            "y": cities[city],
-            # The temperature, as a formatted string
-            "text": f"{temperature}\N{DEGREE SIGN}C",
-            # Change the text color depending on the temperature
-            # so it results in a better contrast
-            "font": {"color": "white" if temperature < 14 else "black"},
-            # Remove the annotation arrow
-            "showarrow": False,
-        }
-        # Add the annotation to the layout's annotations array
-        layout["annotations"].append(annotation)  # type: ignore[attr-defined]
+    seasons = data["Seasons"]
+    cities = data["Cities"]
+    # Iterate over all cities
+    for city in range(len(cities)):
+        # Iterate over all seasons
+        for season in range(len(seasons)):
+            temperature = data["Temperatures"][city][season]
+            # Create the annotation
+            annotation = {
+                # The name of the season
+                "x": seasons[season],
+                # The name of the city
+                "y": cities[city],
+                # The temperature, as a formatted string
+                "text": f"{temperature}\N{DEGREE SIGN}C",
+                # Change the text color depending on the temperature
+                # so it results in a better contrast
+                "font": {"color": "white" if temperature < 14 else "black"},
+                # Remove the annotation arrow
+                "showarrow": False,
+            }
+            # Add the annotation to the layout's annotations array
+            layout["annotations"].append(annotation)  # type: ignore[attr-defined]
 
-page = """
+    page = """
 ## Heatmap - Annotated
 
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-colorscale.py

@@ -15,23 +15,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Temperatures": [
-        [17.2, 27.4, 28.6, 21.5],
-        [5.6, 15.1, 20.2, 8.1],
-        [26.6, 22.8, 21.8, 24.0],
-        [22.3, 15.5, 13.4, 19.6],
-    ],
-    "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
-    "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
-}
+if __name__ == "__main__":
+    data = {
+        "Temperatures": [
+            [17.2, 27.4, 28.6, 21.5],
+            [5.6, 15.1, 20.2, 8.1],
+            [26.6, 22.8, 21.8, 24.0],
+            [22.3, 15.5, 13.4, 19.6],
+        ],
+        "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
+        "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
+    }
 
-options = {"colorscale": "Portland"}
+    options = {"colorscale": "Portland"}
 
-page = """
+    page = """
 # Heatmap - Colorscale
 
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-drawing-on-top.py

@@ -26,66 +26,67 @@ def spiral(th):
     return (r * numpy.cos(th), r * numpy.sin(th))
 
 
-# Prepare Golden spiral data as a parametric curve
-(x, y) = spiral(numpy.linspace(-numpy.pi / 13, 4 * numpy.pi, 1000))
+if __name__ == "__main__":
+    # Prepare Golden spiral data as a parametric curve
+    (x, y) = spiral(numpy.linspace(-numpy.pi / 13, 4 * numpy.pi, 1000))
 
-# Prepare the heatmap x and y cell sizes along the axes
-golden_ratio = (1 + numpy.sqrt(5)) / 2.0  # Golden ratio
-grid_x = [0, 1, 1 + (1 / (golden_ratio**4)), 1 + (1 / (golden_ratio**3)), golden_ratio]
-grid_y = [
-    0,
-    1 / (golden_ratio**3),
-    1 / golden_ratio**3 + 1 / golden_ratio**4,
-    1 / (golden_ratio**2),
-    1,
-]
+    # Prepare the heatmap x and y cell sizes along the axes
+    golden_ratio = (1 + numpy.sqrt(5)) / 2.0  # Golden ratio
+    grid_x = [0, 1, 1 + (1 / (golden_ratio**4)), 1 + (1 / (golden_ratio**3)), golden_ratio]
+    grid_y = [
+        0,
+        1 / (golden_ratio**3),
+        1 / golden_ratio**3 + 1 / golden_ratio**4,
+        1 / (golden_ratio**2),
+        1,
+    ]
 
-# Main value is based on the Fibonacci sequence
-z = [[13, 3, 3, 5], [13, 2, 1, 5], [13, 10, 11, 12], [13, 8, 8, 8]]
+    # Main value is based on the Fibonacci sequence
+    z = [[13, 3, 3, 5], [13, 2, 1, 5], [13, 10, 11, 12], [13, 8, 8, 8]]
 
-# Group all data sets in a single array
-data = [
-    {
-        "z": z,
-    },
-    {"x": numpy.sort(grid_x), "y": numpy.sort(grid_y)},
-    {
-        "xSpiral": -x + x[0],
-        "ySpiral": y - y[0],
-    },
-]
+    # Group all data sets in a single array
+    data = [
+        {
+            "z": z,
+        },
+        {"x": numpy.sort(grid_x), "y": numpy.sort(grid_y)},
+        {
+            "xSpiral": -x + x[0],
+            "ySpiral": y - y[0],
+        },
+    ]
 
-# Axis template: hide all ticks, lines and labels
-axis = {
-    "range": [0, 2.0],
-    "showgrid": False,
-    "zeroline": False,
-    "showticklabels": False,
-    "ticks": "",
-    "title": "",
-}
+    # Axis template: hide all ticks, lines and labels
+    axis = {
+        "range": [0, 2.0],
+        "showgrid": False,
+        "zeroline": False,
+        "showticklabels": False,
+        "ticks": "",
+        "title": "",
+    }
 
-layout = {
-    # Use the axis template for both x and y axes
-    "xaxis": axis,
-    "yaxis": axis,
-}
+    layout = {
+        # Use the axis template for both x and y axes
+        "xaxis": axis,
+        "yaxis": axis,
+    }
 
-options = {
-    # Hide the color scale of the heatmap
-    "showscale": False
-}
+    options = {
+        # Hide the color scale of the heatmap
+        "showscale": False
+    }
 
-# Chart holds two traces, with different types
-types = ["heatmap", "scatter"]
-# x and y values for both traces
-xs = ["1/x", "2/xSpiral"]
-ys = ["1/y", "2/ySpiral"]
+    # Chart holds two traces, with different types
+    types = ["heatmap", "scatter"]
+    # x and y values for both traces
+    xs = ["1/x", "2/xSpiral"]
+    ys = ["1/y", "2/ySpiral"]
 
-page = """
+    page = """
 ## Heatmap - Drawing on top
 
 <|{data}|chart|type={types}|z[1]=0/z|x={xs}|y={ys}|layout={layout}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-simple.py

@@ -15,21 +15,22 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = {
-    "Temperatures": [
-        [17.2, 27.4, 28.6, 21.5],
-        [5.6, 15.1, 20.2, 8.1],
-        [26.6, 22.8, 21.8, 24.0],
-        [22.3, 15.5, 13.4, 19.6],
-    ],
-    "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
-    "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
-}
+if __name__ == "__main__":
+    data = {
+        "Temperatures": [
+            [17.2, 27.4, 28.6, 21.5],
+            [5.6, 15.1, 20.2, 8.1],
+            [26.6, 22.8, 21.8, 24.0],
+            [22.3, 15.5, 13.4, 19.6],
+        ],
+        "Cities": ["Hanoi", "Paris", "Rio", "Sydney"],
+        "Seasons": ["Winter", "Spring", "Summer", "Autumn"],
+    }
 
-page = """
+    page = """
 # Heatmap - Basic
 
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-unbalanced.py

@@ -15,24 +15,25 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = [
-    {
-        "Temperatures": [
-            [17.2, 27.4, 28.6, 21.5],
-            [5.6, 15.1, 20.2, 8.1],
-            [26.6, 22.8, 21.8, 24.0],
-            [22.3, 15.5, 13.4, 19.6],
-            [3.9, 18.9, 25.7, 9.8],
-        ],
-        "Cities": ["Hanoi", "Paris", "Rio", "Sydney", "Washington"],
-    },
-    {"Seasons": ["Winter", "Spring", "Summer", "Autumn"]},
-]
+if __name__ == "__main__":
+    data = [
+        {
+            "Temperatures": [
+                [17.2, 27.4, 28.6, 21.5],
+                [5.6, 15.1, 20.2, 8.1],
+                [26.6, 22.8, 21.8, 24.0],
+                [22.3, 15.5, 13.4, 19.6],
+                [3.9, 18.9, 25.7, 9.8],
+            ],
+            "Cities": ["Hanoi", "Paris", "Rio", "Sydney", "Washington"],
+        },
+        {"Seasons": ["Winter", "Spring", "Summer", "Autumn"]},
+    ]
 
-page = """
+    page = """
 # Heatmap - Unbalanced
 
 <|{data}|chart|type=heatmap|z=0/Temperatures|x=1/Seasons|y=0/Cities|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/heatmap-unequal-cell-sizes.py

@@ -19,47 +19,48 @@ import numpy as np
 
 from taipy.gui import Gui
 
-grid_size = 10
-data = [
-    {
-        # z is set to:
-        # - 0 if row+col is a multiple of 4
-        # - 1 if row+col is a multiple of 2
-        # - 0.5 otherwise
-        "z": [
-            [0.0 if (row + col) % 4 == 0 else 1 if (row + col) % 2 == 0 else 0.5 for col in range(grid_size)]
-            for row in range(grid_size)
-        ]
-    },
-    {
-        # A series of coordinates, growing exponentially
-        "x": [0] + list(accumulate(np.logspace(0, 1, grid_size))),
-        # A series of coordinates, shrinking exponentially
-        "y": [0] + list(accumulate(np.logspace(1, 0, grid_size))),
-    },
-]
+if __name__ == "__main__":
+    grid_size = 10
+    data = [
+        {
+            # z is set to:
+            # - 0 if row+col is a multiple of 4
+            # - 1 if row+col is a multiple of 2
+            # - 0.5 otherwise
+            "z": [
+                [0.0 if (row + col) % 4 == 0 else 1 if (row + col) % 2 == 0 else 0.5 for col in range(grid_size)]
+                for row in range(grid_size)
+            ]
+        },
+        {
+            # A series of coordinates, growing exponentially
+            "x": [0] + list(accumulate(np.logspace(0, 1, grid_size))),
+            # A series of coordinates, shrinking exponentially
+            "y": [0] + list(accumulate(np.logspace(1, 0, grid_size))),
+        },
+    ]
 
-# Axis template used in the layout object
-axis_template = {
-    # Don't show any line or tick or label
-    "showgrid": False,
-    "zeroline": False,
-    "ticks": "",
-    "showticklabels": False,
-    "visible": False,
-}
+    # Axis template used in the layout object
+    axis_template = {
+        # Don't show any line or tick or label
+        "showgrid": False,
+        "zeroline": False,
+        "ticks": "",
+        "showticklabels": False,
+        "visible": False,
+    }
 
-layout = {"xaxis": axis_template, "yaxis": axis_template}
+    layout = {"xaxis": axis_template, "yaxis": axis_template}
 
-options = {
-    # Remove the color scale display
-    "showscale": False
-}
+    options = {
+        # Remove the color scale display
+        "showscale": False
+    }
 
-page = """
+    page = """
 ## Heatmap - Unequal block sizes
 
 <|{data}|chart|type=heatmap|z=0/z|x=1/x|y=1/y|layout={layout}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-binning-function.py

@@ -15,41 +15,42 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Initial data set. y = count_of(x)
-samples = {"x": ["Apples", "Apples", "Apples", "Oranges", "Bananas", "Oranges"], "y": [5, 10, 3, 8, 5, 2]}
+if __name__ == "__main__":
+    # Initial data set. y = count_of(x)
+    samples = {"x": ["Apples", "Apples", "Apples", "Oranges", "Bananas", "Oranges"], "y": [5, 10, 3, 8, 5, 2]}
 
-# Create a data set array to allow for two traces
-data = [samples, samples]
+    # Create a data set array to allow for two traces
+    data = [samples, samples]
 
-# Gather those settings in a single dictionary
-properties = {
-    # 'x' of the first trace is the 'x' data from the first element of data
-    "x[1]": "0/x",
-    # 'y' of the first trace is the 'y' data from the first element of data
-    "y[1]": "0/y",
-    # 'x' of the second trace is the 'x' data from the second element of data
-    "x[2]": "1/x",
-    # 'y' of the second trace is the 'y' data from the second element of data
-    "y[2]": "1/y",
-    # Data set colors
-    "color": ["#cd5c5c", "#505070"],
-    # Data set names (for the legend)
-    "name": ["Count", "Sum"],
-    # Configure the binning functions
-    "options": [
-        # First trace: count the bins
-        {"histfunc": "count"},
-        # Second trace: sum the bin occurrences
-        {"histfunc": "sum"},
-    ],
-    # Set x axis name
-    "layout": {"xaxis": {"title": "Fruit"}},
-}
+    # Gather those settings in a single dictionary
+    properties = {
+        # 'x' of the first trace is the 'x' data from the first element of data
+        "x[1]": "0/x",
+        # 'y' of the first trace is the 'y' data from the first element of data
+        "y[1]": "0/y",
+        # 'x' of the second trace is the 'x' data from the second element of data
+        "x[2]": "1/x",
+        # 'y' of the second trace is the 'y' data from the second element of data
+        "y[2]": "1/y",
+        # Data set colors
+        "color": ["#cd5c5c", "#505070"],
+        # Data set names (for the legend)
+        "name": ["Count", "Sum"],
+        # Configure the binning functions
+        "options": [
+            # First trace: count the bins
+            {"histfunc": "count"},
+            # Second trace: sum the bin occurrences
+            {"histfunc": "sum"},
+        ],
+        # Set x axis name
+        "layout": {"xaxis": {"title": "Fruit"}},
+    }
 
-page = """
+    page = """
 # Histogram - Binning function
 
 <|{data}|chart|type=histogram|properties={properties}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-cumulative.py

@@ -17,18 +17,19 @@ import random
 
 from taipy.gui import Gui
 
-# Random data set
-data = [random.random() for _ in range(500)]
+if __name__ == "__main__":
+    # Random data set
+    data = [random.random() for _ in range(500)]
 
-options = {
-    # Enable the cumulative histogram
-    "cumulative": {"enabled": True}
-}
+    options = {
+        # Enable the cumulative histogram
+        "cumulative": {"enabled": True}
+    }
 
-page = """
+    page = """
 # Histogram - Cumulative
 
 <|{data}|chart|type=histogram|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-horizontal.py

@@ -17,13 +17,14 @@ import random
 
 from taipy.gui import Gui
 
-# Random data set
-data = {"Count": [random.random() for _ in range(100)]}
+if __name__ == "__main__":
+    # Random data set
+    data = {"Count": [random.random() for _ in range(100)]}
 
-page = """
+    page = """
 # Histograms - Horizontal
 
 <|{data}|chart|type=histogram|y=Count|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-nbins.py

@@ -17,29 +17,30 @@ import random
 
 from taipy.gui import Gui
 
-# Random set of 100 samples
-samples = {"x": [random.gauss(mu=0.0, sigma=1.0) for _ in range(100)]}
+if __name__ == "__main__":
+    # Random set of 100 samples
+    samples = {"x": [random.gauss(mu=0.0, sigma=1.0) for _ in range(100)]}
 
-# Use the same data for both traces
-data = [samples, samples]
+    # Use the same data for both traces
+    data = [samples, samples]
 
-options = [
-    # First data set displayed as green-ish, and 5 bins
-    {"marker": {"color": "#4A4"}, "nbinsx": 5},
-    # Second data set displayed as red-ish, and 25 bins
-    {"marker": {"color": "#A33"}, "nbinsx": 25},
-]
+    options = [
+        # First data set displayed as green-ish, and 5 bins
+        {"marker": {"color": "#4A4"}, "nbinsx": 5},
+        # Second data set displayed as red-ish, and 25 bins
+        {"marker": {"color": "#A33"}, "nbinsx": 25},
+    ]
 
-layout = {
-    # Overlay the two histograms
-    "barmode": "overlay",
-    # Hide the legend
-    "showlegend": False,
-}
+    layout = {
+        # Overlay the two histograms
+        "barmode": "overlay",
+        # Hide the legend
+        "showlegend": False,
+    }
 
-page = """
+    page = """
 # Histogram - NBins
 
 <|{data}|chart|type=histogram|options={options}|layout={layout}|>
-"""
-Gui(page).run()
+    """
+    Gui(page).run()

doc/gui/examples/charts/histogram-normalized.py

@@ -17,16 +17,17 @@ import random
 
 from taipy.gui import Gui
 
-# Random data set
-data = [random.random() for _ in range(100)]
+if __name__ == "__main__":
+    # Random data set
+    data = [random.random() for _ in range(100)]
 
-# Normalize to show bin probabilities
-options = {"histnorm": "probability"}
+    # Normalize to show bin probabilities
+    options = {"histnorm": "probability"}
 
-page = """
+    page = """
 # Histogram - Normalized
 
 <|{data}|chart|type=histogram|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-overlay.py

@@ -17,26 +17,27 @@ import random
 
 from taipy.gui import Gui
 
-# Data set made of two series of random numbers
-data = [{"x": [random.random() + 1 for _ in range(100)]}, {"x": [random.random() + 1.1 for _ in range(100)]}]
+if __name__ == "__main__":
+    # Data set made of two series of random numbers
+    data = [{"x": [random.random() + 1 for _ in range(100)]}, {"x": [random.random() + 1.1 for _ in range(100)]}]
 
-options = [
-    # First data set displayed as semi-transparent, green bars
-    {"opacity": 0.5, "marker": {"color": "green"}},
-    # Second data set displayed as semi-transparent, gray bars
-    {"opacity": 0.5, "marker": {"color": "#888"}},
-]
+    options = [
+        # First data set displayed as semi-transparent, green bars
+        {"opacity": 0.5, "marker": {"color": "green"}},
+        # Second data set displayed as semi-transparent, gray bars
+        {"opacity": 0.5, "marker": {"color": "#888"}},
+    ]
 
-layout = {
-    # Overlay the two histograms
-    "barmode": "overlay",
-    # Hide the legend
-    "showlegend": False,
-}
+    layout = {
+        # Overlay the two histograms
+        "barmode": "overlay",
+        # Hide the legend
+        "showlegend": False,
+    }
 
-page = """
+    page = """
 # Histogram - Overlay
 
 <|{data}|chart|type=histogram|options={options}|layout={layout}|>
-"""
-Gui(page).run()
+    """
+    Gui(page).run()

doc/gui/examples/charts/histogram-simple.py

@@ -17,13 +17,14 @@ import random
 
 from taipy import Gui
 
-# Random data set
-data = [random.gauss(0, 5) for _ in range(1000)]
+if __name__ == "__main__":
+    # Random data set
+    data = [random.gauss(0, 5) for _ in range(1000)]
 
-page = """
+    page = """
 # Histogram - Simple
 
 <|{data}|chart|type=histogram|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/histogram-stacked.py

@@ -17,21 +17,22 @@ import random
 
 from taipy.gui import Gui
 
-# Data set made of two series of random numbers
-data = {"A": [random.random() for _ in range(200)], "B": [random.random() for _ in range(200)]}
+if __name__ == "__main__":
+    # Data set made of two series of random numbers
+    data = {"A": [random.random() for _ in range(200)], "B": [random.random() for _ in range(200)]}
 
-# Names of the two traces
-names = ["A samples", "B samples"]
+    # Names of the two traces
+    names = ["A samples", "B samples"]
 
-layout = {
-    # Make the histogram stack the data sets
-    "barmode": "stack"
-}
+    layout = {
+        # Make the histogram stack the data sets
+        "barmode": "stack"
+    }
 
-page = """
+    page = """
 # Histogram - Stacked
 
 <|{data}|chart|type=histogram|x[1]=A|x[2]=B|name={names}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/line-style.py

@@ -17,1117 +17,1118 @@ import pandas
 
 from taipy.gui import Gui
 
-dates = pandas.date_range("2023-01-01", periods=365, freq="D")
-temp = [
-    -11.33333333,
-    -6,
-    -0.111111111,
-    1.444444444,
-    2.388888889,
-    4.555555556,
-    4.333333333,
-    0.666666667,
-    9,
-    9.611111111,
-    -0.555555556,
-    1.833333333,
-    -0.444444444,
-    2.166666667,
-    -4,
-    -12.05555556,
-    -2.722222222,
-    5,
-    9.888888889,
-    6.611111111,
-    -2.833333333,
-    -3.277777778,
-    -1.611111111,
-    -1.388888889,
-    5.777777778,
-    2.166666667,
-    -1.055555556,
-    1.777777778,
-    1.5,
-    8.444444444,
-    6.222222222,
-    -2.5,
-    -0.388888889,
-    6.111111111,
-    -1.5,
-    2.666666667,
-    -2.5,
-    0.611111111,
-    8.222222222,
-    2.333333333,
-    -9.333333333,
-    -7.666666667,
-    -6.277777778,
-    -0.611111111,
-    7.722222222,
-    6.111111111,
-    -4,
-    3.388888889,
-    9.333333333,
-    -6.333333333,
-    -15,
-    -12.94444444,
-    -8.722222222,
-    -6.222222222,
-    -2.833333333,
-    -2.5,
-    1.5,
-    3.444444444,
-    2.666666667,
-    0.888888889,
-    7.555555556,
-    12.66666667,
-    12.83333333,
-    1.777777778,
-    -0.111111111,
-    -1.055555556,
-    4.611111111,
-    11.16666667,
-    8.5,
-    0.5,
-    2.111111111,
-    4.722222222,
-    8.277777778,
-    10.66666667,
-    5.833333333,
-    5.555555556,
-    6.944444444,
-    1.722222222,
-    2.444444444,
-    6.111111111,
-    12.11111111,
-    15.55555556,
-    9.944444444,
-    10.27777778,
-    5.888888889,
-    1.388888889,
-    3.555555556,
-    1.222222222,
-    4.055555556,
-    7.833333333,
-    0.666666667,
-    10.05555556,
-    6.444444444,
-    4.555555556,
-    11,
-    3.555555556,
-    -0.555555556,
-    11.83333333,
-    7.222222222,
-    10.16666667,
-    17.5,
-    14.55555556,
-    6.777777778,
-    3.611111111,
-    5.888888889,
-    10.05555556,
-    16.61111111,
-    5.5,
-    7.055555556,
-    10.5,
-    1.555555556,
-    6.166666667,
-    11.05555556,
-    5.111111111,
-    6.055555556,
-    11,
-    11.05555556,
-    14.72222222,
-    19.16666667,
-    16.5,
-    12.61111111,
-    8.277777778,
-    6.611111111,
-    10.38888889,
-    15.38888889,
-    17.22222222,
-    18.27777778,
-    18.72222222,
-    17.05555556,
-    19.72222222,
-    16.83333333,
-    12.66666667,
-    11.66666667,
-    12.88888889,
-    14.77777778,
-    18,
-    19.44444444,
-    16.5,
-    9.722222222,
-    7.888888889,
-    13.72222222,
-    17.55555556,
-    18.27777778,
-    20.11111111,
-    21.66666667,
-    23.38888889,
-    23.5,
-    16.94444444,
-    16.27777778,
-    18.61111111,
-    20.83333333,
-    24.61111111,
-    18.27777778,
-    17.88888889,
-    22.27777778,
-    25.94444444,
-    25.27777778,
-    24.72222222,
-    25.61111111,
-    23.94444444,
-    26.33333333,
-    22.05555556,
-    20.83333333,
-    24.5,
-    27.83333333,
-    25.61111111,
-    23.11111111,
-    19.27777778,
-    16.44444444,
-    19.44444444,
-    17.22222222,
-    19.44444444,
-    22.16666667,
-    21.77777778,
-    17.38888889,
-    17.22222222,
-    23.88888889,
-    28.44444444,
-    29.44444444,
-    29.61111111,
-    21.05555556,
-    18.55555556,
-    25.27777778,
-    26.55555556,
-    24.55555556,
-    23.38888889,
-    22.55555556,
-    27.05555556,
-    27.66666667,
-    26.66666667,
-    27.61111111,
-    26.66666667,
-    24.77777778,
-    23,
-    26.5,
-    23.11111111,
-    19.83333333,
-    22.27777778,
-    24.61111111,
-    27.05555556,
-    27.05555556,
-    27.94444444,
-    27.33333333,
-    22.05555556,
-    21.5,
-    22,
-    19.72222222,
-    20.27777778,
-    17.88888889,
-    18.55555556,
-    18.94444444,
-    20,
-    22.05555556,
-    23.22222222,
-    24.38888889,
-    24.5,
-    24.5,
-    21.22222222,
-    20.83333333,
-    20.61111111,
-    22.05555556,
-    23.77777778,
-    24.16666667,
-    24.22222222,
-    21.83333333,
-    21.33333333,
-    21.88888889,
-    22.44444444,
-    23.11111111,
-    20.44444444,
-    16.88888889,
-    15.77777778,
-    17.44444444,
-    17.72222222,
-    23.11111111,
-    24.55555556,
-    24.88888889,
-    25.11111111,
-    25.27777778,
-    19.5,
-    19.55555556,
-    24.05555556,
-    24.27777778,
-    21.05555556,
-    19.88888889,
-    20.66666667,
-    20.27777778,
-    17.66666667,
-    16.44444444,
-    15.88888889,
-    18.44444444,
-    22.44444444,
-    23,
-    24.72222222,
-    24.16666667,
-    25.94444444,
-    24.44444444,
-    23.33333333,
-    25.22222222,
-    25,
-    23.88888889,
-    23.72222222,
-    18.94444444,
-    16.22222222,
-    19.5,
-    21.22222222,
-    19.72222222,
-    13.22222222,
-    11.88888889,
-    16.55555556,
-    10.05555556,
-    12.16666667,
-    11.5,
-    10.22222222,
-    17.27777778,
-    21.72222222,
-    13.83333333,
-    13,
-    6.944444444,
-    6.388888889,
-    4.222222222,
-    2.5,
-    1.111111111,
-    3.055555556,
-    6.388888889,
-    10.44444444,
-    -2,
-    -2.222222222,
-    4.388888889,
-    8.333333333,
-    11.11111111,
-    12.66666667,
-    10.88888889,
-    12.83333333,
-    14.16666667,
-    12.55555556,
-    12.05555556,
-    11.22222222,
-    12.44444444,
-    14.38888889,
-    12,
-    15.83333333,
-    6.722222222,
-    2.5,
-    4.833333333,
-    7.5,
-    8.888888889,
-    4,
-    7.388888889,
-    3.888888889,
-    1.611111111,
-    -0.333333333,
-    -2,
-    4.833333333,
-    -1.055555556,
-    -5.611111111,
-    -2.388888889,
-    5.722222222,
-    8.444444444,
-    5.277777778,
-    0.5,
-    -2.5,
-    1.111111111,
-    2.111111111,
-    5.777777778,
-    7.555555556,
-    7.555555556,
-    4.111111111,
-    -0.388888889,
-    -1,
-    4.944444444,
-    9.444444444,
-    4.722222222,
-    -0.166666667,
-    0.5,
-    -2.444444444,
-    -2.722222222,
-    -2.888888889,
-    -1.111111111,
-    -4.944444444,
-    -3.111111111,
-    -1.444444444,
-    -0.833333333,
-    2.333333333,
-    6.833333333,
-    4.722222222,
-    0.888888889,
-    0.666666667,
-    4.611111111,
-    4.666666667,
-    4.444444444,
-    6.777777778,
-    5.833333333,
-    0.5,
-    4.888888889,
-    1.444444444,
-    -2.111111111,
-    2.444444444,
-    -0.111111111,
-    -2.555555556,
-    -4.611111111,
-    -8.666666667,
-    -8.055555556,
-    1.555555556,
-    -4.777777778,
-]
-min = [
-    -14.33333333,
-    -12.9,
-    -3.311111111,
-    -4.955555556,
-    -3.611111111,
-    0.555555556,
-    1.133333333,
-    -5.133333333,
-    2.3,
-    3.911111111,
-    -7.055555556,
-    -1.366666667,
-    -4.844444444,
-    -3.333333333,
-    -6.1,
-    -17.15555556,
-    -4.822222222,
-    0.4,
-    3.488888889,
-    4.211111111,
-    -6.433333333,
-    -7.577777778,
-    -7.111111111,
-    -7.088888889,
-    1.577777778,
-    -3.433333333,
-    -4.355555556,
-    -0.722222222,
-    -2.1,
-    2.044444444,
-    2.222222222,
-    -4.7,
-    -2.388888889,
-    4.111111111,
-    -5,
-    -0.133333333,
-    -5.3,
-    -2.288888889,
-    6.022222222,
-    -1.766666667,
-    -15.53333333,
-    -13.46666667,
-    -9.277777778,
-    -3.211111111,
-    3.122222222,
-    1.411111111,
-    -6.8,
-    1.388888889,
-    5.333333333,
-    -9.833333333,
-    -22,
-    -19.74444444,
-    -14.62222222,
-    -9.622222222,
-    -8.433333333,
-    -8.5,
-    -2.8,
-    0.144444444,
-    -3.233333333,
-    -3.411111111,
-    5.355555556,
-    8.366666667,
-    7.333333333,
-    -0.322222222,
-    -6.911111111,
-    -4.955555556,
-    -1.588888889,
-    4.966666667,
-    2.5,
-    -4.3,
-    -1.888888889,
-    -1.777777778,
-    2.477777778,
-    3.766666667,
-    0.533333333,
-    1.755555556,
-    2.944444444,
-    -4.977777778,
-    -4.055555556,
-    1.711111111,
-    6.011111111,
-    13.15555556,
-    5.044444444,
-    6.577777778,
-    3.388888889,
-    -1.011111111,
-    -0.244444444,
-    -2.477777778,
-    -1.444444444,
-    2.533333333,
-    -6.333333333,
-    4.255555556,
-    1.944444444,
-    0.855555556,
-    5.4,
-    -1.244444444,
-    -2.855555556,
-    4.833333333,
-    2.722222222,
-    6.466666667,
-    14.5,
-    9.855555556,
-    2.277777778,
-    -3.188888889,
-    0.788888889,
-    4.155555556,
-    13.41111111,
-    2.3,
-    0.855555556,
-    8.4,
-    -0.444444444,
-    1.166666667,
-    7.755555556,
-    -0.288888889,
-    -0.244444444,
-    8.7,
-    5.555555556,
-    8.222222222,
-    16.26666667,
-    14.4,
-    5.711111111,
-    5.177777778,
-    4.511111111,
-    5.988888889,
-    10.08888889,
-    10.52222222,
-    15.37777778,
-    12.42222222,
-    14.95555556,
-    15.22222222,
-    11.93333333,
-    6.866666667,
-    6.866666667,
-    9.688888889,
-    11.57777778,
-    12,
-    13.34444444,
-    11.3,
-    6.222222222,
-    2.088888889,
-    8.322222222,
-    14.05555556,
-    13.77777778,
-    16.91111111,
-    16.86666667,
-    16.68888889,
-    18.5,
-    12.54444444,
-    12.27777778,
-    15.91111111,
-    15.03333333,
-    22.11111111,
-    15.77777778,
-    13.68888889,
-    17.87777778,
-    19.94444444,
-    18.57777778,
-    18.62222222,
-    20.11111111,
-    17.14444444,
-    20.43333333,
-    15.75555556,
-    17.33333333,
-    20,
-    23.03333333,
-    19.61111111,
-    18.51111111,
-    15.27777778,
-    11.44444444,
-    13.64444444,
-    11.42222222,
-    16.14444444,
-    19.76666667,
-    18.77777778,
-    11.88888889,
-    12.32222222,
-    20.78888889,
-    25.04444444,
-    25.34444444,
-    23.81111111,
-    18.35555556,
-    11.85555556,
-    18.37777778,
-    23.15555556,
-    21.55555556,
-    17.48888889,
-    19.05555556,
-    20.25555556,
-    23.86666667,
-    23.86666667,
-    21.41111111,
-    21.16666667,
-    18.67777778,
-    18.1,
-    24.4,
-    19.01111111,
-    17.13333333,
-    18.27777778,
-    21.71111111,
-    22.85555556,
-    22.65555556,
-    25.14444444,
-    24.13333333,
-    17.95555556,
-    14.7,
-    15.1,
-    16.02222222,
-    14.27777778,
-    11.18888889,
-    13.65555556,
-    16.74444444,
-    16.7,
-    17.65555556,
-    16.62222222,
-    21.68888889,
-    19.6,
-    18.6,
-    15.52222222,
-    18.53333333,
-    17.01111111,
-    17.75555556,
-    20.47777778,
-    17.76666667,
-    22.22222222,
-    18.23333333,
-    17.83333333,
-    15.38888889,
-    19.64444444,
-    17.81111111,
-    15.44444444,
-    14.88888889,
-    13.07777778,
-    15.24444444,
-    11.82222222,
-    20.81111111,
-    21.45555556,
-    18.98888889,
-    19.71111111,
-    19.27777778,
-    12.7,
-    15.05555556,
-    19.15555556,
-    20.77777778,
-    15.35555556,
-    17.68888889,
-    18.26666667,
-    15.47777778,
-    12.76666667,
-    10.54444444,
-    13.38888889,
-    12.54444444,
-    19.84444444,
-    19.5,
-    21.92222222,
-    17.86666667,
-    22.44444444,
-    19.64444444,
-    20.73333333,
-    22.02222222,
-    19,
-    20.48888889,
-    19.02222222,
-    16.44444444,
-    14.22222222,
-    16.3,
-    16.42222222,
-    17.22222222,
-    8.322222222,
-    8.288888889,
-    13.95555556,
-    5.555555556,
-    5.666666667,
-    7.7,
-    4.022222222,
-    11.77777778,
-    16.42222222,
-    11.83333333,
-    9.7,
-    0.044444444,
-    3.688888889,
-    -2.077777778,
-    0.1,
-    -5.388888889,
-    -3.244444444,
-    0.688888889,
-    5.744444444,
-    -7.7,
-    -7.022222222,
-    -0.211111111,
-    4.833333333,
-    8.111111111,
-    5.766666667,
-    7.888888889,
-    10.43333333,
-    11.56666667,
-    10.15555556,
-    7.155555556,
-    4.522222222,
-    7.144444444,
-    10.88888889,
-    9.5,
-    12.13333333,
-    4.022222222,
-    -3.9,
-    1.433333333,
-    0.7,
-    3.188888889,
-    -1.7,
-    3.588888889,
-    -0.111111111,
-    -2.788888889,
-    -7.133333333,
-    -5,
-    0.733333333,
-    -7.555555556,
-    -12.51111111,
-    -8.188888889,
-    3.122222222,
-    2.944444444,
-    0.477777778,
-    -3.2,
-    -9.2,
-    -4.788888889,
-    -0.288888889,
-    1.077777778,
-    4.755555556,
-    5.455555556,
-    0.511111111,
-    -3.888888889,
-    -7.4,
-    -1.355555556,
-    5.144444444,
-    0.122222222,
-    -5.166666667,
-    -5,
-    -5.144444444,
-    -8.822222222,
-    -6.388888889,
-    -6.811111111,
-    -8.944444444,
-    -10.11111111,
-    -7.144444444,
-    -5.133333333,
-    -1.166666667,
-    1.833333333,
-    -1.477777778,
-    -1.811111111,
-    -2.433333333,
-    -1.188888889,
-    -2.333333333,
-    0.744444444,
-    1.877777778,
-    1.333333333,
-    -1.7,
-    0.888888889,
-    -3.855555556,
-    -8.211111111,
-    -1.055555556,
-    -4.211111111,
-    -7.355555556,
-    -8.111111111,
-    -10.96666667,
-    -13.05555556,
-    -4.644444444,
-    -7.577777778,
-]
-max = [
-    -7.233333333,
-    -1.6,
-    5.488888889,
-    7.744444444,
-    6.188888889,
-    6.555555556,
-    10.53333333,
-    6.766666667,
-    14.1,
-    14.11111111,
-    2.044444444,
-    4.633333333,
-    2.055555556,
-    8.666666667,
-    -1.4,
-    -5.555555556,
-    4.177777778,
-    11.8,
-    15.58888889,
-    12.31111111,
-    3.666666667,
-    -0.977777778,
-    1.288888889,
-    4.211111111,
-    9.377777778,
-    5.266666667,
-    2.144444444,
-    3.977777778,
-    7.2,
-    11.94444444,
-    11.32222222,
-    4,
-    6.611111111,
-    8.211111111,
-    3.5,
-    8.866666667,
-    3.6,
-    3.711111111,
-    13.12222222,
-    7.833333333,
-    -3.333333333,
-    -2.166666667,
-    -2.877777778,
-    5.188888889,
-    13.12222222,
-    12.11111111,
-    -0.7,
-    6.688888889,
-    14.03333333,
-    -2.433333333,
-    -8.6,
-    -8.244444444,
-    -2.122222222,
-    -2.722222222,
-    1.266666667,
-    2.8,
-    5.7,
-    6.944444444,
-    5.066666667,
-    5.688888889,
-    13.35555556,
-    16.66666667,
-    17.33333333,
-    7.277777778,
-    6.388888889,
-    1.344444444,
-    9.111111111,
-    17.96666667,
-    12.8,
-    5.8,
-    6.911111111,
-    6.822222222,
-    11.87777778,
-    13.16666667,
-    9.233333333,
-    8.655555556,
-    10.04444444,
-    7.022222222,
-    7.644444444,
-    8.311111111,
-    16.71111111,
-    18.85555556,
-    12.14444444,
-    13.27777778,
-    11.18888889,
-    7.088888889,
-    8.255555556,
-    7.522222222,
-    9.955555556,
-    9.933333333,
-    4.866666667,
-    15.25555556,
-    9.244444444,
-    9.755555556,
-    14,
-    8.955555556,
-    2.344444444,
-    17.43333333,
-    12.12222222,
-    13.46666667,
-    23,
-    18.45555556,
-    12.77777778,
-    7.211111111,
-    8.588888889,
-    14.35555556,
-    19.01111111,
-    12.4,
-    9.155555556,
-    15.6,
-    4.955555556,
-    8.966666667,
-    16.95555556,
-    9.511111111,
-    10.15555556,
-    16,
-    14.45555556,
-    21.02222222,
-    25.76666667,
-    20.5,
-    15.71111111,
-    11.67777778,
-    12.81111111,
-    12.88888889,
-    17.58888889,
-    23.12222222,
-    21.77777778,
-    24.42222222,
-    20.05555556,
-    24.32222222,
-    18.83333333,
-    19.56666667,
-    14.96666667,
-    19.68888889,
-    18.57777778,
-    23,
-    23.34444444,
-    20.7,
-    11.82222222,
-    11.48888889,
-    17.52222222,
-    22.55555556,
-    20.47777778,
-    23.01111111,
-    27.86666667,
-    30.28888889,
-    30.3,
-    22.94444444,
-    18.57777778,
-    25.51111111,
-    24.13333333,
-    30.01111111,
-    24.77777778,
-    20.28888889,
-    28.67777778,
-    32.74444444,
-    31.37777778,
-    28.52222222,
-    31.81111111,
-    27.24444444,
-    32.53333333,
-    26.15555556,
-    24.63333333,
-    28.3,
-    31.23333333,
-    32.21111111,
-    28.21111111,
-    23.07777778,
-    21.64444444,
-    24.34444444,
-    19.62222222,
-    25.14444444,
-    24.46666667,
-    23.87777778,
-    21.28888889,
-    20.22222222,
-    29.98888889,
-    32.04444444,
-    36.44444444,
-    36.01111111,
-    24.85555556,
-    23.45555556,
-    29.17777778,
-    32.25555556,
-    28.75555556,
-    30.28888889,
-    28.85555556,
-    30.45555556,
-    31.26666667,
-    28.86666667,
-    33.31111111,
-    30.66666667,
-    28.67777778,
-    27.4,
-    32.2,
-    25.41111111,
-    22.23333333,
-    26.67777778,
-    30.21111111,
-    29.15555556,
-    29.65555556,
-    31.94444444,
-    31.43333333,
-    28.35555556,
-    24.8,
-    25.5,
-    25.42222222,
-    24.17777778,
-    20.88888889,
-    24.35555556,
-    25.54444444,
-    22,
-    27.95555556,
-    29.42222222,
-    28.88888889,
-    26.8,
-    28.2,
-    26.92222222,
-    24.13333333,
-    22.61111111,
-    26.15555556,
-    30.57777778,
-    30.86666667,
-    29.92222222,
-    27.33333333,
-    23.43333333,
-    24.68888889,
-    26.94444444,
-    28.81111111,
-    25.54444444,
-    22.48888889,
-    21.67777778,
-    19.74444444,
-    23.82222222,
-    25.91111111,
-    30.85555556,
-    28.48888889,
-    29.21111111,
-    28.37777778,
-    22.4,
-    25.55555556,
-    27.35555556,
-    30.67777778,
-    27.95555556,
-    25.98888889,
-    23.46666667,
-    25.37777778,
-    20.46666667,
-    22.54444444,
-    20.18888889,
-    22.24444444,
-    26.84444444,
-    25.8,
-    29.62222222,
-    26.36666667,
-    32.24444444,
-    29.84444444,
-    28.33333333,
-    31.22222222,
-    29.9,
-    29.98888889,
-    27.42222222,
-    25.54444444,
-    20.22222222,
-    24,
-    24.52222222,
-    25.02222222,
-    16.12222222,
-    17.58888889,
-    23.25555556,
-    15.75555556,
-    18.66666667,
-    18.4,
-    12.52222222,
-    20.07777778,
-    28.62222222,
-    17.23333333,
-    16.6,
-    13.34444444,
-    10.98888889,
-    9.522222222,
-    5.8,
-    6.811111111,
-    6.555555556,
-    12.18888889,
-    12.64444444,
-    4.2,
-    3.577777778,
-    8.888888889,
-    15.23333333,
-    16.11111111,
-    18.36666667,
-    16.98888889,
-    15.63333333,
-    16.46666667,
-    15.55555556,
-    15.65555556,
-    17.42222222,
-    18.74444444,
-    19.48888889,
-    15.9,
-    19.73333333,
-    13.02222222,
-    8.1,
-    8.933333333,
-    11.3,
-    12.38888889,
-    8.3,
-    12.38888889,
-    6.388888889,
-    4.211111111,
-    4.666666667,
-    0.7,
-    7.133333333,
-    2.344444444,
-    1.088888889,
-    0.111111111,
-    11.62222222,
-    10.84444444,
-    8.777777778,
-    3.5,
-    3.4,
-    7.211111111,
-    5.711111111,
-    9.677777778,
-    12.25555556,
-    10.15555556,
-    6.511111111,
-    4.911111111,
-    1.5,
-    11.44444444,
-    15.54444444,
-    8.122222222,
-    6.233333333,
-    7,
-    4.355555556,
-    0.277777778,
-    3.711111111,
-    2.888888889,
-    1.555555556,
-    3.888888889,
-    4.555555556,
-    5.666666667,
-    7.833333333,
-    9.833333333,
-    10.02222222,
-    6.288888889,
-    5.366666667,
-    11.41111111,
-    9.566666667,
-    9.744444444,
-    13.57777778,
-    9.433333333,
-    3.1,
-    11.08888889,
-    3.844444444,
-    2.488888889,
-    7.544444444,
-    4.488888889,
-    -0.455555556,
-    -2.111111111,
-    -3.566666667,
-    -1.955555556,
-    3.955555556,
-    1.222222222,
-]
+if __name__ == "__main__":
+    dates = pandas.date_range("2023-01-01", periods=365, freq="D")
+    temp = [
+        -11.33333333,
+        -6,
+        -0.111111111,
+        1.444444444,
+        2.388888889,
+        4.555555556,
+        4.333333333,
+        0.666666667,
+        9,
+        9.611111111,
+        -0.555555556,
+        1.833333333,
+        -0.444444444,
+        2.166666667,
+        -4,
+        -12.05555556,
+        -2.722222222,
+        5,
+        9.888888889,
+        6.611111111,
+        -2.833333333,
+        -3.277777778,
+        -1.611111111,
+        -1.388888889,
+        5.777777778,
+        2.166666667,
+        -1.055555556,
+        1.777777778,
+        1.5,
+        8.444444444,
+        6.222222222,
+        -2.5,
+        -0.388888889,
+        6.111111111,
+        -1.5,
+        2.666666667,
+        -2.5,
+        0.611111111,
+        8.222222222,
+        2.333333333,
+        -9.333333333,
+        -7.666666667,
+        -6.277777778,
+        -0.611111111,
+        7.722222222,
+        6.111111111,
+        -4,
+        3.388888889,
+        9.333333333,
+        -6.333333333,
+        -15,
+        -12.94444444,
+        -8.722222222,
+        -6.222222222,
+        -2.833333333,
+        -2.5,
+        1.5,
+        3.444444444,
+        2.666666667,
+        0.888888889,
+        7.555555556,
+        12.66666667,
+        12.83333333,
+        1.777777778,
+        -0.111111111,
+        -1.055555556,
+        4.611111111,
+        11.16666667,
+        8.5,
+        0.5,
+        2.111111111,
+        4.722222222,
+        8.277777778,
+        10.66666667,
+        5.833333333,
+        5.555555556,
+        6.944444444,
+        1.722222222,
+        2.444444444,
+        6.111111111,
+        12.11111111,
+        15.55555556,
+        9.944444444,
+        10.27777778,
+        5.888888889,
+        1.388888889,
+        3.555555556,
+        1.222222222,
+        4.055555556,
+        7.833333333,
+        0.666666667,
+        10.05555556,
+        6.444444444,
+        4.555555556,
+        11,
+        3.555555556,
+        -0.555555556,
+        11.83333333,
+        7.222222222,
+        10.16666667,
+        17.5,
+        14.55555556,
+        6.777777778,
+        3.611111111,
+        5.888888889,
+        10.05555556,
+        16.61111111,
+        5.5,
+        7.055555556,
+        10.5,
+        1.555555556,
+        6.166666667,
+        11.05555556,
+        5.111111111,
+        6.055555556,
+        11,
+        11.05555556,
+        14.72222222,
+        19.16666667,
+        16.5,
+        12.61111111,
+        8.277777778,
+        6.611111111,
+        10.38888889,
+        15.38888889,
+        17.22222222,
+        18.27777778,
+        18.72222222,
+        17.05555556,
+        19.72222222,
+        16.83333333,
+        12.66666667,
+        11.66666667,
+        12.88888889,
+        14.77777778,
+        18,
+        19.44444444,
+        16.5,
+        9.722222222,
+        7.888888889,
+        13.72222222,
+        17.55555556,
+        18.27777778,
+        20.11111111,
+        21.66666667,
+        23.38888889,
+        23.5,
+        16.94444444,
+        16.27777778,
+        18.61111111,
+        20.83333333,
+        24.61111111,
+        18.27777778,
+        17.88888889,
+        22.27777778,
+        25.94444444,
+        25.27777778,
+        24.72222222,
+        25.61111111,
+        23.94444444,
+        26.33333333,
+        22.05555556,
+        20.83333333,
+        24.5,
+        27.83333333,
+        25.61111111,
+        23.11111111,
+        19.27777778,
+        16.44444444,
+        19.44444444,
+        17.22222222,
+        19.44444444,
+        22.16666667,
+        21.77777778,
+        17.38888889,
+        17.22222222,
+        23.88888889,
+        28.44444444,
+        29.44444444,
+        29.61111111,
+        21.05555556,
+        18.55555556,
+        25.27777778,
+        26.55555556,
+        24.55555556,
+        23.38888889,
+        22.55555556,
+        27.05555556,
+        27.66666667,
+        26.66666667,
+        27.61111111,
+        26.66666667,
+        24.77777778,
+        23,
+        26.5,
+        23.11111111,
+        19.83333333,
+        22.27777778,
+        24.61111111,
+        27.05555556,
+        27.05555556,
+        27.94444444,
+        27.33333333,
+        22.05555556,
+        21.5,
+        22,
+        19.72222222,
+        20.27777778,
+        17.88888889,
+        18.55555556,
+        18.94444444,
+        20,
+        22.05555556,
+        23.22222222,
+        24.38888889,
+        24.5,
+        24.5,
+        21.22222222,
+        20.83333333,
+        20.61111111,
+        22.05555556,
+        23.77777778,
+        24.16666667,
+        24.22222222,
+        21.83333333,
+        21.33333333,
+        21.88888889,
+        22.44444444,
+        23.11111111,
+        20.44444444,
+        16.88888889,
+        15.77777778,
+        17.44444444,
+        17.72222222,
+        23.11111111,
+        24.55555556,
+        24.88888889,
+        25.11111111,
+        25.27777778,
+        19.5,
+        19.55555556,
+        24.05555556,
+        24.27777778,
+        21.05555556,
+        19.88888889,
+        20.66666667,
+        20.27777778,
+        17.66666667,
+        16.44444444,
+        15.88888889,
+        18.44444444,
+        22.44444444,
+        23,
+        24.72222222,
+        24.16666667,
+        25.94444444,
+        24.44444444,
+        23.33333333,
+        25.22222222,
+        25,
+        23.88888889,
+        23.72222222,
+        18.94444444,
+        16.22222222,
+        19.5,
+        21.22222222,
+        19.72222222,
+        13.22222222,
+        11.88888889,
+        16.55555556,
+        10.05555556,
+        12.16666667,
+        11.5,
+        10.22222222,
+        17.27777778,
+        21.72222222,
+        13.83333333,
+        13,
+        6.944444444,
+        6.388888889,
+        4.222222222,
+        2.5,
+        1.111111111,
+        3.055555556,
+        6.388888889,
+        10.44444444,
+        -2,
+        -2.222222222,
+        4.388888889,
+        8.333333333,
+        11.11111111,
+        12.66666667,
+        10.88888889,
+        12.83333333,
+        14.16666667,
+        12.55555556,
+        12.05555556,
+        11.22222222,
+        12.44444444,
+        14.38888889,
+        12,
+        15.83333333,
+        6.722222222,
+        2.5,
+        4.833333333,
+        7.5,
+        8.888888889,
+        4,
+        7.388888889,
+        3.888888889,
+        1.611111111,
+        -0.333333333,
+        -2,
+        4.833333333,
+        -1.055555556,
+        -5.611111111,
+        -2.388888889,
+        5.722222222,
+        8.444444444,
+        5.277777778,
+        0.5,
+        -2.5,
+        1.111111111,
+        2.111111111,
+        5.777777778,
+        7.555555556,
+        7.555555556,
+        4.111111111,
+        -0.388888889,
+        -1,
+        4.944444444,
+        9.444444444,
+        4.722222222,
+        -0.166666667,
+        0.5,
+        -2.444444444,
+        -2.722222222,
+        -2.888888889,
+        -1.111111111,
+        -4.944444444,
+        -3.111111111,
+        -1.444444444,
+        -0.833333333,
+        2.333333333,
+        6.833333333,
+        4.722222222,
+        0.888888889,
+        0.666666667,
+        4.611111111,
+        4.666666667,
+        4.444444444,
+        6.777777778,
+        5.833333333,
+        0.5,
+        4.888888889,
+        1.444444444,
+        -2.111111111,
+        2.444444444,
+        -0.111111111,
+        -2.555555556,
+        -4.611111111,
+        -8.666666667,
+        -8.055555556,
+        1.555555556,
+        -4.777777778,
+    ]
+    min = [
+        -14.33333333,
+        -12.9,
+        -3.311111111,
+        -4.955555556,
+        -3.611111111,
+        0.555555556,
+        1.133333333,
+        -5.133333333,
+        2.3,
+        3.911111111,
+        -7.055555556,
+        -1.366666667,
+        -4.844444444,
+        -3.333333333,
+        -6.1,
+        -17.15555556,
+        -4.822222222,
+        0.4,
+        3.488888889,
+        4.211111111,
+        -6.433333333,
+        -7.577777778,
+        -7.111111111,
+        -7.088888889,
+        1.577777778,
+        -3.433333333,
+        -4.355555556,
+        -0.722222222,
+        -2.1,
+        2.044444444,
+        2.222222222,
+        -4.7,
+        -2.388888889,
+        4.111111111,
+        -5,
+        -0.133333333,
+        -5.3,
+        -2.288888889,
+        6.022222222,
+        -1.766666667,
+        -15.53333333,
+        -13.46666667,
+        -9.277777778,
+        -3.211111111,
+        3.122222222,
+        1.411111111,
+        -6.8,
+        1.388888889,
+        5.333333333,
+        -9.833333333,
+        -22,
+        -19.74444444,
+        -14.62222222,
+        -9.622222222,
+        -8.433333333,
+        -8.5,
+        -2.8,
+        0.144444444,
+        -3.233333333,
+        -3.411111111,
+        5.355555556,
+        8.366666667,
+        7.333333333,
+        -0.322222222,
+        -6.911111111,
+        -4.955555556,
+        -1.588888889,
+        4.966666667,
+        2.5,
+        -4.3,
+        -1.888888889,
+        -1.777777778,
+        2.477777778,
+        3.766666667,
+        0.533333333,
+        1.755555556,
+        2.944444444,
+        -4.977777778,
+        -4.055555556,
+        1.711111111,
+        6.011111111,
+        13.15555556,
+        5.044444444,
+        6.577777778,
+        3.388888889,
+        -1.011111111,
+        -0.244444444,
+        -2.477777778,
+        -1.444444444,
+        2.533333333,
+        -6.333333333,
+        4.255555556,
+        1.944444444,
+        0.855555556,
+        5.4,
+        -1.244444444,
+        -2.855555556,
+        4.833333333,
+        2.722222222,
+        6.466666667,
+        14.5,
+        9.855555556,
+        2.277777778,
+        -3.188888889,
+        0.788888889,
+        4.155555556,
+        13.41111111,
+        2.3,
+        0.855555556,
+        8.4,
+        -0.444444444,
+        1.166666667,
+        7.755555556,
+        -0.288888889,
+        -0.244444444,
+        8.7,
+        5.555555556,
+        8.222222222,
+        16.26666667,
+        14.4,
+        5.711111111,
+        5.177777778,
+        4.511111111,
+        5.988888889,
+        10.08888889,
+        10.52222222,
+        15.37777778,
+        12.42222222,
+        14.95555556,
+        15.22222222,
+        11.93333333,
+        6.866666667,
+        6.866666667,
+        9.688888889,
+        11.57777778,
+        12,
+        13.34444444,
+        11.3,
+        6.222222222,
+        2.088888889,
+        8.322222222,
+        14.05555556,
+        13.77777778,
+        16.91111111,
+        16.86666667,
+        16.68888889,
+        18.5,
+        12.54444444,
+        12.27777778,
+        15.91111111,
+        15.03333333,
+        22.11111111,
+        15.77777778,
+        13.68888889,
+        17.87777778,
+        19.94444444,
+        18.57777778,
+        18.62222222,
+        20.11111111,
+        17.14444444,
+        20.43333333,
+        15.75555556,
+        17.33333333,
+        20,
+        23.03333333,
+        19.61111111,
+        18.51111111,
+        15.27777778,
+        11.44444444,
+        13.64444444,
+        11.42222222,
+        16.14444444,
+        19.76666667,
+        18.77777778,
+        11.88888889,
+        12.32222222,
+        20.78888889,
+        25.04444444,
+        25.34444444,
+        23.81111111,
+        18.35555556,
+        11.85555556,
+        18.37777778,
+        23.15555556,
+        21.55555556,
+        17.48888889,
+        19.05555556,
+        20.25555556,
+        23.86666667,
+        23.86666667,
+        21.41111111,
+        21.16666667,
+        18.67777778,
+        18.1,
+        24.4,
+        19.01111111,
+        17.13333333,
+        18.27777778,
+        21.71111111,
+        22.85555556,
+        22.65555556,
+        25.14444444,
+        24.13333333,
+        17.95555556,
+        14.7,
+        15.1,
+        16.02222222,
+        14.27777778,
+        11.18888889,
+        13.65555556,
+        16.74444444,
+        16.7,
+        17.65555556,
+        16.62222222,
+        21.68888889,
+        19.6,
+        18.6,
+        15.52222222,
+        18.53333333,
+        17.01111111,
+        17.75555556,
+        20.47777778,
+        17.76666667,
+        22.22222222,
+        18.23333333,
+        17.83333333,
+        15.38888889,
+        19.64444444,
+        17.81111111,
+        15.44444444,
+        14.88888889,
+        13.07777778,
+        15.24444444,
+        11.82222222,
+        20.81111111,
+        21.45555556,
+        18.98888889,
+        19.71111111,
+        19.27777778,
+        12.7,
+        15.05555556,
+        19.15555556,
+        20.77777778,
+        15.35555556,
+        17.68888889,
+        18.26666667,
+        15.47777778,
+        12.76666667,
+        10.54444444,
+        13.38888889,
+        12.54444444,
+        19.84444444,
+        19.5,
+        21.92222222,
+        17.86666667,
+        22.44444444,
+        19.64444444,
+        20.73333333,
+        22.02222222,
+        19,
+        20.48888889,
+        19.02222222,
+        16.44444444,
+        14.22222222,
+        16.3,
+        16.42222222,
+        17.22222222,
+        8.322222222,
+        8.288888889,
+        13.95555556,
+        5.555555556,
+        5.666666667,
+        7.7,
+        4.022222222,
+        11.77777778,
+        16.42222222,
+        11.83333333,
+        9.7,
+        0.044444444,
+        3.688888889,
+        -2.077777778,
+        0.1,
+        -5.388888889,
+        -3.244444444,
+        0.688888889,
+        5.744444444,
+        -7.7,
+        -7.022222222,
+        -0.211111111,
+        4.833333333,
+        8.111111111,
+        5.766666667,
+        7.888888889,
+        10.43333333,
+        11.56666667,
+        10.15555556,
+        7.155555556,
+        4.522222222,
+        7.144444444,
+        10.88888889,
+        9.5,
+        12.13333333,
+        4.022222222,
+        -3.9,
+        1.433333333,
+        0.7,
+        3.188888889,
+        -1.7,
+        3.588888889,
+        -0.111111111,
+        -2.788888889,
+        -7.133333333,
+        -5,
+        0.733333333,
+        -7.555555556,
+        -12.51111111,
+        -8.188888889,
+        3.122222222,
+        2.944444444,
+        0.477777778,
+        -3.2,
+        -9.2,
+        -4.788888889,
+        -0.288888889,
+        1.077777778,
+        4.755555556,
+        5.455555556,
+        0.511111111,
+        -3.888888889,
+        -7.4,
+        -1.355555556,
+        5.144444444,
+        0.122222222,
+        -5.166666667,
+        -5,
+        -5.144444444,
+        -8.822222222,
+        -6.388888889,
+        -6.811111111,
+        -8.944444444,
+        -10.11111111,
+        -7.144444444,
+        -5.133333333,
+        -1.166666667,
+        1.833333333,
+        -1.477777778,
+        -1.811111111,
+        -2.433333333,
+        -1.188888889,
+        -2.333333333,
+        0.744444444,
+        1.877777778,
+        1.333333333,
+        -1.7,
+        0.888888889,
+        -3.855555556,
+        -8.211111111,
+        -1.055555556,
+        -4.211111111,
+        -7.355555556,
+        -8.111111111,
+        -10.96666667,
+        -13.05555556,
+        -4.644444444,
+        -7.577777778,
+    ]
+    max = [
+        -7.233333333,
+        -1.6,
+        5.488888889,
+        7.744444444,
+        6.188888889,
+        6.555555556,
+        10.53333333,
+        6.766666667,
+        14.1,
+        14.11111111,
+        2.044444444,
+        4.633333333,
+        2.055555556,
+        8.666666667,
+        -1.4,
+        -5.555555556,
+        4.177777778,
+        11.8,
+        15.58888889,
+        12.31111111,
+        3.666666667,
+        -0.977777778,
+        1.288888889,
+        4.211111111,
+        9.377777778,
+        5.266666667,
+        2.144444444,
+        3.977777778,
+        7.2,
+        11.94444444,
+        11.32222222,
+        4,
+        6.611111111,
+        8.211111111,
+        3.5,
+        8.866666667,
+        3.6,
+        3.711111111,
+        13.12222222,
+        7.833333333,
+        -3.333333333,
+        -2.166666667,
+        -2.877777778,
+        5.188888889,
+        13.12222222,
+        12.11111111,
+        -0.7,
+        6.688888889,
+        14.03333333,
+        -2.433333333,
+        -8.6,
+        -8.244444444,
+        -2.122222222,
+        -2.722222222,
+        1.266666667,
+        2.8,
+        5.7,
+        6.944444444,
+        5.066666667,
+        5.688888889,
+        13.35555556,
+        16.66666667,
+        17.33333333,
+        7.277777778,
+        6.388888889,
+        1.344444444,
+        9.111111111,
+        17.96666667,
+        12.8,
+        5.8,
+        6.911111111,
+        6.822222222,
+        11.87777778,
+        13.16666667,
+        9.233333333,
+        8.655555556,
+        10.04444444,
+        7.022222222,
+        7.644444444,
+        8.311111111,
+        16.71111111,
+        18.85555556,
+        12.14444444,
+        13.27777778,
+        11.18888889,
+        7.088888889,
+        8.255555556,
+        7.522222222,
+        9.955555556,
+        9.933333333,
+        4.866666667,
+        15.25555556,
+        9.244444444,
+        9.755555556,
+        14,
+        8.955555556,
+        2.344444444,
+        17.43333333,
+        12.12222222,
+        13.46666667,
+        23,
+        18.45555556,
+        12.77777778,
+        7.211111111,
+        8.588888889,
+        14.35555556,
+        19.01111111,
+        12.4,
+        9.155555556,
+        15.6,
+        4.955555556,
+        8.966666667,
+        16.95555556,
+        9.511111111,
+        10.15555556,
+        16,
+        14.45555556,
+        21.02222222,
+        25.76666667,
+        20.5,
+        15.71111111,
+        11.67777778,
+        12.81111111,
+        12.88888889,
+        17.58888889,
+        23.12222222,
+        21.77777778,
+        24.42222222,
+        20.05555556,
+        24.32222222,
+        18.83333333,
+        19.56666667,
+        14.96666667,
+        19.68888889,
+        18.57777778,
+        23,
+        23.34444444,
+        20.7,
+        11.82222222,
+        11.48888889,
+        17.52222222,
+        22.55555556,
+        20.47777778,
+        23.01111111,
+        27.86666667,
+        30.28888889,
+        30.3,
+        22.94444444,
+        18.57777778,
+        25.51111111,
+        24.13333333,
+        30.01111111,
+        24.77777778,
+        20.28888889,
+        28.67777778,
+        32.74444444,
+        31.37777778,
+        28.52222222,
+        31.81111111,
+        27.24444444,
+        32.53333333,
+        26.15555556,
+        24.63333333,
+        28.3,
+        31.23333333,
+        32.21111111,
+        28.21111111,
+        23.07777778,
+        21.64444444,
+        24.34444444,
+        19.62222222,
+        25.14444444,
+        24.46666667,
+        23.87777778,
+        21.28888889,
+        20.22222222,
+        29.98888889,
+        32.04444444,
+        36.44444444,
+        36.01111111,
+        24.85555556,
+        23.45555556,
+        29.17777778,
+        32.25555556,
+        28.75555556,
+        30.28888889,
+        28.85555556,
+        30.45555556,
+        31.26666667,
+        28.86666667,
+        33.31111111,
+        30.66666667,
+        28.67777778,
+        27.4,
+        32.2,
+        25.41111111,
+        22.23333333,
+        26.67777778,
+        30.21111111,
+        29.15555556,
+        29.65555556,
+        31.94444444,
+        31.43333333,
+        28.35555556,
+        24.8,
+        25.5,
+        25.42222222,
+        24.17777778,
+        20.88888889,
+        24.35555556,
+        25.54444444,
+        22,
+        27.95555556,
+        29.42222222,
+        28.88888889,
+        26.8,
+        28.2,
+        26.92222222,
+        24.13333333,
+        22.61111111,
+        26.15555556,
+        30.57777778,
+        30.86666667,
+        29.92222222,
+        27.33333333,
+        23.43333333,
+        24.68888889,
+        26.94444444,
+        28.81111111,
+        25.54444444,
+        22.48888889,
+        21.67777778,
+        19.74444444,
+        23.82222222,
+        25.91111111,
+        30.85555556,
+        28.48888889,
+        29.21111111,
+        28.37777778,
+        22.4,
+        25.55555556,
+        27.35555556,
+        30.67777778,
+        27.95555556,
+        25.98888889,
+        23.46666667,
+        25.37777778,
+        20.46666667,
+        22.54444444,
+        20.18888889,
+        22.24444444,
+        26.84444444,
+        25.8,
+        29.62222222,
+        26.36666667,
+        32.24444444,
+        29.84444444,
+        28.33333333,
+        31.22222222,
+        29.9,
+        29.98888889,
+        27.42222222,
+        25.54444444,
+        20.22222222,
+        24,
+        24.52222222,
+        25.02222222,
+        16.12222222,
+        17.58888889,
+        23.25555556,
+        15.75555556,
+        18.66666667,
+        18.4,
+        12.52222222,
+        20.07777778,
+        28.62222222,
+        17.23333333,
+        16.6,
+        13.34444444,
+        10.98888889,
+        9.522222222,
+        5.8,
+        6.811111111,
+        6.555555556,
+        12.18888889,
+        12.64444444,
+        4.2,
+        3.577777778,
+        8.888888889,
+        15.23333333,
+        16.11111111,
+        18.36666667,
+        16.98888889,
+        15.63333333,
+        16.46666667,
+        15.55555556,
+        15.65555556,
+        17.42222222,
+        18.74444444,
+        19.48888889,
+        15.9,
+        19.73333333,
+        13.02222222,
+        8.1,
+        8.933333333,
+        11.3,
+        12.38888889,
+        8.3,
+        12.38888889,
+        6.388888889,
+        4.211111111,
+        4.666666667,
+        0.7,
+        7.133333333,
+        2.344444444,
+        1.088888889,
+        0.111111111,
+        11.62222222,
+        10.84444444,
+        8.777777778,
+        3.5,
+        3.4,
+        7.211111111,
+        5.711111111,
+        9.677777778,
+        12.25555556,
+        10.15555556,
+        6.511111111,
+        4.911111111,
+        1.5,
+        11.44444444,
+        15.54444444,
+        8.122222222,
+        6.233333333,
+        7,
+        4.355555556,
+        0.277777778,
+        3.711111111,
+        2.888888889,
+        1.555555556,
+        3.888888889,
+        4.555555556,
+        5.666666667,
+        7.833333333,
+        9.833333333,
+        10.02222222,
+        6.288888889,
+        5.366666667,
+        11.41111111,
+        9.566666667,
+        9.744444444,
+        13.57777778,
+        9.433333333,
+        3.1,
+        11.08888889,
+        3.844444444,
+        2.488888889,
+        7.544444444,
+        4.488888889,
+        -0.455555556,
+        -2.111111111,
+        -3.566666667,
+        -1.955555556,
+        3.955555556,
+        1.222222222,
+    ]
 
-start = 50
-size = 100
-data = {"Date": dates[start:size], "Temp°C": temp[start:size], "Min": min[start:size], "Max": max[start:size]}
+    start = 50
+    size = 100
+    data = {"Date": dates[start:size], "Temp°C": temp[start:size], "Min": min[start:size], "Max": max[start:size]}
 
-page = """
+    page = """
 # Line - Style
 
 <|{data}|chart|mode=lines|x=Date|y[1]=Temp°C|y[2]=Min|y[3]=Max|line[1]=dash|color[2]=blue|color[3]=red|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/line-texts.py

@@ -18,1123 +18,1124 @@ import pandas
 
 from taipy.gui import Gui
 
-dates = pandas.date_range("2023-01-01", periods=365, freq="D")
-temp = [
-    -11.33333333,
-    -6,
-    -0.111111111,
-    1.444444444,
-    2.388888889,
-    4.555555556,
-    4.333333333,
-    0.666666667,
-    9,
-    9.611111111,
-    -0.555555556,
-    1.833333333,
-    -0.444444444,
-    2.166666667,
-    -4,
-    -12.05555556,
-    -2.722222222,
-    5,
-    9.888888889,
-    6.611111111,
-    -2.833333333,
-    -3.277777778,
-    -1.611111111,
-    -1.388888889,
-    5.777777778,
-    2.166666667,
-    -1.055555556,
-    1.777777778,
-    1.5,
-    8.444444444,
-    6.222222222,
-    -2.5,
-    -0.388888889,
-    6.111111111,
-    -1.5,
-    2.666666667,
-    -2.5,
-    0.611111111,
-    8.222222222,
-    2.333333333,
-    -9.333333333,
-    -7.666666667,
-    -6.277777778,
-    -0.611111111,
-    7.722222222,
-    6.111111111,
-    -4,
-    3.388888889,
-    9.333333333,
-    -6.333333333,
-    -15,
-    -12.94444444,
-    -8.722222222,
-    -6.222222222,
-    -2.833333333,
-    -2.5,
-    1.5,
-    3.444444444,
-    2.666666667,
-    0.888888889,
-    7.555555556,
-    12.66666667,
-    12.83333333,
-    1.777777778,
-    -0.111111111,
-    -1.055555556,
-    4.611111111,
-    11.16666667,
-    8.5,
-    0.5,
-    2.111111111,
-    4.722222222,
-    8.277777778,
-    10.66666667,
-    5.833333333,
-    5.555555556,
-    6.944444444,
-    1.722222222,
-    2.444444444,
-    6.111111111,
-    12.11111111,
-    15.55555556,
-    9.944444444,
-    10.27777778,
-    5.888888889,
-    1.388888889,
-    3.555555556,
-    1.222222222,
-    4.055555556,
-    7.833333333,
-    0.666666667,
-    10.05555556,
-    6.444444444,
-    4.555555556,
-    11,
-    3.555555556,
-    -0.555555556,
-    11.83333333,
-    7.222222222,
-    10.16666667,
-    17.5,
-    14.55555556,
-    6.777777778,
-    3.611111111,
-    5.888888889,
-    10.05555556,
-    16.61111111,
-    5.5,
-    7.055555556,
-    10.5,
-    1.555555556,
-    6.166666667,
-    11.05555556,
-    5.111111111,
-    6.055555556,
-    11,
-    11.05555556,
-    14.72222222,
-    19.16666667,
-    16.5,
-    12.61111111,
-    8.277777778,
-    6.611111111,
-    10.38888889,
-    15.38888889,
-    17.22222222,
-    18.27777778,
-    18.72222222,
-    17.05555556,
-    19.72222222,
-    16.83333333,
-    12.66666667,
-    11.66666667,
-    12.88888889,
-    14.77777778,
-    18,
-    19.44444444,
-    16.5,
-    9.722222222,
-    7.888888889,
-    13.72222222,
-    17.55555556,
-    18.27777778,
-    20.11111111,
-    21.66666667,
-    23.38888889,
-    23.5,
-    16.94444444,
-    16.27777778,
-    18.61111111,
-    20.83333333,
-    24.61111111,
-    18.27777778,
-    17.88888889,
-    22.27777778,
-    25.94444444,
-    25.27777778,
-    24.72222222,
-    25.61111111,
-    23.94444444,
-    26.33333333,
-    22.05555556,
-    20.83333333,
-    24.5,
-    27.83333333,
-    25.61111111,
-    23.11111111,
-    19.27777778,
-    16.44444444,
-    19.44444444,
-    17.22222222,
-    19.44444444,
-    22.16666667,
-    21.77777778,
-    17.38888889,
-    17.22222222,
-    23.88888889,
-    28.44444444,
-    29.44444444,
-    29.61111111,
-    21.05555556,
-    18.55555556,
-    25.27777778,
-    26.55555556,
-    24.55555556,
-    23.38888889,
-    22.55555556,
-    27.05555556,
-    27.66666667,
-    26.66666667,
-    27.61111111,
-    26.66666667,
-    24.77777778,
-    23,
-    26.5,
-    23.11111111,
-    19.83333333,
-    22.27777778,
-    24.61111111,
-    27.05555556,
-    27.05555556,
-    27.94444444,
-    27.33333333,
-    22.05555556,
-    21.5,
-    22,
-    19.72222222,
-    20.27777778,
-    17.88888889,
-    18.55555556,
-    18.94444444,
-    20,
-    22.05555556,
-    23.22222222,
-    24.38888889,
-    24.5,
-    24.5,
-    21.22222222,
-    20.83333333,
-    20.61111111,
-    22.05555556,
-    23.77777778,
-    24.16666667,
-    24.22222222,
-    21.83333333,
-    21.33333333,
-    21.88888889,
-    22.44444444,
-    23.11111111,
-    20.44444444,
-    16.88888889,
-    15.77777778,
-    17.44444444,
-    17.72222222,
-    23.11111111,
-    24.55555556,
-    24.88888889,
-    25.11111111,
-    25.27777778,
-    19.5,
-    19.55555556,
-    24.05555556,
-    24.27777778,
-    21.05555556,
-    19.88888889,
-    20.66666667,
-    20.27777778,
-    17.66666667,
-    16.44444444,
-    15.88888889,
-    18.44444444,
-    22.44444444,
-    23,
-    24.72222222,
-    24.16666667,
-    25.94444444,
-    24.44444444,
-    23.33333333,
-    25.22222222,
-    25,
-    23.88888889,
-    23.72222222,
-    18.94444444,
-    16.22222222,
-    19.5,
-    21.22222222,
-    19.72222222,
-    13.22222222,
-    11.88888889,
-    16.55555556,
-    10.05555556,
-    12.16666667,
-    11.5,
-    10.22222222,
-    17.27777778,
-    21.72222222,
-    13.83333333,
-    13,
-    6.944444444,
-    6.388888889,
-    4.222222222,
-    2.5,
-    1.111111111,
-    3.055555556,
-    6.388888889,
-    10.44444444,
-    -2,
-    -2.222222222,
-    4.388888889,
-    8.333333333,
-    11.11111111,
-    12.66666667,
-    10.88888889,
-    12.83333333,
-    14.16666667,
-    12.55555556,
-    12.05555556,
-    11.22222222,
-    12.44444444,
-    14.38888889,
-    12,
-    15.83333333,
-    6.722222222,
-    2.5,
-    4.833333333,
-    7.5,
-    8.888888889,
-    4,
-    7.388888889,
-    3.888888889,
-    1.611111111,
-    -0.333333333,
-    -2,
-    4.833333333,
-    -1.055555556,
-    -5.611111111,
-    -2.388888889,
-    5.722222222,
-    8.444444444,
-    5.277777778,
-    0.5,
-    -2.5,
-    1.111111111,
-    2.111111111,
-    5.777777778,
-    7.555555556,
-    7.555555556,
-    4.111111111,
-    -0.388888889,
-    -1,
-    4.944444444,
-    9.444444444,
-    4.722222222,
-    -0.166666667,
-    0.5,
-    -2.444444444,
-    -2.722222222,
-    -2.888888889,
-    -1.111111111,
-    -4.944444444,
-    -3.111111111,
-    -1.444444444,
-    -0.833333333,
-    2.333333333,
-    6.833333333,
-    4.722222222,
-    0.888888889,
-    0.666666667,
-    4.611111111,
-    4.666666667,
-    4.444444444,
-    6.777777778,
-    5.833333333,
-    0.5,
-    4.888888889,
-    1.444444444,
-    -2.111111111,
-    2.444444444,
-    -0.111111111,
-    -2.555555556,
-    -4.611111111,
-    -8.666666667,
-    -8.055555556,
-    1.555555556,
-    -4.777777778,
-]
-min = [
-    -14.33333333,
-    -12.9,
-    -3.311111111,
-    -4.955555556,
-    -3.611111111,
-    0.555555556,
-    1.133333333,
-    -5.133333333,
-    2.3,
-    3.911111111,
-    -7.055555556,
-    -1.366666667,
-    -4.844444444,
-    -3.333333333,
-    -6.1,
-    -17.15555556,
-    -4.822222222,
-    0.4,
-    3.488888889,
-    4.211111111,
-    -6.433333333,
-    -7.577777778,
-    -7.111111111,
-    -7.088888889,
-    1.577777778,
-    -3.433333333,
-    -4.355555556,
-    -0.722222222,
-    -2.1,
-    2.044444444,
-    2.222222222,
-    -4.7,
-    -2.388888889,
-    4.111111111,
-    -5,
-    -0.133333333,
-    -5.3,
-    -2.288888889,
-    6.022222222,
-    -1.766666667,
-    -15.53333333,
-    -13.46666667,
-    -9.277777778,
-    -3.211111111,
-    3.122222222,
-    1.411111111,
-    -6.8,
-    1.388888889,
-    5.333333333,
-    -9.833333333,
-    -22,
-    -19.74444444,
-    -14.62222222,
-    -9.622222222,
-    -8.433333333,
-    -8.5,
-    -2.8,
-    0.144444444,
-    -3.233333333,
-    -3.411111111,
-    5.355555556,
-    8.366666667,
-    7.333333333,
-    -0.322222222,
-    -6.911111111,
-    -4.955555556,
-    -1.588888889,
-    4.966666667,
-    2.5,
-    -4.3,
-    -1.888888889,
-    -1.777777778,
-    2.477777778,
-    3.766666667,
-    0.533333333,
-    1.755555556,
-    2.944444444,
-    -4.977777778,
-    -4.055555556,
-    1.711111111,
-    6.011111111,
-    13.15555556,
-    5.044444444,
-    6.577777778,
-    3.388888889,
-    -1.011111111,
-    -0.244444444,
-    -2.477777778,
-    -1.444444444,
-    2.533333333,
-    -6.333333333,
-    4.255555556,
-    1.944444444,
-    0.855555556,
-    5.4,
-    -1.244444444,
-    -2.855555556,
-    4.833333333,
-    2.722222222,
-    6.466666667,
-    14.5,
-    9.855555556,
-    2.277777778,
-    -3.188888889,
-    0.788888889,
-    4.155555556,
-    13.41111111,
-    2.3,
-    0.855555556,
-    8.4,
-    -0.444444444,
-    1.166666667,
-    7.755555556,
-    -0.288888889,
-    -0.244444444,
-    8.7,
-    5.555555556,
-    8.222222222,
-    16.26666667,
-    14.4,
-    5.711111111,
-    5.177777778,
-    4.511111111,
-    5.988888889,
-    10.08888889,
-    10.52222222,
-    15.37777778,
-    12.42222222,
-    14.95555556,
-    15.22222222,
-    11.93333333,
-    6.866666667,
-    6.866666667,
-    9.688888889,
-    11.57777778,
-    12,
-    13.34444444,
-    11.3,
-    6.222222222,
-    2.088888889,
-    8.322222222,
-    14.05555556,
-    13.77777778,
-    16.91111111,
-    16.86666667,
-    16.68888889,
-    18.5,
-    12.54444444,
-    12.27777778,
-    15.91111111,
-    15.03333333,
-    22.11111111,
-    15.77777778,
-    13.68888889,
-    17.87777778,
-    19.94444444,
-    18.57777778,
-    18.62222222,
-    20.11111111,
-    17.14444444,
-    20.43333333,
-    15.75555556,
-    17.33333333,
-    20,
-    23.03333333,
-    19.61111111,
-    18.51111111,
-    15.27777778,
-    11.44444444,
-    13.64444444,
-    11.42222222,
-    16.14444444,
-    19.76666667,
-    18.77777778,
-    11.88888889,
-    12.32222222,
-    20.78888889,
-    25.04444444,
-    25.34444444,
-    23.81111111,
-    18.35555556,
-    11.85555556,
-    18.37777778,
-    23.15555556,
-    21.55555556,
-    17.48888889,
-    19.05555556,
-    20.25555556,
-    23.86666667,
-    23.86666667,
-    21.41111111,
-    21.16666667,
-    18.67777778,
-    18.1,
-    24.4,
-    19.01111111,
-    17.13333333,
-    18.27777778,
-    21.71111111,
-    22.85555556,
-    22.65555556,
-    25.14444444,
-    24.13333333,
-    17.95555556,
-    14.7,
-    15.1,
-    16.02222222,
-    14.27777778,
-    11.18888889,
-    13.65555556,
-    16.74444444,
-    16.7,
-    17.65555556,
-    16.62222222,
-    21.68888889,
-    19.6,
-    18.6,
-    15.52222222,
-    18.53333333,
-    17.01111111,
-    17.75555556,
-    20.47777778,
-    17.76666667,
-    22.22222222,
-    18.23333333,
-    17.83333333,
-    15.38888889,
-    19.64444444,
-    17.81111111,
-    15.44444444,
-    14.88888889,
-    13.07777778,
-    15.24444444,
-    11.82222222,
-    20.81111111,
-    21.45555556,
-    18.98888889,
-    19.71111111,
-    19.27777778,
-    12.7,
-    15.05555556,
-    19.15555556,
-    20.77777778,
-    15.35555556,
-    17.68888889,
-    18.26666667,
-    15.47777778,
-    12.76666667,
-    10.54444444,
-    13.38888889,
-    12.54444444,
-    19.84444444,
-    19.5,
-    21.92222222,
-    17.86666667,
-    22.44444444,
-    19.64444444,
-    20.73333333,
-    22.02222222,
-    19,
-    20.48888889,
-    19.02222222,
-    16.44444444,
-    14.22222222,
-    16.3,
-    16.42222222,
-    17.22222222,
-    8.322222222,
-    8.288888889,
-    13.95555556,
-    5.555555556,
-    5.666666667,
-    7.7,
-    4.022222222,
-    11.77777778,
-    16.42222222,
-    11.83333333,
-    9.7,
-    0.044444444,
-    3.688888889,
-    -2.077777778,
-    0.1,
-    -5.388888889,
-    -3.244444444,
-    0.688888889,
-    5.744444444,
-    -7.7,
-    -7.022222222,
-    -0.211111111,
-    4.833333333,
-    8.111111111,
-    5.766666667,
-    7.888888889,
-    10.43333333,
-    11.56666667,
-    10.15555556,
-    7.155555556,
-    4.522222222,
-    7.144444444,
-    10.88888889,
-    9.5,
-    12.13333333,
-    4.022222222,
-    -3.9,
-    1.433333333,
-    0.7,
-    3.188888889,
-    -1.7,
-    3.588888889,
-    -0.111111111,
-    -2.788888889,
-    -7.133333333,
-    -5,
-    0.733333333,
-    -7.555555556,
-    -12.51111111,
-    -8.188888889,
-    3.122222222,
-    2.944444444,
-    0.477777778,
-    -3.2,
-    -9.2,
-    -4.788888889,
-    -0.288888889,
-    1.077777778,
-    4.755555556,
-    5.455555556,
-    0.511111111,
-    -3.888888889,
-    -7.4,
-    -1.355555556,
-    5.144444444,
-    0.122222222,
-    -5.166666667,
-    -5,
-    -5.144444444,
-    -8.822222222,
-    -6.388888889,
-    -6.811111111,
-    -8.944444444,
-    -10.11111111,
-    -7.144444444,
-    -5.133333333,
-    -1.166666667,
-    1.833333333,
-    -1.477777778,
-    -1.811111111,
-    -2.433333333,
-    -1.188888889,
-    -2.333333333,
-    0.744444444,
-    1.877777778,
-    1.333333333,
-    -1.7,
-    0.888888889,
-    -3.855555556,
-    -8.211111111,
-    -1.055555556,
-    -4.211111111,
-    -7.355555556,
-    -8.111111111,
-    -10.96666667,
-    -13.05555556,
-    -4.644444444,
-    -7.577777778,
-]
-max = [
-    -7.233333333,
-    -1.6,
-    5.488888889,
-    7.744444444,
-    6.188888889,
-    6.555555556,
-    10.53333333,
-    6.766666667,
-    14.1,
-    14.11111111,
-    2.044444444,
-    4.633333333,
-    2.055555556,
-    8.666666667,
-    -1.4,
-    -5.555555556,
-    4.177777778,
-    11.8,
-    15.58888889,
-    12.31111111,
-    3.666666667,
-    -0.977777778,
-    1.288888889,
-    4.211111111,
-    9.377777778,
-    5.266666667,
-    2.144444444,
-    3.977777778,
-    7.2,
-    11.94444444,
-    11.32222222,
-    4,
-    6.611111111,
-    8.211111111,
-    3.5,
-    8.866666667,
-    3.6,
-    3.711111111,
-    13.12222222,
-    7.833333333,
-    -3.333333333,
-    -2.166666667,
-    -2.877777778,
-    5.188888889,
-    13.12222222,
-    12.11111111,
-    -0.7,
-    6.688888889,
-    14.03333333,
-    -2.433333333,
-    -8.6,
-    -8.244444444,
-    -2.122222222,
-    -2.722222222,
-    1.266666667,
-    2.8,
-    5.7,
-    6.944444444,
-    5.066666667,
-    5.688888889,
-    13.35555556,
-    16.66666667,
-    17.33333333,
-    7.277777778,
-    6.388888889,
-    1.344444444,
-    9.111111111,
-    17.96666667,
-    12.8,
-    5.8,
-    6.911111111,
-    6.822222222,
-    11.87777778,
-    13.16666667,
-    9.233333333,
-    8.655555556,
-    10.04444444,
-    7.022222222,
-    7.644444444,
-    8.311111111,
-    16.71111111,
-    18.85555556,
-    12.14444444,
-    13.27777778,
-    11.18888889,
-    7.088888889,
-    8.255555556,
-    7.522222222,
-    9.955555556,
-    9.933333333,
-    4.866666667,
-    15.25555556,
-    9.244444444,
-    9.755555556,
-    14,
-    8.955555556,
-    2.344444444,
-    17.43333333,
-    12.12222222,
-    13.46666667,
-    23,
-    18.45555556,
-    12.77777778,
-    7.211111111,
-    8.588888889,
-    14.35555556,
-    19.01111111,
-    12.4,
-    9.155555556,
-    15.6,
-    4.955555556,
-    8.966666667,
-    16.95555556,
-    9.511111111,
-    10.15555556,
-    16,
-    14.45555556,
-    21.02222222,
-    25.76666667,
-    20.5,
-    15.71111111,
-    11.67777778,
-    12.81111111,
-    12.88888889,
-    17.58888889,
-    23.12222222,
-    21.77777778,
-    24.42222222,
-    20.05555556,
-    24.32222222,
-    18.83333333,
-    19.56666667,
-    14.96666667,
-    19.68888889,
-    18.57777778,
-    23,
-    23.34444444,
-    20.7,
-    11.82222222,
-    11.48888889,
-    17.52222222,
-    22.55555556,
-    20.47777778,
-    23.01111111,
-    27.86666667,
-    30.28888889,
-    30.3,
-    22.94444444,
-    18.57777778,
-    25.51111111,
-    24.13333333,
-    30.01111111,
-    24.77777778,
-    20.28888889,
-    28.67777778,
-    32.74444444,
-    31.37777778,
-    28.52222222,
-    31.81111111,
-    27.24444444,
-    32.53333333,
-    26.15555556,
-    24.63333333,
-    28.3,
-    31.23333333,
-    32.21111111,
-    28.21111111,
-    23.07777778,
-    21.64444444,
-    24.34444444,
-    19.62222222,
-    25.14444444,
-    24.46666667,
-    23.87777778,
-    21.28888889,
-    20.22222222,
-    29.98888889,
-    32.04444444,
-    36.44444444,
-    36.01111111,
-    24.85555556,
-    23.45555556,
-    29.17777778,
-    32.25555556,
-    28.75555556,
-    30.28888889,
-    28.85555556,
-    30.45555556,
-    31.26666667,
-    28.86666667,
-    33.31111111,
-    30.66666667,
-    28.67777778,
-    27.4,
-    32.2,
-    25.41111111,
-    22.23333333,
-    26.67777778,
-    30.21111111,
-    29.15555556,
-    29.65555556,
-    31.94444444,
-    31.43333333,
-    28.35555556,
-    24.8,
-    25.5,
-    25.42222222,
-    24.17777778,
-    20.88888889,
-    24.35555556,
-    25.54444444,
-    22,
-    27.95555556,
-    29.42222222,
-    28.88888889,
-    26.8,
-    28.2,
-    26.92222222,
-    24.13333333,
-    22.61111111,
-    26.15555556,
-    30.57777778,
-    30.86666667,
-    29.92222222,
-    27.33333333,
-    23.43333333,
-    24.68888889,
-    26.94444444,
-    28.81111111,
-    25.54444444,
-    22.48888889,
-    21.67777778,
-    19.74444444,
-    23.82222222,
-    25.91111111,
-    30.85555556,
-    28.48888889,
-    29.21111111,
-    28.37777778,
-    22.4,
-    25.55555556,
-    27.35555556,
-    30.67777778,
-    27.95555556,
-    25.98888889,
-    23.46666667,
-    25.37777778,
-    20.46666667,
-    22.54444444,
-    20.18888889,
-    22.24444444,
-    26.84444444,
-    25.8,
-    29.62222222,
-    26.36666667,
-    32.24444444,
-    29.84444444,
-    28.33333333,
-    31.22222222,
-    29.9,
-    29.98888889,
-    27.42222222,
-    25.54444444,
-    20.22222222,
-    24,
-    24.52222222,
-    25.02222222,
-    16.12222222,
-    17.58888889,
-    23.25555556,
-    15.75555556,
-    18.66666667,
-    18.4,
-    12.52222222,
-    20.07777778,
-    28.62222222,
-    17.23333333,
-    16.6,
-    13.34444444,
-    10.98888889,
-    9.522222222,
-    5.8,
-    6.811111111,
-    6.555555556,
-    12.18888889,
-    12.64444444,
-    4.2,
-    3.577777778,
-    8.888888889,
-    15.23333333,
-    16.11111111,
-    18.36666667,
-    16.98888889,
-    15.63333333,
-    16.46666667,
-    15.55555556,
-    15.65555556,
-    17.42222222,
-    18.74444444,
-    19.48888889,
-    15.9,
-    19.73333333,
-    13.02222222,
-    8.1,
-    8.933333333,
-    11.3,
-    12.38888889,
-    8.3,
-    12.38888889,
-    6.388888889,
-    4.211111111,
-    4.666666667,
-    0.7,
-    7.133333333,
-    2.344444444,
-    1.088888889,
-    0.111111111,
-    11.62222222,
-    10.84444444,
-    8.777777778,
-    3.5,
-    3.4,
-    7.211111111,
-    5.711111111,
-    9.677777778,
-    12.25555556,
-    10.15555556,
-    6.511111111,
-    4.911111111,
-    1.5,
-    11.44444444,
-    15.54444444,
-    8.122222222,
-    6.233333333,
-    7,
-    4.355555556,
-    0.277777778,
-    3.711111111,
-    2.888888889,
-    1.555555556,
-    3.888888889,
-    4.555555556,
-    5.666666667,
-    7.833333333,
-    9.833333333,
-    10.02222222,
-    6.288888889,
-    5.366666667,
-    11.41111111,
-    9.566666667,
-    9.744444444,
-    13.57777778,
-    9.433333333,
-    3.1,
-    11.08888889,
-    3.844444444,
-    2.488888889,
-    7.544444444,
-    4.488888889,
-    -0.455555556,
-    -2.111111111,
-    -3.566666667,
-    -1.955555556,
-    3.955555556,
-    1.222222222,
-]
-week_number = [f"W{i//7}" if i % 7 == 0 else None for i in range(0, 365)]
+if __name__ == "__main__":
+    dates = pandas.date_range("2023-01-01", periods=365, freq="D")
+    temp = [
+        -11.33333333,
+        -6,
+        -0.111111111,
+        1.444444444,
+        2.388888889,
+        4.555555556,
+        4.333333333,
+        0.666666667,
+        9,
+        9.611111111,
+        -0.555555556,
+        1.833333333,
+        -0.444444444,
+        2.166666667,
+        -4,
+        -12.05555556,
+        -2.722222222,
+        5,
+        9.888888889,
+        6.611111111,
+        -2.833333333,
+        -3.277777778,
+        -1.611111111,
+        -1.388888889,
+        5.777777778,
+        2.166666667,
+        -1.055555556,
+        1.777777778,
+        1.5,
+        8.444444444,
+        6.222222222,
+        -2.5,
+        -0.388888889,
+        6.111111111,
+        -1.5,
+        2.666666667,
+        -2.5,
+        0.611111111,
+        8.222222222,
+        2.333333333,
+        -9.333333333,
+        -7.666666667,
+        -6.277777778,
+        -0.611111111,
+        7.722222222,
+        6.111111111,
+        -4,
+        3.388888889,
+        9.333333333,
+        -6.333333333,
+        -15,
+        -12.94444444,
+        -8.722222222,
+        -6.222222222,
+        -2.833333333,
+        -2.5,
+        1.5,
+        3.444444444,
+        2.666666667,
+        0.888888889,
+        7.555555556,
+        12.66666667,
+        12.83333333,
+        1.777777778,
+        -0.111111111,
+        -1.055555556,
+        4.611111111,
+        11.16666667,
+        8.5,
+        0.5,
+        2.111111111,
+        4.722222222,
+        8.277777778,
+        10.66666667,
+        5.833333333,
+        5.555555556,
+        6.944444444,
+        1.722222222,
+        2.444444444,
+        6.111111111,
+        12.11111111,
+        15.55555556,
+        9.944444444,
+        10.27777778,
+        5.888888889,
+        1.388888889,
+        3.555555556,
+        1.222222222,
+        4.055555556,
+        7.833333333,
+        0.666666667,
+        10.05555556,
+        6.444444444,
+        4.555555556,
+        11,
+        3.555555556,
+        -0.555555556,
+        11.83333333,
+        7.222222222,
+        10.16666667,
+        17.5,
+        14.55555556,
+        6.777777778,
+        3.611111111,
+        5.888888889,
+        10.05555556,
+        16.61111111,
+        5.5,
+        7.055555556,
+        10.5,
+        1.555555556,
+        6.166666667,
+        11.05555556,
+        5.111111111,
+        6.055555556,
+        11,
+        11.05555556,
+        14.72222222,
+        19.16666667,
+        16.5,
+        12.61111111,
+        8.277777778,
+        6.611111111,
+        10.38888889,
+        15.38888889,
+        17.22222222,
+        18.27777778,
+        18.72222222,
+        17.05555556,
+        19.72222222,
+        16.83333333,
+        12.66666667,
+        11.66666667,
+        12.88888889,
+        14.77777778,
+        18,
+        19.44444444,
+        16.5,
+        9.722222222,
+        7.888888889,
+        13.72222222,
+        17.55555556,
+        18.27777778,
+        20.11111111,
+        21.66666667,
+        23.38888889,
+        23.5,
+        16.94444444,
+        16.27777778,
+        18.61111111,
+        20.83333333,
+        24.61111111,
+        18.27777778,
+        17.88888889,
+        22.27777778,
+        25.94444444,
+        25.27777778,
+        24.72222222,
+        25.61111111,
+        23.94444444,
+        26.33333333,
+        22.05555556,
+        20.83333333,
+        24.5,
+        27.83333333,
+        25.61111111,
+        23.11111111,
+        19.27777778,
+        16.44444444,
+        19.44444444,
+        17.22222222,
+        19.44444444,
+        22.16666667,
+        21.77777778,
+        17.38888889,
+        17.22222222,
+        23.88888889,
+        28.44444444,
+        29.44444444,
+        29.61111111,
+        21.05555556,
+        18.55555556,
+        25.27777778,
+        26.55555556,
+        24.55555556,
+        23.38888889,
+        22.55555556,
+        27.05555556,
+        27.66666667,
+        26.66666667,
+        27.61111111,
+        26.66666667,
+        24.77777778,
+        23,
+        26.5,
+        23.11111111,
+        19.83333333,
+        22.27777778,
+        24.61111111,
+        27.05555556,
+        27.05555556,
+        27.94444444,
+        27.33333333,
+        22.05555556,
+        21.5,
+        22,
+        19.72222222,
+        20.27777778,
+        17.88888889,
+        18.55555556,
+        18.94444444,
+        20,
+        22.05555556,
+        23.22222222,
+        24.38888889,
+        24.5,
+        24.5,
+        21.22222222,
+        20.83333333,
+        20.61111111,
+        22.05555556,
+        23.77777778,
+        24.16666667,
+        24.22222222,
+        21.83333333,
+        21.33333333,
+        21.88888889,
+        22.44444444,
+        23.11111111,
+        20.44444444,
+        16.88888889,
+        15.77777778,
+        17.44444444,
+        17.72222222,
+        23.11111111,
+        24.55555556,
+        24.88888889,
+        25.11111111,
+        25.27777778,
+        19.5,
+        19.55555556,
+        24.05555556,
+        24.27777778,
+        21.05555556,
+        19.88888889,
+        20.66666667,
+        20.27777778,
+        17.66666667,
+        16.44444444,
+        15.88888889,
+        18.44444444,
+        22.44444444,
+        23,
+        24.72222222,
+        24.16666667,
+        25.94444444,
+        24.44444444,
+        23.33333333,
+        25.22222222,
+        25,
+        23.88888889,
+        23.72222222,
+        18.94444444,
+        16.22222222,
+        19.5,
+        21.22222222,
+        19.72222222,
+        13.22222222,
+        11.88888889,
+        16.55555556,
+        10.05555556,
+        12.16666667,
+        11.5,
+        10.22222222,
+        17.27777778,
+        21.72222222,
+        13.83333333,
+        13,
+        6.944444444,
+        6.388888889,
+        4.222222222,
+        2.5,
+        1.111111111,
+        3.055555556,
+        6.388888889,
+        10.44444444,
+        -2,
+        -2.222222222,
+        4.388888889,
+        8.333333333,
+        11.11111111,
+        12.66666667,
+        10.88888889,
+        12.83333333,
+        14.16666667,
+        12.55555556,
+        12.05555556,
+        11.22222222,
+        12.44444444,
+        14.38888889,
+        12,
+        15.83333333,
+        6.722222222,
+        2.5,
+        4.833333333,
+        7.5,
+        8.888888889,
+        4,
+        7.388888889,
+        3.888888889,
+        1.611111111,
+        -0.333333333,
+        -2,
+        4.833333333,
+        -1.055555556,
+        -5.611111111,
+        -2.388888889,
+        5.722222222,
+        8.444444444,
+        5.277777778,
+        0.5,
+        -2.5,
+        1.111111111,
+        2.111111111,
+        5.777777778,
+        7.555555556,
+        7.555555556,
+        4.111111111,
+        -0.388888889,
+        -1,
+        4.944444444,
+        9.444444444,
+        4.722222222,
+        -0.166666667,
+        0.5,
+        -2.444444444,
+        -2.722222222,
+        -2.888888889,
+        -1.111111111,
+        -4.944444444,
+        -3.111111111,
+        -1.444444444,
+        -0.833333333,
+        2.333333333,
+        6.833333333,
+        4.722222222,
+        0.888888889,
+        0.666666667,
+        4.611111111,
+        4.666666667,
+        4.444444444,
+        6.777777778,
+        5.833333333,
+        0.5,
+        4.888888889,
+        1.444444444,
+        -2.111111111,
+        2.444444444,
+        -0.111111111,
+        -2.555555556,
+        -4.611111111,
+        -8.666666667,
+        -8.055555556,
+        1.555555556,
+        -4.777777778,
+    ]
+    min = [
+        -14.33333333,
+        -12.9,
+        -3.311111111,
+        -4.955555556,
+        -3.611111111,
+        0.555555556,
+        1.133333333,
+        -5.133333333,
+        2.3,
+        3.911111111,
+        -7.055555556,
+        -1.366666667,
+        -4.844444444,
+        -3.333333333,
+        -6.1,
+        -17.15555556,
+        -4.822222222,
+        0.4,
+        3.488888889,
+        4.211111111,
+        -6.433333333,
+        -7.577777778,
+        -7.111111111,
+        -7.088888889,
+        1.577777778,
+        -3.433333333,
+        -4.355555556,
+        -0.722222222,
+        -2.1,
+        2.044444444,
+        2.222222222,
+        -4.7,
+        -2.388888889,
+        4.111111111,
+        -5,
+        -0.133333333,
+        -5.3,
+        -2.288888889,
+        6.022222222,
+        -1.766666667,
+        -15.53333333,
+        -13.46666667,
+        -9.277777778,
+        -3.211111111,
+        3.122222222,
+        1.411111111,
+        -6.8,
+        1.388888889,
+        5.333333333,
+        -9.833333333,
+        -22,
+        -19.74444444,
+        -14.62222222,
+        -9.622222222,
+        -8.433333333,
+        -8.5,
+        -2.8,
+        0.144444444,
+        -3.233333333,
+        -3.411111111,
+        5.355555556,
+        8.366666667,
+        7.333333333,
+        -0.322222222,
+        -6.911111111,
+        -4.955555556,
+        -1.588888889,
+        4.966666667,
+        2.5,
+        -4.3,
+        -1.888888889,
+        -1.777777778,
+        2.477777778,
+        3.766666667,
+        0.533333333,
+        1.755555556,
+        2.944444444,
+        -4.977777778,
+        -4.055555556,
+        1.711111111,
+        6.011111111,
+        13.15555556,
+        5.044444444,
+        6.577777778,
+        3.388888889,
+        -1.011111111,
+        -0.244444444,
+        -2.477777778,
+        -1.444444444,
+        2.533333333,
+        -6.333333333,
+        4.255555556,
+        1.944444444,
+        0.855555556,
+        5.4,
+        -1.244444444,
+        -2.855555556,
+        4.833333333,
+        2.722222222,
+        6.466666667,
+        14.5,
+        9.855555556,
+        2.277777778,
+        -3.188888889,
+        0.788888889,
+        4.155555556,
+        13.41111111,
+        2.3,
+        0.855555556,
+        8.4,
+        -0.444444444,
+        1.166666667,
+        7.755555556,
+        -0.288888889,
+        -0.244444444,
+        8.7,
+        5.555555556,
+        8.222222222,
+        16.26666667,
+        14.4,
+        5.711111111,
+        5.177777778,
+        4.511111111,
+        5.988888889,
+        10.08888889,
+        10.52222222,
+        15.37777778,
+        12.42222222,
+        14.95555556,
+        15.22222222,
+        11.93333333,
+        6.866666667,
+        6.866666667,
+        9.688888889,
+        11.57777778,
+        12,
+        13.34444444,
+        11.3,
+        6.222222222,
+        2.088888889,
+        8.322222222,
+        14.05555556,
+        13.77777778,
+        16.91111111,
+        16.86666667,
+        16.68888889,
+        18.5,
+        12.54444444,
+        12.27777778,
+        15.91111111,
+        15.03333333,
+        22.11111111,
+        15.77777778,
+        13.68888889,
+        17.87777778,
+        19.94444444,
+        18.57777778,
+        18.62222222,
+        20.11111111,
+        17.14444444,
+        20.43333333,
+        15.75555556,
+        17.33333333,
+        20,
+        23.03333333,
+        19.61111111,
+        18.51111111,
+        15.27777778,
+        11.44444444,
+        13.64444444,
+        11.42222222,
+        16.14444444,
+        19.76666667,
+        18.77777778,
+        11.88888889,
+        12.32222222,
+        20.78888889,
+        25.04444444,
+        25.34444444,
+        23.81111111,
+        18.35555556,
+        11.85555556,
+        18.37777778,
+        23.15555556,
+        21.55555556,
+        17.48888889,
+        19.05555556,
+        20.25555556,
+        23.86666667,
+        23.86666667,
+        21.41111111,
+        21.16666667,
+        18.67777778,
+        18.1,
+        24.4,
+        19.01111111,
+        17.13333333,
+        18.27777778,
+        21.71111111,
+        22.85555556,
+        22.65555556,
+        25.14444444,
+        24.13333333,
+        17.95555556,
+        14.7,
+        15.1,
+        16.02222222,
+        14.27777778,
+        11.18888889,
+        13.65555556,
+        16.74444444,
+        16.7,
+        17.65555556,
+        16.62222222,
+        21.68888889,
+        19.6,
+        18.6,
+        15.52222222,
+        18.53333333,
+        17.01111111,
+        17.75555556,
+        20.47777778,
+        17.76666667,
+        22.22222222,
+        18.23333333,
+        17.83333333,
+        15.38888889,
+        19.64444444,
+        17.81111111,
+        15.44444444,
+        14.88888889,
+        13.07777778,
+        15.24444444,
+        11.82222222,
+        20.81111111,
+        21.45555556,
+        18.98888889,
+        19.71111111,
+        19.27777778,
+        12.7,
+        15.05555556,
+        19.15555556,
+        20.77777778,
+        15.35555556,
+        17.68888889,
+        18.26666667,
+        15.47777778,
+        12.76666667,
+        10.54444444,
+        13.38888889,
+        12.54444444,
+        19.84444444,
+        19.5,
+        21.92222222,
+        17.86666667,
+        22.44444444,
+        19.64444444,
+        20.73333333,
+        22.02222222,
+        19,
+        20.48888889,
+        19.02222222,
+        16.44444444,
+        14.22222222,
+        16.3,
+        16.42222222,
+        17.22222222,
+        8.322222222,
+        8.288888889,
+        13.95555556,
+        5.555555556,
+        5.666666667,
+        7.7,
+        4.022222222,
+        11.77777778,
+        16.42222222,
+        11.83333333,
+        9.7,
+        0.044444444,
+        3.688888889,
+        -2.077777778,
+        0.1,
+        -5.388888889,
+        -3.244444444,
+        0.688888889,
+        5.744444444,
+        -7.7,
+        -7.022222222,
+        -0.211111111,
+        4.833333333,
+        8.111111111,
+        5.766666667,
+        7.888888889,
+        10.43333333,
+        11.56666667,
+        10.15555556,
+        7.155555556,
+        4.522222222,
+        7.144444444,
+        10.88888889,
+        9.5,
+        12.13333333,
+        4.022222222,
+        -3.9,
+        1.433333333,
+        0.7,
+        3.188888889,
+        -1.7,
+        3.588888889,
+        -0.111111111,
+        -2.788888889,
+        -7.133333333,
+        -5,
+        0.733333333,
+        -7.555555556,
+        -12.51111111,
+        -8.188888889,
+        3.122222222,
+        2.944444444,
+        0.477777778,
+        -3.2,
+        -9.2,
+        -4.788888889,
+        -0.288888889,
+        1.077777778,
+        4.755555556,
+        5.455555556,
+        0.511111111,
+        -3.888888889,
+        -7.4,
+        -1.355555556,
+        5.144444444,
+        0.122222222,
+        -5.166666667,
+        -5,
+        -5.144444444,
+        -8.822222222,
+        -6.388888889,
+        -6.811111111,
+        -8.944444444,
+        -10.11111111,
+        -7.144444444,
+        -5.133333333,
+        -1.166666667,
+        1.833333333,
+        -1.477777778,
+        -1.811111111,
+        -2.433333333,
+        -1.188888889,
+        -2.333333333,
+        0.744444444,
+        1.877777778,
+        1.333333333,
+        -1.7,
+        0.888888889,
+        -3.855555556,
+        -8.211111111,
+        -1.055555556,
+        -4.211111111,
+        -7.355555556,
+        -8.111111111,
+        -10.96666667,
+        -13.05555556,
+        -4.644444444,
+        -7.577777778,
+    ]
+    max = [
+        -7.233333333,
+        -1.6,
+        5.488888889,
+        7.744444444,
+        6.188888889,
+        6.555555556,
+        10.53333333,
+        6.766666667,
+        14.1,
+        14.11111111,
+        2.044444444,
+        4.633333333,
+        2.055555556,
+        8.666666667,
+        -1.4,
+        -5.555555556,
+        4.177777778,
+        11.8,
+        15.58888889,
+        12.31111111,
+        3.666666667,
+        -0.977777778,
+        1.288888889,
+        4.211111111,
+        9.377777778,
+        5.266666667,
+        2.144444444,
+        3.977777778,
+        7.2,
+        11.94444444,
+        11.32222222,
+        4,
+        6.611111111,
+        8.211111111,
+        3.5,
+        8.866666667,
+        3.6,
+        3.711111111,
+        13.12222222,
+        7.833333333,
+        -3.333333333,
+        -2.166666667,
+        -2.877777778,
+        5.188888889,
+        13.12222222,
+        12.11111111,
+        -0.7,
+        6.688888889,
+        14.03333333,
+        -2.433333333,
+        -8.6,
+        -8.244444444,
+        -2.122222222,
+        -2.722222222,
+        1.266666667,
+        2.8,
+        5.7,
+        6.944444444,
+        5.066666667,
+        5.688888889,
+        13.35555556,
+        16.66666667,
+        17.33333333,
+        7.277777778,
+        6.388888889,
+        1.344444444,
+        9.111111111,
+        17.96666667,
+        12.8,
+        5.8,
+        6.911111111,
+        6.822222222,
+        11.87777778,
+        13.16666667,
+        9.233333333,
+        8.655555556,
+        10.04444444,
+        7.022222222,
+        7.644444444,
+        8.311111111,
+        16.71111111,
+        18.85555556,
+        12.14444444,
+        13.27777778,
+        11.18888889,
+        7.088888889,
+        8.255555556,
+        7.522222222,
+        9.955555556,
+        9.933333333,
+        4.866666667,
+        15.25555556,
+        9.244444444,
+        9.755555556,
+        14,
+        8.955555556,
+        2.344444444,
+        17.43333333,
+        12.12222222,
+        13.46666667,
+        23,
+        18.45555556,
+        12.77777778,
+        7.211111111,
+        8.588888889,
+        14.35555556,
+        19.01111111,
+        12.4,
+        9.155555556,
+        15.6,
+        4.955555556,
+        8.966666667,
+        16.95555556,
+        9.511111111,
+        10.15555556,
+        16,
+        14.45555556,
+        21.02222222,
+        25.76666667,
+        20.5,
+        15.71111111,
+        11.67777778,
+        12.81111111,
+        12.88888889,
+        17.58888889,
+        23.12222222,
+        21.77777778,
+        24.42222222,
+        20.05555556,
+        24.32222222,
+        18.83333333,
+        19.56666667,
+        14.96666667,
+        19.68888889,
+        18.57777778,
+        23,
+        23.34444444,
+        20.7,
+        11.82222222,
+        11.48888889,
+        17.52222222,
+        22.55555556,
+        20.47777778,
+        23.01111111,
+        27.86666667,
+        30.28888889,
+        30.3,
+        22.94444444,
+        18.57777778,
+        25.51111111,
+        24.13333333,
+        30.01111111,
+        24.77777778,
+        20.28888889,
+        28.67777778,
+        32.74444444,
+        31.37777778,
+        28.52222222,
+        31.81111111,
+        27.24444444,
+        32.53333333,
+        26.15555556,
+        24.63333333,
+        28.3,
+        31.23333333,
+        32.21111111,
+        28.21111111,
+        23.07777778,
+        21.64444444,
+        24.34444444,
+        19.62222222,
+        25.14444444,
+        24.46666667,
+        23.87777778,
+        21.28888889,
+        20.22222222,
+        29.98888889,
+        32.04444444,
+        36.44444444,
+        36.01111111,
+        24.85555556,
+        23.45555556,
+        29.17777778,
+        32.25555556,
+        28.75555556,
+        30.28888889,
+        28.85555556,
+        30.45555556,
+        31.26666667,
+        28.86666667,
+        33.31111111,
+        30.66666667,
+        28.67777778,
+        27.4,
+        32.2,
+        25.41111111,
+        22.23333333,
+        26.67777778,
+        30.21111111,
+        29.15555556,
+        29.65555556,
+        31.94444444,
+        31.43333333,
+        28.35555556,
+        24.8,
+        25.5,
+        25.42222222,
+        24.17777778,
+        20.88888889,
+        24.35555556,
+        25.54444444,
+        22,
+        27.95555556,
+        29.42222222,
+        28.88888889,
+        26.8,
+        28.2,
+        26.92222222,
+        24.13333333,
+        22.61111111,
+        26.15555556,
+        30.57777778,
+        30.86666667,
+        29.92222222,
+        27.33333333,
+        23.43333333,
+        24.68888889,
+        26.94444444,
+        28.81111111,
+        25.54444444,
+        22.48888889,
+        21.67777778,
+        19.74444444,
+        23.82222222,
+        25.91111111,
+        30.85555556,
+        28.48888889,
+        29.21111111,
+        28.37777778,
+        22.4,
+        25.55555556,
+        27.35555556,
+        30.67777778,
+        27.95555556,
+        25.98888889,
+        23.46666667,
+        25.37777778,
+        20.46666667,
+        22.54444444,
+        20.18888889,
+        22.24444444,
+        26.84444444,
+        25.8,
+        29.62222222,
+        26.36666667,
+        32.24444444,
+        29.84444444,
+        28.33333333,
+        31.22222222,
+        29.9,
+        29.98888889,
+        27.42222222,
+        25.54444444,
+        20.22222222,
+        24,
+        24.52222222,
+        25.02222222,
+        16.12222222,
+        17.58888889,
+        23.25555556,
+        15.75555556,
+        18.66666667,
+        18.4,
+        12.52222222,
+        20.07777778,
+        28.62222222,
+        17.23333333,
+        16.6,
+        13.34444444,
+        10.98888889,
+        9.522222222,
+        5.8,
+        6.811111111,
+        6.555555556,
+        12.18888889,
+        12.64444444,
+        4.2,
+        3.577777778,
+        8.888888889,
+        15.23333333,
+        16.11111111,
+        18.36666667,
+        16.98888889,
+        15.63333333,
+        16.46666667,
+        15.55555556,
+        15.65555556,
+        17.42222222,
+        18.74444444,
+        19.48888889,
+        15.9,
+        19.73333333,
+        13.02222222,
+        8.1,
+        8.933333333,
+        11.3,
+        12.38888889,
+        8.3,
+        12.38888889,
+        6.388888889,
+        4.211111111,
+        4.666666667,
+        0.7,
+        7.133333333,
+        2.344444444,
+        1.088888889,
+        0.111111111,
+        11.62222222,
+        10.84444444,
+        8.777777778,
+        3.5,
+        3.4,
+        7.211111111,
+        5.711111111,
+        9.677777778,
+        12.25555556,
+        10.15555556,
+        6.511111111,
+        4.911111111,
+        1.5,
+        11.44444444,
+        15.54444444,
+        8.122222222,
+        6.233333333,
+        7,
+        4.355555556,
+        0.277777778,
+        3.711111111,
+        2.888888889,
+        1.555555556,
+        3.888888889,
+        4.555555556,
+        5.666666667,
+        7.833333333,
+        9.833333333,
+        10.02222222,
+        6.288888889,
+        5.366666667,
+        11.41111111,
+        9.566666667,
+        9.744444444,
+        13.57777778,
+        9.433333333,
+        3.1,
+        11.08888889,
+        3.844444444,
+        2.488888889,
+        7.544444444,
+        4.488888889,
+        -0.455555556,
+        -2.111111111,
+        -3.566666667,
+        -1.955555556,
+        3.955555556,
+        1.222222222,
+    ]
+    week_number = [f"W{i//7}" if i % 7 == 0 else None for i in range(0, 365)]
 
-start = 50
-size = 100
-data = {
-    "Date": dates[start:size],
-    "Temp°C": temp[start:size],
-    "Week": numpy.array(max[start:size]) + 5,
-    "WeekN": week_number[start:size],
-}
+    start = 50
+    size = 100
+    data = {
+        "Date": dates[start:size],
+        "Temp°C": temp[start:size],
+        "Week": numpy.array(max[start:size]) + 5,
+        "WeekN": week_number[start:size],
+    }
 
-page = """
+    page = """
 # Line - Texts
 
 <|{data}|chart|x=Date|y[1]=Temp°C|y[2]=Week|mode[2]=text|text[2]=WeekN|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/map-bubbles.py

@@ -18,135 +18,136 @@ import pandas
 
 from taipy.gui import Gui
 
-# Largest cities: name, location and population
-# Source: https://simplemaps.com/data/world-cities
-cities = [
-    {"name": "Tokyo", "lat": 35.6839, "lon": 139.7744, "population": 39105000},
-    {"name": "Jakarta", "lat": -6.2146, "lon": 106.8451, "population": 35362000},
-    {"name": "Delhi", "lat": 28.6667, "lon": 77.2167, "population": 31870000},
-    {"name": "Manila", "lat": 14.6, "lon": 120.9833, "population": 23971000},
-    {"name": "São Paulo", "lat": -23.5504, "lon": -46.6339, "population": 22495000},
-    {"name": "Seoul", "lat": 37.56, "lon": 126.99, "population": 22394000},
-    {"name": "Mumbai", "lat": 19.0758, "lon": 72.8775, "population": 22186000},
-    {"name": "Shanghai", "lat": 31.1667, "lon": 121.4667, "population": 22118000},
-    {"name": "Mexico City", "lat": 19.4333, "lon": -99.1333, "population": 21505000},
-    {"name": "Guangzhou", "lat": 23.1288, "lon": 113.259, "population": 21489000},
-    {"name": "Cairo", "lat": 30.0444, "lon": 31.2358, "population": 19787000},
-    {"name": "Beijing", "lat": 39.904, "lon": 116.4075, "population": 19437000},
-    {"name": "New York", "lat": 40.6943, "lon": -73.9249, "population": 18713220},
-    {"name": "Kolkāta", "lat": 22.5727, "lon": 88.3639, "population": 18698000},
-    {"name": "Moscow", "lat": 55.7558, "lon": 37.6178, "population": 17693000},
-    {"name": "Bangkok", "lat": 13.75, "lon": 100.5167, "population": 17573000},
-    {"name": "Dhaka", "lat": 23.7289, "lon": 90.3944, "population": 16839000},
-    {"name": "Buenos Aires", "lat": -34.5997, "lon": -58.3819, "population": 16216000},
-    {"name": "Ōsaka", "lat": 34.752, "lon": 135.4582, "population": 15490000},
-    {"name": "Lagos", "lat": 6.45, "lon": 3.4, "population": 15487000},
-    {"name": "Istanbul", "lat": 41.01, "lon": 28.9603, "population": 15311000},
-    {"name": "Karachi", "lat": 24.86, "lon": 67.01, "population": 15292000},
-    {"name": "Kinshasa", "lat": -4.3317, "lon": 15.3139, "population": 15056000},
-    {"name": "Shenzhen", "lat": 22.535, "lon": 114.054, "population": 14678000},
-    {"name": "Bangalore", "lat": 12.9791, "lon": 77.5913, "population": 13999000},
-    {"name": "Ho Chi Minh City", "lat": 10.8167, "lon": 106.6333, "population": 13954000},
-    {"name": "Tehran", "lat": 35.7, "lon": 51.4167, "population": 13819000},
-    {"name": "Los Angeles", "lat": 34.1139, "lon": -118.4068, "population": 12750807},
-    {"name": "Rio de Janeiro", "lat": -22.9083, "lon": -43.1964, "population": 12486000},
-    {"name": "Chengdu", "lat": 30.66, "lon": 104.0633, "population": 11920000},
-    {"name": "Baoding", "lat": 38.8671, "lon": 115.4845, "population": 11860000},
-    {"name": "Chennai", "lat": 13.0825, "lon": 80.275, "population": 11564000},
-    {"name": "Lahore", "lat": 31.5497, "lon": 74.3436, "population": 11148000},
-    {"name": "London", "lat": 51.5072, "lon": -0.1275, "population": 11120000},
-    {"name": "Paris", "lat": 48.8566, "lon": 2.3522, "population": 11027000},
-    {"name": "Tianjin", "lat": 39.1467, "lon": 117.2056, "population": 10932000},
-    {"name": "Linyi", "lat": 35.0606, "lon": 118.3425, "population": 10820000},
-    {"name": "Shijiazhuang", "lat": 38.0422, "lon": 114.5086, "population": 10784600},
-    {"name": "Zhengzhou", "lat": 34.7492, "lon": 113.6605, "population": 10136000},
-    {"name": "Nanyang", "lat": 32.9987, "lon": 112.5292, "population": 10013600},
-    {"name": "Hyderābād", "lat": 17.3617, "lon": 78.4747, "population": 9840000},
-    {"name": "Wuhan", "lat": 30.5872, "lon": 114.2881, "population": 9729000},
-    {"name": "Handan", "lat": 36.6116, "lon": 114.4894, "population": 9549700},
-    {"name": "Nagoya", "lat": 35.1167, "lon": 136.9333, "population": 9522000},
-    {"name": "Weifang", "lat": 36.7167, "lon": 119.1, "population": 9373000},
-    {"name": "Lima", "lat": -12.06, "lon": -77.0375, "population": 8992000},
-    {"name": "Zhoukou", "lat": 33.625, "lon": 114.6418, "population": 8953172},
-    {"name": "Luanda", "lat": -8.8383, "lon": 13.2344, "population": 8883000},
-    {"name": "Ganzhou", "lat": 25.8292, "lon": 114.9336, "population": 8677600},
-    {"name": "Tongshan", "lat": 34.261, "lon": 117.1859, "population": 8669000},
-    {"name": "Kuala Lumpur", "lat": 3.1478, "lon": 101.6953, "population": 8639000},
-    {"name": "Chicago", "lat": 41.8373, "lon": -87.6862, "population": 8604203},
-    {"name": "Heze", "lat": 35.2333, "lon": 115.4333, "population": 8287693},
-    {"name": "Chongqing", "lat": 29.55, "lon": 106.5069, "population": 8261000},
-    {"name": "Hanoi", "lat": 21.0245, "lon": 105.8412, "population": 8246600},
-    {"name": "Fuyang", "lat": 32.8986, "lon": 115.8045, "population": 8200264},
-    {"name": "Changsha", "lat": 28.1987, "lon": 112.9709, "population": 8154700},
-    {"name": "Dongguan", "lat": 23.0475, "lon": 113.7493, "population": 8142000},
-    {"name": "Jining", "lat": 35.4, "lon": 116.5667, "population": 8081905},
-    {"name": "Jinan", "lat": 36.6667, "lon": 116.9833, "population": 7967400},
-    {"name": "Pune", "lat": 18.5196, "lon": 73.8553, "population": 7948000},
-    {"name": "Foshan", "lat": 23.0292, "lon": 113.1056, "population": 7905700},
-    {"name": "Bogotá", "lat": 4.6126, "lon": -74.0705, "population": 7743955},
-    {"name": "Ahmedabad", "lat": 23.03, "lon": 72.58, "population": 7717000},
-    {"name": "Nanjing", "lat": 32.05, "lon": 118.7667, "population": 7729000},
-    {"name": "Changchun", "lat": 43.9, "lon": 125.2, "population": 7674439},
-    {"name": "Tangshan", "lat": 39.6292, "lon": 118.1742, "population": 7577289},
-    {"name": "Cangzhou", "lat": 38.3037, "lon": 116.8452, "population": 7544300},
-    {"name": "Dar es Salaam", "lat": -6.8, "lon": 39.2833, "population": 7461000},
-    {"name": "Hefei", "lat": 31.8639, "lon": 117.2808, "population": 7457027},
-    {"name": "Hong Kong", "lat": 22.3069, "lon": 114.1831, "population": 7398000},
-    {"name": "Shaoyang", "lat": 27.2418, "lon": 111.4725, "population": 7370500},
-    {"name": "Zhanjiang", "lat": 21.1967, "lon": 110.4031, "population": 7332000},
-    {"name": "Shangqiu", "lat": 34.4259, "lon": 115.6467, "population": 7325300},
-    {"name": "Nantong", "lat": 31.9829, "lon": 120.8873, "population": 7283622},
-    {"name": "Yancheng", "lat": 33.3936, "lon": 120.1339, "population": 7260240},
-    {"name": "Nanning", "lat": 22.8192, "lon": 108.315, "population": 7254100},
-    {"name": "Hengyang", "lat": 26.8968, "lon": 112.5857, "population": 7243400},
-    {"name": "Zhumadian", "lat": 32.9773, "lon": 114.0253, "population": 7231234},
-    {"name": "Shenyang", "lat": 41.8039, "lon": 123.4258, "population": 7208000},
-    {"name": "Xingtai", "lat": 37.0659, "lon": 114.4753, "population": 7104103},
-    {"name": "Xi’an", "lat": 34.2667, "lon": 108.9, "population": 7090000},
-    {"name": "Santiago", "lat": -33.45, "lon": -70.6667, "population": 7026000},
-    {"name": "Yantai", "lat": 37.3997, "lon": 121.2664, "population": 6968202},
-    {"name": "Riyadh", "lat": 24.65, "lon": 46.71, "population": 6889000},
-    {"name": "Luoyang", "lat": 34.6587, "lon": 112.4245, "population": 6888500},
-    {"name": "Kunming", "lat": 25.0433, "lon": 102.7061, "population": 6850000},
-    {"name": "Shangrao", "lat": 28.4419, "lon": 117.9633, "population": 6810700},
-    {"name": "Hangzhou", "lat": 30.25, "lon": 120.1675, "population": 6713000},
-    {"name": "Bijie", "lat": 27.3019, "lon": 105.2863, "population": 6686100},
-    {"name": "Quanzhou", "lat": 24.9139, "lon": 118.5858, "population": 6480000},
-    {"name": "Miami", "lat": 25.7839, "lon": -80.2102, "population": 6445545},
-    {"name": "Wuxi", "lat": 31.5667, "lon": 120.2833, "population": 6372624},
-    {"name": "Huanggang", "lat": 30.45, "lon": 114.875, "population": 6333000},
-    {"name": "Maoming", "lat": 21.6618, "lon": 110.9178, "population": 6313200},
-    {"name": "Nanchong", "lat": 30.7991, "lon": 106.0784, "population": 6278614},
-    {"name": "Zunyi", "lat": 27.705, "lon": 106.9336, "population": 6270700},
-    {"name": "Qujing", "lat": 25.5102, "lon": 103.8029, "population": 6155400},
-    {"name": "Baghdad", "lat": 33.35, "lon": 44.4167, "population": 6107000},
-    {"name": "Xinyang", "lat": 32.1264, "lon": 114.0672, "population": 6109106},
-]
+if __name__ == "__main__":
+    # Largest cities: name, location and population
+    # Source: https://simplemaps.com/data/world-cities
+    cities = [
+        {"name": "Tokyo", "lat": 35.6839, "lon": 139.7744, "population": 39105000},
+        {"name": "Jakarta", "lat": -6.2146, "lon": 106.8451, "population": 35362000},
+        {"name": "Delhi", "lat": 28.6667, "lon": 77.2167, "population": 31870000},
+        {"name": "Manila", "lat": 14.6, "lon": 120.9833, "population": 23971000},
+        {"name": "São Paulo", "lat": -23.5504, "lon": -46.6339, "population": 22495000},
+        {"name": "Seoul", "lat": 37.56, "lon": 126.99, "population": 22394000},
+        {"name": "Mumbai", "lat": 19.0758, "lon": 72.8775, "population": 22186000},
+        {"name": "Shanghai", "lat": 31.1667, "lon": 121.4667, "population": 22118000},
+        {"name": "Mexico City", "lat": 19.4333, "lon": -99.1333, "population": 21505000},
+        {"name": "Guangzhou", "lat": 23.1288, "lon": 113.259, "population": 21489000},
+        {"name": "Cairo", "lat": 30.0444, "lon": 31.2358, "population": 19787000},
+        {"name": "Beijing", "lat": 39.904, "lon": 116.4075, "population": 19437000},
+        {"name": "New York", "lat": 40.6943, "lon": -73.9249, "population": 18713220},
+        {"name": "Kolkāta", "lat": 22.5727, "lon": 88.3639, "population": 18698000},
+        {"name": "Moscow", "lat": 55.7558, "lon": 37.6178, "population": 17693000},
+        {"name": "Bangkok", "lat": 13.75, "lon": 100.5167, "population": 17573000},
+        {"name": "Dhaka", "lat": 23.7289, "lon": 90.3944, "population": 16839000},
+        {"name": "Buenos Aires", "lat": -34.5997, "lon": -58.3819, "population": 16216000},
+        {"name": "Ōsaka", "lat": 34.752, "lon": 135.4582, "population": 15490000},
+        {"name": "Lagos", "lat": 6.45, "lon": 3.4, "population": 15487000},
+        {"name": "Istanbul", "lat": 41.01, "lon": 28.9603, "population": 15311000},
+        {"name": "Karachi", "lat": 24.86, "lon": 67.01, "population": 15292000},
+        {"name": "Kinshasa", "lat": -4.3317, "lon": 15.3139, "population": 15056000},
+        {"name": "Shenzhen", "lat": 22.535, "lon": 114.054, "population": 14678000},
+        {"name": "Bangalore", "lat": 12.9791, "lon": 77.5913, "population": 13999000},
+        {"name": "Ho Chi Minh City", "lat": 10.8167, "lon": 106.6333, "population": 13954000},
+        {"name": "Tehran", "lat": 35.7, "lon": 51.4167, "population": 13819000},
+        {"name": "Los Angeles", "lat": 34.1139, "lon": -118.4068, "population": 12750807},
+        {"name": "Rio de Janeiro", "lat": -22.9083, "lon": -43.1964, "population": 12486000},
+        {"name": "Chengdu", "lat": 30.66, "lon": 104.0633, "population": 11920000},
+        {"name": "Baoding", "lat": 38.8671, "lon": 115.4845, "population": 11860000},
+        {"name": "Chennai", "lat": 13.0825, "lon": 80.275, "population": 11564000},
+        {"name": "Lahore", "lat": 31.5497, "lon": 74.3436, "population": 11148000},
+        {"name": "London", "lat": 51.5072, "lon": -0.1275, "population": 11120000},
+        {"name": "Paris", "lat": 48.8566, "lon": 2.3522, "population": 11027000},
+        {"name": "Tianjin", "lat": 39.1467, "lon": 117.2056, "population": 10932000},
+        {"name": "Linyi", "lat": 35.0606, "lon": 118.3425, "population": 10820000},
+        {"name": "Shijiazhuang", "lat": 38.0422, "lon": 114.5086, "population": 10784600},
+        {"name": "Zhengzhou", "lat": 34.7492, "lon": 113.6605, "population": 10136000},
+        {"name": "Nanyang", "lat": 32.9987, "lon": 112.5292, "population": 10013600},
+        {"name": "Hyderābād", "lat": 17.3617, "lon": 78.4747, "population": 9840000},
+        {"name": "Wuhan", "lat": 30.5872, "lon": 114.2881, "population": 9729000},
+        {"name": "Handan", "lat": 36.6116, "lon": 114.4894, "population": 9549700},
+        {"name": "Nagoya", "lat": 35.1167, "lon": 136.9333, "population": 9522000},
+        {"name": "Weifang", "lat": 36.7167, "lon": 119.1, "population": 9373000},
+        {"name": "Lima", "lat": -12.06, "lon": -77.0375, "population": 8992000},
+        {"name": "Zhoukou", "lat": 33.625, "lon": 114.6418, "population": 8953172},
+        {"name": "Luanda", "lat": -8.8383, "lon": 13.2344, "population": 8883000},
+        {"name": "Ganzhou", "lat": 25.8292, "lon": 114.9336, "population": 8677600},
+        {"name": "Tongshan", "lat": 34.261, "lon": 117.1859, "population": 8669000},
+        {"name": "Kuala Lumpur", "lat": 3.1478, "lon": 101.6953, "population": 8639000},
+        {"name": "Chicago", "lat": 41.8373, "lon": -87.6862, "population": 8604203},
+        {"name": "Heze", "lat": 35.2333, "lon": 115.4333, "population": 8287693},
+        {"name": "Chongqing", "lat": 29.55, "lon": 106.5069, "population": 8261000},
+        {"name": "Hanoi", "lat": 21.0245, "lon": 105.8412, "population": 8246600},
+        {"name": "Fuyang", "lat": 32.8986, "lon": 115.8045, "population": 8200264},
+        {"name": "Changsha", "lat": 28.1987, "lon": 112.9709, "population": 8154700},
+        {"name": "Dongguan", "lat": 23.0475, "lon": 113.7493, "population": 8142000},
+        {"name": "Jining", "lat": 35.4, "lon": 116.5667, "population": 8081905},
+        {"name": "Jinan", "lat": 36.6667, "lon": 116.9833, "population": 7967400},
+        {"name": "Pune", "lat": 18.5196, "lon": 73.8553, "population": 7948000},
+        {"name": "Foshan", "lat": 23.0292, "lon": 113.1056, "population": 7905700},
+        {"name": "Bogotá", "lat": 4.6126, "lon": -74.0705, "population": 7743955},
+        {"name": "Ahmedabad", "lat": 23.03, "lon": 72.58, "population": 7717000},
+        {"name": "Nanjing", "lat": 32.05, "lon": 118.7667, "population": 7729000},
+        {"name": "Changchun", "lat": 43.9, "lon": 125.2, "population": 7674439},
+        {"name": "Tangshan", "lat": 39.6292, "lon": 118.1742, "population": 7577289},
+        {"name": "Cangzhou", "lat": 38.3037, "lon": 116.8452, "population": 7544300},
+        {"name": "Dar es Salaam", "lat": -6.8, "lon": 39.2833, "population": 7461000},
+        {"name": "Hefei", "lat": 31.8639, "lon": 117.2808, "population": 7457027},
+        {"name": "Hong Kong", "lat": 22.3069, "lon": 114.1831, "population": 7398000},
+        {"name": "Shaoyang", "lat": 27.2418, "lon": 111.4725, "population": 7370500},
+        {"name": "Zhanjiang", "lat": 21.1967, "lon": 110.4031, "population": 7332000},
+        {"name": "Shangqiu", "lat": 34.4259, "lon": 115.6467, "population": 7325300},
+        {"name": "Nantong", "lat": 31.9829, "lon": 120.8873, "population": 7283622},
+        {"name": "Yancheng", "lat": 33.3936, "lon": 120.1339, "population": 7260240},
+        {"name": "Nanning", "lat": 22.8192, "lon": 108.315, "population": 7254100},
+        {"name": "Hengyang", "lat": 26.8968, "lon": 112.5857, "population": 7243400},
+        {"name": "Zhumadian", "lat": 32.9773, "lon": 114.0253, "population": 7231234},
+        {"name": "Shenyang", "lat": 41.8039, "lon": 123.4258, "population": 7208000},
+        {"name": "Xingtai", "lat": 37.0659, "lon": 114.4753, "population": 7104103},
+        {"name": "Xi’an", "lat": 34.2667, "lon": 108.9, "population": 7090000},
+        {"name": "Santiago", "lat": -33.45, "lon": -70.6667, "population": 7026000},
+        {"name": "Yantai", "lat": 37.3997, "lon": 121.2664, "population": 6968202},
+        {"name": "Riyadh", "lat": 24.65, "lon": 46.71, "population": 6889000},
+        {"name": "Luoyang", "lat": 34.6587, "lon": 112.4245, "population": 6888500},
+        {"name": "Kunming", "lat": 25.0433, "lon": 102.7061, "population": 6850000},
+        {"name": "Shangrao", "lat": 28.4419, "lon": 117.9633, "population": 6810700},
+        {"name": "Hangzhou", "lat": 30.25, "lon": 120.1675, "population": 6713000},
+        {"name": "Bijie", "lat": 27.3019, "lon": 105.2863, "population": 6686100},
+        {"name": "Quanzhou", "lat": 24.9139, "lon": 118.5858, "population": 6480000},
+        {"name": "Miami", "lat": 25.7839, "lon": -80.2102, "population": 6445545},
+        {"name": "Wuxi", "lat": 31.5667, "lon": 120.2833, "population": 6372624},
+        {"name": "Huanggang", "lat": 30.45, "lon": 114.875, "population": 6333000},
+        {"name": "Maoming", "lat": 21.6618, "lon": 110.9178, "population": 6313200},
+        {"name": "Nanchong", "lat": 30.7991, "lon": 106.0784, "population": 6278614},
+        {"name": "Zunyi", "lat": 27.705, "lon": 106.9336, "population": 6270700},
+        {"name": "Qujing", "lat": 25.5102, "lon": 103.8029, "population": 6155400},
+        {"name": "Baghdad", "lat": 33.35, "lon": 44.4167, "population": 6107000},
+        {"name": "Xinyang", "lat": 32.1264, "lon": 114.0672, "population": 6109106},
+    ]
 
-# Convert to Pandas DataFrame
-data = pandas.DataFrame(cities)
+    # Convert to Pandas DataFrame
+    data = pandas.DataFrame(cities)
 
-# Add a column holding the bubble size:
-#   Min(population) -> size =  5
-#   Max(population) -> size = 60
-solve = numpy.linalg.solve([[data["population"].min(), 1], [data["population"].max(), 1]], [5, 60])
-data["size"] = data["population"].apply(lambda p: p * solve[0] + solve[1])
+    # Add a column holding the bubble size:
+    #   Min(population) -> size =  5
+    #   Max(population) -> size = 60
+    solve = numpy.linalg.solve([[data["population"].min(), 1], [data["population"].max(), 1]], [5, 60])
+    data["size"] = data["population"].apply(lambda p: p * solve[0] + solve[1])
 
-# Add a column holding the bubble hover texts
-# Format is "<city name> [<population>]"
-data["text"] = data.apply(lambda row: f"{row['name']} [{row['population']}]", axis=1)
+    # Add a column holding the bubble hover texts
+    # Format is "<city name> [<population>]"
+    data["text"] = data.apply(lambda row: f"{row['name']} [{row['population']}]", axis=1)
 
-marker = {
-    # Use the "size" column to set the bubble size
-    "size": "size"
-}
+    marker = {
+        # Use the "size" column to set the bubble size
+        "size": "size"
+    }
 
-layout = {"geo": {"showland": True, "landcolor": "4A4"}}
+    layout = {"geo": {"showland": True, "landcolor": "4A4"}}
 
-page = """
+    page = """
 # Maps - Bubbles
 
 <|{data}|chart|type=scattergeo|lat=lat|lon=lon|mode=markers|marker={marker}|text=text|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/map-lines.py

@@ -17,162 +17,163 @@ from typing import Any, Dict, List
 
 from taipy.gui import Gui
 
-# Busiest US airports
-# Source: https://en.wikipedia.org/wiki/List_of_busiest_airports_by_passenger_traffic
-airports: Dict[str, Dict[str, float]] = {
-    "AMS": {"lat": 52.31047296675518, "lon": 4.76819929439927},
-    "ATL": {"lat": 33.64086185344307, "lon": -84.43600501711686},
-    "AYT": {"lat": 36.90419539293911, "lon": 30.801855337974292},
-    "BOS": {"lat": 42.36556559649881, "lon": -71.00960311751096},
-    "CAN": {"lat": 23.38848323741897, "lon": 113.30277713668413},
-    "CDG": {"lat": 49.008029034119915, "lon": 2.550879924581871},
-    "CJU": {"lat": 33.51035978854847, "lon": 126.4913319405336},
-    "CKG": {"lat": 29.71931573810283, "lon": 106.64211731662628},
-    "CLT": {"lat": 35.214730980190616, "lon": -80.9474735034797},
-    "CSX": {"lat": 28.196638298182446, "lon": 113.22083329905352},
-    "CTU": {"lat": 30.567492917634063, "lon": 103.94912193845805},
-    "CUN": {"lat": 21.04160313837335, "lon": -86.87407057500725},
-    "DEL": {"lat": 28.556426221725868, "lon": 77.10031185913002},
-    "DEN": {"lat": 39.85589532386815, "lon": -104.67329901305273},
-    "DFW": {"lat": 32.89998507111719, "lon": -97.04044513206443},
-    "DME": {"lat": 55.41032513421412, "lon": 37.902386927376234},
-    "DTW": {"lat": 42.216145762248594, "lon": -83.35541784824225},
-    "DXB": {"lat": 25.253155060720765, "lon": 55.365672799304534},
-    "EWR": {"lat": 40.68951508829295, "lon": -74.17446240095387},
-    "FLL": {"lat": 26.072469069499288, "lon": -80.1502073285754},
-    "FRA": {"lat": 50.037870541116, "lon": 8.562119610188235},
-    "GMP": {"lat": 37.558628944763534, "lon": 126.79445244110332},
-    "GRU": {"lat": -23.430691200492866, "lon": -46.473107371367846},
-    "HGH": {"lat": 30.2359856421667, "lon": 120.43880486944619},
-    "HND": {"lat": 35.54938443207139, "lon": 139.77979568388005},
-    "IAH": {"lat": 29.98997826322153, "lon": -95.33684707873988},
-    "IST": {"lat": 41.27696594578831, "lon": 28.73004303446375},
-    "JFK": {"lat": 40.64129497654287, "lon": -73.77813830094803},
-    "KMG": {"lat": 24.99723271310971, "lon": 102.74030761670535},
-    "LAS": {"lat": 36.08256046166282, "lon": -115.15700045025673},
-    "LAX": {"lat": 33.94157995977848, "lon": -118.40848708486908},
-    "MAD": {"lat": 40.49832400063489, "lon": -3.5676196584173754},
-    "MCO": {"lat": 28.419119921670067, "lon": -81.30451008534465},
-    "MEX": {"lat": 19.436096410278736, "lon": -99.07204777544095},
-    "MIA": {"lat": 25.795823878101675, "lon": -80.28701871639629},
-    "MSP": {"lat": 44.88471735079015, "lon": -93.22233824616785},
-    "ORD": {"lat": 41.98024003208415, "lon": -87.9089657513565},
-    "PEK": {"lat": 40.079816213451416, "lon": 116.60309064055198},
-    "PHX": {"lat": 33.43614430802288, "lon": -112.01128270596944},
-    "PKX": {"lat": 39.50978840400886, "lon": 116.41050689906415},
-    "PVG": {"lat": 31.144398958515847, "lon": 121.80823008537978},
-    "SAW": {"lat": 40.9053709590178, "lon": 29.316838841845318},
-    "SEA": {"lat": 47.448024349661814, "lon": -122.30897973141963},
-    "SFO": {"lat": 37.62122788155908, "lon": -122.37901977603573},
-    "SHA": {"lat": 31.192227319334787, "lon": 121.33425408454256},
-    "SLC": {"lat": 40.78985913031307, "lon": -111.97911351851535},
-    "SVO": {"lat": 55.97381026156798, "lon": 37.412288430689664},
-    "SZX": {"lat": 22.636827890877626, "lon": 113.81454162446936},
-    "WUH": {"lat": 30.776589409566686, "lon": 114.21244949898504},
-    "XIY": {"lat": 34.437119809208546, "lon": 108.7573508575816},
-}
+if __name__ == "__main__":
+    # Busiest US airports
+    # Source: https://en.wikipedia.org/wiki/List_of_busiest_airports_by_passenger_traffic
+    airports: Dict[str, Dict[str, float]] = {
+        "AMS": {"lat": 52.31047296675518, "lon": 4.76819929439927},
+        "ATL": {"lat": 33.64086185344307, "lon": -84.43600501711686},
+        "AYT": {"lat": 36.90419539293911, "lon": 30.801855337974292},
+        "BOS": {"lat": 42.36556559649881, "lon": -71.00960311751096},
+        "CAN": {"lat": 23.38848323741897, "lon": 113.30277713668413},
+        "CDG": {"lat": 49.008029034119915, "lon": 2.550879924581871},
+        "CJU": {"lat": 33.51035978854847, "lon": 126.4913319405336},
+        "CKG": {"lat": 29.71931573810283, "lon": 106.64211731662628},
+        "CLT": {"lat": 35.214730980190616, "lon": -80.9474735034797},
+        "CSX": {"lat": 28.196638298182446, "lon": 113.22083329905352},
+        "CTU": {"lat": 30.567492917634063, "lon": 103.94912193845805},
+        "CUN": {"lat": 21.04160313837335, "lon": -86.87407057500725},
+        "DEL": {"lat": 28.556426221725868, "lon": 77.10031185913002},
+        "DEN": {"lat": 39.85589532386815, "lon": -104.67329901305273},
+        "DFW": {"lat": 32.89998507111719, "lon": -97.04044513206443},
+        "DME": {"lat": 55.41032513421412, "lon": 37.902386927376234},
+        "DTW": {"lat": 42.216145762248594, "lon": -83.35541784824225},
+        "DXB": {"lat": 25.253155060720765, "lon": 55.365672799304534},
+        "EWR": {"lat": 40.68951508829295, "lon": -74.17446240095387},
+        "FLL": {"lat": 26.072469069499288, "lon": -80.1502073285754},
+        "FRA": {"lat": 50.037870541116, "lon": 8.562119610188235},
+        "GMP": {"lat": 37.558628944763534, "lon": 126.79445244110332},
+        "GRU": {"lat": -23.430691200492866, "lon": -46.473107371367846},
+        "HGH": {"lat": 30.2359856421667, "lon": 120.43880486944619},
+        "HND": {"lat": 35.54938443207139, "lon": 139.77979568388005},
+        "IAH": {"lat": 29.98997826322153, "lon": -95.33684707873988},
+        "IST": {"lat": 41.27696594578831, "lon": 28.73004303446375},
+        "JFK": {"lat": 40.64129497654287, "lon": -73.77813830094803},
+        "KMG": {"lat": 24.99723271310971, "lon": 102.74030761670535},
+        "LAS": {"lat": 36.08256046166282, "lon": -115.15700045025673},
+        "LAX": {"lat": 33.94157995977848, "lon": -118.40848708486908},
+        "MAD": {"lat": 40.49832400063489, "lon": -3.5676196584173754},
+        "MCO": {"lat": 28.419119921670067, "lon": -81.30451008534465},
+        "MEX": {"lat": 19.436096410278736, "lon": -99.07204777544095},
+        "MIA": {"lat": 25.795823878101675, "lon": -80.28701871639629},
+        "MSP": {"lat": 44.88471735079015, "lon": -93.22233824616785},
+        "ORD": {"lat": 41.98024003208415, "lon": -87.9089657513565},
+        "PEK": {"lat": 40.079816213451416, "lon": 116.60309064055198},
+        "PHX": {"lat": 33.43614430802288, "lon": -112.01128270596944},
+        "PKX": {"lat": 39.50978840400886, "lon": 116.41050689906415},
+        "PVG": {"lat": 31.144398958515847, "lon": 121.80823008537978},
+        "SAW": {"lat": 40.9053709590178, "lon": 29.316838841845318},
+        "SEA": {"lat": 47.448024349661814, "lon": -122.30897973141963},
+        "SFO": {"lat": 37.62122788155908, "lon": -122.37901977603573},
+        "SHA": {"lat": 31.192227319334787, "lon": 121.33425408454256},
+        "SLC": {"lat": 40.78985913031307, "lon": -111.97911351851535},
+        "SVO": {"lat": 55.97381026156798, "lon": 37.412288430689664},
+        "SZX": {"lat": 22.636827890877626, "lon": 113.81454162446936},
+        "WUH": {"lat": 30.776589409566686, "lon": 114.21244949898504},
+        "XIY": {"lat": 34.437119809208546, "lon": 108.7573508575816},
+    }
 
-# Inter US airports flights
-# Source: https://www.faa.gov/air_traffic/by_the_numbers
-flights: List[Dict[str, Any]] = [
-    {"from": "ATL", "to": "DFW", "traffic": 580},
-    {"from": "ATL", "to": "MIA", "traffic": 224},
-    {"from": "BOS", "to": "LAX", "traffic": 168},
-    {"from": "DEN", "to": "DFW", "traffic": 558},
-    {"from": "DFW", "to": "BOS", "traffic": 422},
-    {"from": "DFW", "to": "CLT", "traffic": 360},
-    {"from": "DFW", "to": "JFK", "traffic": 56},
-    {"from": "DFW", "to": "LAS", "traffic": 569},
-    {"from": "DFW", "to": "SEA", "traffic": 392},
-    {"from": "DTW", "to": "DFW", "traffic": 260},
-    {"from": "EWR", "to": "DFW", "traffic": 310},
-    {"from": "EWR", "to": "ORD", "traffic": 168},
-    {"from": "FLL", "to": "DFW", "traffic": 336},
-    {"from": "FLL", "to": "ORD", "traffic": 168},
-    {"from": "IAH", "to": "DFW", "traffic": 324},
-    {"from": "JFK", "to": "FLL", "traffic": 112},
-    {"from": "JFK", "to": "LAS", "traffic": 112},
-    {"from": "JFK", "to": "LAX", "traffic": 548},
-    {"from": "JFK", "to": "ORD", "traffic": 56},
-    {"from": "LAS", "to": "MIA", "traffic": 168},
-    {"from": "LAX", "to": "DFW", "traffic": 914},
-    {"from": "LAX", "to": "EWR", "traffic": 54},
-    {"from": "LAX", "to": "LAS", "traffic": 222},
-    {"from": "LAX", "to": "MCO", "traffic": 56},
-    {"from": "LAX", "to": "MIA", "traffic": 392},
-    {"from": "LAX", "to": "SFO", "traffic": 336},
-    {"from": "MCO", "to": "DFW", "traffic": 500},
-    {"from": "MCO", "to": "JFK", "traffic": 224},
-    {"from": "MCO", "to": "ORD", "traffic": 224},
-    {"from": "MIA", "to": "BOS", "traffic": 392},
-    {"from": "MIA", "to": "DEN", "traffic": 112},
-    {"from": "MIA", "to": "DFW", "traffic": 560},
-    {"from": "MIA", "to": "DTW", "traffic": 112},
-    {"from": "MIA", "to": "EWR", "traffic": 168},
-    {"from": "MIA", "to": "IAH", "traffic": 168},
-    {"from": "MIA", "to": "JFK", "traffic": 392},
-    {"from": "MIA", "to": "MCO", "traffic": 448},
-    {"from": "MSP", "to": "DFW", "traffic": 326},
-    {"from": "MSP", "to": "MIA", "traffic": 56},
-    {"from": "ORD", "to": "BOS", "traffic": 430},
-    {"from": "ORD", "to": "DEN", "traffic": 112},
-    {"from": "ORD", "to": "DFW", "traffic": 825},
-    {"from": "ORD", "to": "LAS", "traffic": 280},
-    {"from": "ORD", "to": "LAX", "traffic": 496},
-    {"from": "ORD", "to": "MIA", "traffic": 505},
-    {"from": "ORD", "to": "MSP", "traffic": 160},
-    {"from": "ORD", "to": "PHX", "traffic": 280},
-    {"from": "ORD", "to": "SEA", "traffic": 214},
-    {"from": "ORD", "to": "SFO", "traffic": 326},
-    {"from": "PHX", "to": "DFW", "traffic": 550},
-    {"from": "PHX", "to": "MIA", "traffic": 56},
-    {"from": "SEA", "to": "JFK", "traffic": 56},
-    {"from": "SFO", "to": "DFW", "traffic": 526},
-    {"from": "SFO", "to": "JFK", "traffic": 278},
-    {"from": "SFO", "to": "MIA", "traffic": 168},
-    {"from": "SLC", "to": "DFW", "traffic": 280},
-]
+    # Inter US airports flights
+    # Source: https://www.faa.gov/air_traffic/by_the_numbers
+    flights: List[Dict[str, Any]] = [
+        {"from": "ATL", "to": "DFW", "traffic": 580},
+        {"from": "ATL", "to": "MIA", "traffic": 224},
+        {"from": "BOS", "to": "LAX", "traffic": 168},
+        {"from": "DEN", "to": "DFW", "traffic": 558},
+        {"from": "DFW", "to": "BOS", "traffic": 422},
+        {"from": "DFW", "to": "CLT", "traffic": 360},
+        {"from": "DFW", "to": "JFK", "traffic": 56},
+        {"from": "DFW", "to": "LAS", "traffic": 569},
+        {"from": "DFW", "to": "SEA", "traffic": 392},
+        {"from": "DTW", "to": "DFW", "traffic": 260},
+        {"from": "EWR", "to": "DFW", "traffic": 310},
+        {"from": "EWR", "to": "ORD", "traffic": 168},
+        {"from": "FLL", "to": "DFW", "traffic": 336},
+        {"from": "FLL", "to": "ORD", "traffic": 168},
+        {"from": "IAH", "to": "DFW", "traffic": 324},
+        {"from": "JFK", "to": "FLL", "traffic": 112},
+        {"from": "JFK", "to": "LAS", "traffic": 112},
+        {"from": "JFK", "to": "LAX", "traffic": 548},
+        {"from": "JFK", "to": "ORD", "traffic": 56},
+        {"from": "LAS", "to": "MIA", "traffic": 168},
+        {"from": "LAX", "to": "DFW", "traffic": 914},
+        {"from": "LAX", "to": "EWR", "traffic": 54},
+        {"from": "LAX", "to": "LAS", "traffic": 222},
+        {"from": "LAX", "to": "MCO", "traffic": 56},
+        {"from": "LAX", "to": "MIA", "traffic": 392},
+        {"from": "LAX", "to": "SFO", "traffic": 336},
+        {"from": "MCO", "to": "DFW", "traffic": 500},
+        {"from": "MCO", "to": "JFK", "traffic": 224},
+        {"from": "MCO", "to": "ORD", "traffic": 224},
+        {"from": "MIA", "to": "BOS", "traffic": 392},
+        {"from": "MIA", "to": "DEN", "traffic": 112},
+        {"from": "MIA", "to": "DFW", "traffic": 560},
+        {"from": "MIA", "to": "DTW", "traffic": 112},
+        {"from": "MIA", "to": "EWR", "traffic": 168},
+        {"from": "MIA", "to": "IAH", "traffic": 168},
+        {"from": "MIA", "to": "JFK", "traffic": 392},
+        {"from": "MIA", "to": "MCO", "traffic": 448},
+        {"from": "MSP", "to": "DFW", "traffic": 326},
+        {"from": "MSP", "to": "MIA", "traffic": 56},
+        {"from": "ORD", "to": "BOS", "traffic": 430},
+        {"from": "ORD", "to": "DEN", "traffic": 112},
+        {"from": "ORD", "to": "DFW", "traffic": 825},
+        {"from": "ORD", "to": "LAS", "traffic": 280},
+        {"from": "ORD", "to": "LAX", "traffic": 496},
+        {"from": "ORD", "to": "MIA", "traffic": 505},
+        {"from": "ORD", "to": "MSP", "traffic": 160},
+        {"from": "ORD", "to": "PHX", "traffic": 280},
+        {"from": "ORD", "to": "SEA", "traffic": 214},
+        {"from": "ORD", "to": "SFO", "traffic": 326},
+        {"from": "PHX", "to": "DFW", "traffic": 550},
+        {"from": "PHX", "to": "MIA", "traffic": 56},
+        {"from": "SEA", "to": "JFK", "traffic": 56},
+        {"from": "SFO", "to": "DFW", "traffic": 526},
+        {"from": "SFO", "to": "JFK", "traffic": 278},
+        {"from": "SFO", "to": "MIA", "traffic": 168},
+        {"from": "SLC", "to": "DFW", "traffic": 280},
+    ]
 
-data = []
-max_traffic = 0
-for flight in flights:
-    airport_from = airports[flight["from"]]
-    airport_to = airports[flight["to"]]
-    # Define data source to plot this flight
-    data.append({"lat": [airport_from["lat"], airport_to["lat"]], "lon": [airport_from["lon"], airport_to["lon"]]})
-    # Store the maximum traffic
-    if flight["traffic"] > max_traffic:
-        max_traffic = flight["traffic"]
+    data = []
+    max_traffic = 0
+    for flight in flights:
+        airport_from = airports[flight["from"]]
+        airport_to = airports[flight["to"]]
+        # Define data source to plot this flight
+        data.append({"lat": [airport_from["lat"], airport_to["lat"]], "lon": [airport_from["lon"], airport_to["lon"]]})
+        # Store the maximum traffic
+        if flight["traffic"] > max_traffic:
+            max_traffic = flight["traffic"]
 
-properties = {
-    # Chart data
-    "data": data,
-    # Chart type
-    "type": "scattergeo",
-    # Keep lines only
-    "mode": "lines",
-    # Flights display as redish lines
-    "line": {"width": 2, "color": "E22"},
-    "layout": {
-        # Focus on the USA region
-        "geo": {"scope": "usa"}
-    },
-}
+    properties = {
+        # Chart data
+        "data": data,
+        # Chart type
+        "type": "scattergeo",
+        # Keep lines only
+        "mode": "lines",
+        # Flights display as redish lines
+        "line": {"width": 2, "color": "E22"},
+        "layout": {
+            # Focus on the USA region
+            "geo": {"scope": "usa"}
+        },
+    }
 
-# Set the proper data source and opacity for each trace
-for i, flight in enumerate(flights):
-    # lat[trace_index] = "[index_in_data]/lat"
-    properties[f"lat[{i+1}]"] = f"{i}/lat"
-    # lon[trace_index] = "[index_in_data]/lon"
-    properties[f"lon[{i+1}]"] = f"{i}/lon"
-    # Set flight opacity (max traffic -> max opacity)
-    # Hide legend for all flights
-    properties[f"options[{i+1}]"] = {"opacity": flight["traffic"] / max_traffic, "showlegend": False}
+    # Set the proper data source and opacity for each trace
+    for i, flight in enumerate(flights):
+        # lat[trace_index] = "[index_in_data]/lat"
+        properties[f"lat[{i+1}]"] = f"{i}/lat"
+        # lon[trace_index] = "[index_in_data]/lon"
+        properties[f"lon[{i+1}]"] = f"{i}/lon"
+        # Set flight opacity (max traffic -> max opacity)
+        # Hide legend for all flights
+        properties[f"options[{i+1}]"] = {"opacity": flight["traffic"] / max_traffic, "showlegend": False}
 
-page = """
+    page = """
 # Maps - Multiple Lines
 
 <|chart|properties={properties}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/map-simple.py

@@ -15,39 +15,40 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Flight start and end locations
-data = {
-    # Hartsfield-Jackson Atlanta International Airport
-    # to
-    # Aéroport de Paris-Charles de Gaulle
-    "lat": [33.64, 49.01],
-    "lon": [-84.44, 2.55],
-}
+if __name__ == "__main__":
+    # Flight start and end locations
+    data = {
+        # Hartsfield-Jackson Atlanta International Airport
+        # to
+        # Aéroport de Paris-Charles de Gaulle
+        "lat": [33.64, 49.01],
+        "lon": [-84.44, 2.55],
+    }
 
-layout = {
-    # Chart title
-    "title": "ATL to CDG",
-    # Hide legend
-    "showlegend": False,
-    # Focus on relevant area
-    "geo": {
-        "resolution": 50,
-        "showland": True,
-        "showocean": True,
-        "landcolor": "4a4",
-        "oceancolor": "77d",
-        "lataxis": {"range": [20, 60]},
-        "lonaxis": {"range": [-100, 20]},
-    },
-}
+    layout = {
+        # Chart title
+        "title": "ATL to CDG",
+        # Hide legend
+        "showlegend": False,
+        # Focus on relevant area
+        "geo": {
+            "resolution": 50,
+            "showland": True,
+            "showocean": True,
+            "landcolor": "4a4",
+            "oceancolor": "77d",
+            "lataxis": {"range": [20, 60]},
+            "lonaxis": {"range": [-100, 20]},
+        },
+    }
 
-# Flight displayed as a thick, red plot
-line = {"width": 5, "color": "red"}
+    # Flight displayed as a thick, red plot
+    line = {"width": 5, "color": "red"}
 
-page = """
+    page = """
 # Maps - Simple
 
 <|{data}|chart|type=scattergeo|mode=lines|lat=lat|lon=lon|line={line}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/pie-multiple.py

@@ -15,76 +15,77 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# List of countries, used as labels in the pie charts
-countries = ["US", "China", "European Union", "Russian Federation", "Brazil", "India", "Rest of World"]
+if __name__ == "__main__":
+    # List of countries, used as labels in the pie charts
+    countries = ["US", "China", "European Union", "Russian Federation", "Brazil", "India", "Rest of World"]
 
-data = [
-    {
-        # Values for GHG Emissions
-        "values": [16, 15, 12, 6, 5, 4, 42],
-        "labels": countries,
-    },
-    {
-        # Values for CO2 Emissions
-        "values": [27, 11, 25, 8, 1, 3, 25],
-        "labels": countries,
-    },
-]
-
-options = [
-    # First pie chart
-    {
-        # Show label value on hover
-        "hoverinfo": "label",
-        # Leave a hole in the middle of the chart
-        "hole": 0.4,
-        # Place the trace on the left side
-        "domain": {"column": 0},
-    },
-    # Second pie chart
-    {
-        # Show label value on hover
-        "hoverinfo": "label",
-        # Leave a hole in the middle of the chart
-        "hole": 0.4,
-        # Place the trace on the right side
-        "domain": {"column": 1},
-    },
-]
+    data = [
+        {
+            # Values for GHG Emissions
+            "values": [16, 15, 12, 6, 5, 4, 42],
+            "labels": countries,
+        },
+        {
+            # Values for CO2 Emissions
+            "values": [27, 11, 25, 8, 1, 3, 25],
+            "labels": countries,
+        },
+    ]
 
-layout = {
-    # Chart title
-    "title": "Global Emissions 1990-2011",
-    # Show traces in a 1x2 grid
-    "grid": {"rows": 1, "columns": 2},
-    "annotations": [
-        # Annotation for the first trace
+    options = [
+        # First pie chart
         {
-            "text": "GHG",
-            "font": {"size": 20},
-            # Hide annotation arrow
-            "showarrow": False,
-            # Move to the center of the trace
-            "x": 0.18,
-            "y": 0.5,
+            # Show label value on hover
+            "hoverinfo": "label",
+            # Leave a hole in the middle of the chart
+            "hole": 0.4,
+            # Place the trace on the left side
+            "domain": {"column": 0},
         },
-        # Annotation for the second trace
+        # Second pie chart
         {
-            "text": "CO2",
-            "font": {"size": 20},
-            "showarrow": False,
-            # Move to the center of the trace
-            "x": 0.81,
-            "y": 0.5,
+            # Show label value on hover
+            "hoverinfo": "label",
+            # Leave a hole in the middle of the chart
+            "hole": 0.4,
+            # Place the trace on the right side
+            "domain": {"column": 1},
         },
-    ],
-    "showlegend": False,
-}
+    ]
+
+    layout = {
+        # Chart title
+        "title": "Global Emissions 1990-2011",
+        # Show traces in a 1x2 grid
+        "grid": {"rows": 1, "columns": 2},
+        "annotations": [
+            # Annotation for the first trace
+            {
+                "text": "GHG",
+                "font": {"size": 20},
+                # Hide annotation arrow
+                "showarrow": False,
+                # Move to the center of the trace
+                "x": 0.18,
+                "y": 0.5,
+            },
+            # Annotation for the second trace
+            {
+                "text": "CO2",
+                "font": {"size": 20},
+                "showarrow": False,
+                # Move to the center of the trace
+                "x": 0.81,
+                "y": 0.5,
+            },
+        ],
+        "showlegend": False,
+    }
 
-page = """
+    page = """
 # Pie - Multiple
 
 <|{data}|chart|type=pie|x[1]=0/values|x[2]=1/values|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/pie-simple.py

@@ -15,27 +15,28 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Source https://www.fao.org/faostat/en/#data/SDGB
-data = {
-    "Country": [
-        "Rest of the world",
-        "Russian Federation",
-        "Brazil",
-        "Canada",
-        "United States of America",
-        "China",
-        "Australia",
-        "Democratic Republic of the Congo",
-        "Indonesia",
-        "Peru",
-    ],
-    "Area": [1445674.66, 815312, 496620, 346928, 309795, 219978, 134005, 126155, 92133.2, 72330.4],
-}
+if __name__ == "__main__":
+    # Source https://www.fao.org/faostat/en/#data/SDGB
+    data = {
+        "Country": [
+            "Rest of the world",
+            "Russian Federation",
+            "Brazil",
+            "Canada",
+            "United States of America",
+            "China",
+            "Australia",
+            "Democratic Republic of the Congo",
+            "Indonesia",
+            "Peru",
+        ],
+        "Area": [1445674.66, 815312, 496620, 346928, 309795, 219978, 134005, 126155, 92133.2, 72330.4],
+    }
 
-page = """
+    page = """
 # Pie - Simple
 
 <|{data}|chart|type=pie|values=Area|label=Country|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/pie-styling.py

@@ -15,30 +15,31 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-n_slices = 20
-# List: [1..n_slices]
-# Slices are bigger and bigger
-values = list(range(1, n_slices + 1))
+if __name__ == "__main__":
+    n_slices = 20
+    # List: [1..n_slices]
+    # Slices are bigger and bigger
+    values = list(range(1, n_slices + 1))
 
-marker = {
-    # Colors move around the Hue color disk
-    "colors": [f"hsl({360 * (i - 1)/(n_slices - 1)},90%,60%)" for i in values]
-}
+    marker = {
+        # Colors move around the Hue color disk
+        "colors": [f"hsl({360 * (i - 1)/(n_slices - 1)},90%,60%)" for i in values]
+    }
 
-layout = {
-    # Hide the legend
-    "showlegend": False
-}
+    layout = {
+        # Hide the legend
+        "showlegend": False
+    }
 
-options = {
-    # Hide the texts
-    "textinfo": "none"
-}
+    options = {
+        # Hide the texts
+        "textinfo": "none"
+    }
 
-page = """
+    page = """
 # Pie - Style
 
 <|{values}|chart|type=pie|marker={marker}|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/polar-angular-axis.py

@@ -15,41 +15,42 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Create a star shape
-data = {"r": [3, 1] * 5 + [3], "theta": list(range(0, 360, 36)) + [0]}
+if __name__ == "__main__":
+    # Create a star shape
+    data = {"r": [3, 1] * 5 + [3], "theta": list(range(0, 360, 36)) + [0]}
 
-options = [
-    # First plot is filled with a yellow-ish color
-    {"subplot": "polar", "fill": "toself", "fillcolor": "#E4FF87"},
-    # Second plot is filled with a blue-ish color
-    {"fill": "toself", "subplot": "polar2", "fillcolor": "#709BFF"},
-]
+    options = [
+        # First plot is filled with a yellow-ish color
+        {"subplot": "polar", "fill": "toself", "fillcolor": "#E4FF87"},
+        # Second plot is filled with a blue-ish color
+        {"fill": "toself", "subplot": "polar2", "fillcolor": "#709BFF"},
+    ]
 
-layout = {
-    "polar": {
-        # This actually is the default value
-        "angularaxis": {
-            "direction": "counterclockwise",
+    layout = {
+        "polar": {
+            # This actually is the default value
+            "angularaxis": {
+                "direction": "counterclockwise",
+            },
         },
-    },
-    "polar2": {
-        "angularaxis": {
-            # Rotate the axis 180° (0 is on the left)
-            "rotation": 180,
-            # Orient the axis clockwise
-            "direction": "clockwise",
-            # Show the angles as radians
-            "thetaunit": "radians",
+        "polar2": {
+            "angularaxis": {
+                # Rotate the axis 180° (0 is on the left)
+                "rotation": 180,
+                # Orient the axis clockwise
+                "direction": "clockwise",
+                # Show the angles as radians
+                "thetaunit": "radians",
+            },
         },
-    },
-    # Hide the legend
-    "showlegend": False,
-}
+        # Hide the legend
+        "showlegend": False,
+    }
 
-page = """
+    page = """
 # Polar Charts - Direction
 
 <|{data}|chart|type=scatterpolar|layout={layout}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/polar-area.py

@@ -17,9 +17,6 @@ import math
 
 from taipy.gui import Gui
 
-# One data point for each degree
-theta = range(0, 360)
-
 
 # Parametric equation that draws a shape (source Wolfram Mathworld)
 def draw_heart(angle):
@@ -28,29 +25,33 @@ def draw_heart(angle):
     return 2 - 2 * sa + sa * (math.sqrt(math.fabs(math.cos(a))) / (sa + 1.4))
 
 
-data = {
-    # Create the heart shape
-    "r": [draw_heart(angle) for angle in theta],
-    "theta": theta,
-}
+if __name__ == "__main__":
+    # One data point for each degree
+    theta = range(0, 360)
+
+    data = {
+        # Create the heart shape
+        "r": [draw_heart(angle) for angle in theta],
+        "theta": theta,
+    }
 
-options = {"fill": "toself"}
+    options = {"fill": "toself"}
 
-layout = {
-    # Hide the legend
-    "showlegend": False,
-    "polar": {
-        # Hide the angular axis
-        "angularaxis": {"visible": False},
-        # Hide the radial axis
-        "radialaxis": {"visible": False},
-    },
-}
+    layout = {
+        # Hide the legend
+        "showlegend": False,
+        "polar": {
+            # Hide the angular axis
+            "angularaxis": {"visible": False},
+            # Hide the radial axis
+            "radialaxis": {"visible": False},
+        },
+    }
 
-page = """
+    page = """
 # Polar - Area
 
 <|{data}|chart|type=scatterpolar|mode=none|layout={layout}|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/polar-multiple.py

@@ -17,35 +17,36 @@ import math
 
 from taipy.gui import Gui
 
-# One data point for each degree
-theta = range(0, 360)
-
 
 # Create a rose-like shaped radius-array
 def create_rose(n_petals):
     return [math.cos(math.radians(n_petals * angle)) for angle in theta]
 
 
-data = {"theta": theta, "r1": create_rose(2), "r2": create_rose(3), "r3": create_rose(4)}
+if __name__ == "__main__":
+    # One data point for each degree
+    theta = range(0, 360)
+
+    data = {"theta": theta, "r1": create_rose(2), "r2": create_rose(3), "r3": create_rose(4)}
 
-# We want three traces in the same chart
-r = ["r1", "r2", "r3"]
+    # We want three traces in the same chart
+    r = ["r1", "r2", "r3"]
 
-layout = {
-    # Hide the legend
-    "showlegend": False,
-    "polar": {
-        # Hide the angular axis
-        "angularaxis": {"visible": False},
-        # Hide the radial axis
-        "radialaxis": {"visible": False},
-    },
-}
+    layout = {
+        # Hide the legend
+        "showlegend": False,
+        "polar": {
+            # Hide the angular axis
+            "angularaxis": {"visible": False},
+            # Hide the radial axis
+            "radialaxis": {"visible": False},
+        },
+    }
 
-page = """
+    page = """
 # Polar - Multiple
 
 <|{data}|chart|type=scatterpolar|mode=lines|r={r}|theta=theta|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/polar-sectors.py

@@ -15,35 +15,36 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Sample small plot definition
-trace = {
-    "r": [1, 2, 3, 4, 1],
-    "theta": [0, 40, 80, 120, 160],
-}
+if __name__ == "__main__":
+    # Sample small plot definition
+    trace = {
+        "r": [1, 2, 3, 4, 1],
+        "theta": [0, 40, 80, 120, 160],
+    }
 
-# The same data is used in both traces
-data = [trace, trace]
+    # The same data is used in both traces
+    data = [trace, trace]
 
-# Naming the subplot is mandatory to get them both in
-# the same chart
-options = [
-    {
-        "subplot": "polar",
-    },
-    {"subplot": "polar2"},
-]
+    # Naming the subplot is mandatory to get them both in
+    # the same chart
+    options = [
+        {
+            "subplot": "polar",
+        },
+        {"subplot": "polar2"},
+    ]
 
-layout = {
-    # Hide the legend
-    "showlegend": False,
-    # Restrict the angular values for second trace
-    "polar2": {"sector": [30, 130]},
-}
+    layout = {
+        # Hide the legend
+        "showlegend": False,
+        # Restrict the angular values for second trace
+        "polar2": {"sector": [30, 130]},
+    }
 
-md = """
+    md = """
 # Polar - Sectors
 
 <|{data}|chart|type=scatterpolar|layout={layout}|options={options}|>
-"""
+    """
 
-Gui(md).run()
+    Gui(md).run()

doc/gui/examples/charts/polar-simple.py

@@ -17,9 +17,6 @@ import math
 
 from taipy.gui import Gui
 
-# One data point for each degree
-theta = range(0, 360)
-
 
 # Parametric equation that draws a shape (source Wolfram Mathworld)
 def draw_heart(angle):
@@ -28,16 +25,20 @@ def draw_heart(angle):
     return 2 - 2 * sa + sa * (math.sqrt(math.fabs(math.cos(a))) / (sa + 1.4))
 
 
-data = {
-    # Create the heart shape
-    "r": [draw_heart(angle) for angle in theta],
-    "theta": theta,
-}
+if __name__ == "__main__":
+    # One data point for each degree
+    theta = range(0, 360)
+
+    data = {
+        # Create the heart shape
+        "r": [draw_heart(angle) for angle in theta],
+        "theta": theta,
+    }
 
-page = """
+    page = """
 # Polar - Simple
 
 <|{data}|chart|type=scatterpolar|mode=lines|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/polar-tick-texts.py

@@ -45,67 +45,67 @@ def generate_hand_shapes():
     return [hours_hand, minutes_hand, seconds_hand]
 
 
-# Initialize the data set with the current time
-data = generate_hand_shapes()
-
-layout = {
-    "polar": {
-        "angularaxis": {
-            "rotation": 90,
-            "direction": "clockwise",
-            # One tick every 30 degrees
-            "tickvals": list(numpy.arange(0.0, 360.0, 30)),
-            # Text value for every tick
-            "ticktext": ["XII", "I", "II", "III", "IV", "V", "VI", "VII", "VIII", "IX", "X", "XI"],
-        },
-        "radialaxis": {"angle": 90, "visible": False, "range": [0, 12]},
-    },
-    "showlegend": False,
-}
-
-# Options to be used for all three traces
-base_opts = {"fill": "toself"}
-# Specific for hours
-hours_opts = dict(base_opts)
-hours_opts["fillcolor"] = "#FF0000"
-# Specific for minutes
-minutes_opts = dict(base_opts)
-minutes_opts["fillcolor"] = "#00FF00"
-# Specific for seconds
-seconds_opts = dict(base_opts)
-seconds_opts["fillcolor"] = "#0000FF"
-
-# Store all the chart control properties in a single object
-properties = {
-    # Don't show data point markers
-    "mode": "lines",
-    # Data for the hours
-    "theta[1]": "0/a",
-    "r[1]": "0/r",
-    # Data for the minutes
-    "theta[2]": "1/a",
-    "r[2]": "1/r",
-    # Data for the seconds
-    "theta[3]": "2/a",
-    "r[3]": "2/r",
-    # Options for the three traces
-    "options[1]": hours_opts,
-    "options[2]": minutes_opts,
-    "options[3]": seconds_opts,
-    "line": {"color": "black"},
-    "layout": layout,
-}
-
-
 # Update time on every refresh
 def on_navigate(state, page):
     state.data = generate_hand_shapes()
     return page
 
 
-page = """
+if __name__ == "__main__":
+    # Initialize the data set with the current time
+    data = generate_hand_shapes()
+
+    layout = {
+        "polar": {
+            "angularaxis": {
+                "rotation": 90,
+                "direction": "clockwise",
+                # One tick every 30 degrees
+                "tickvals": list(numpy.arange(0.0, 360.0, 30)),
+                # Text value for every tick
+                "ticktext": ["XII", "I", "II", "III", "IV", "V", "VI", "VII", "VIII", "IX", "X", "XI"],
+            },
+            "radialaxis": {"angle": 90, "visible": False, "range": [0, 12]},
+        },
+        "showlegend": False,
+    }
+
+    # Options to be used for all three traces
+    base_opts = {"fill": "toself"}
+    # Specific for hours
+    hours_opts = dict(base_opts)
+    hours_opts["fillcolor"] = "#FF0000"
+    # Specific for minutes
+    minutes_opts = dict(base_opts)
+    minutes_opts["fillcolor"] = "#00FF00"
+    # Specific for seconds
+    seconds_opts = dict(base_opts)
+    seconds_opts["fillcolor"] = "#0000FF"
+
+    # Store all the chart control properties in a single object
+    properties = {
+        # Don't show data point markers
+        "mode": "lines",
+        # Data for the hours
+        "theta[1]": "0/a",
+        "r[1]": "0/r",
+        # Data for the minutes
+        "theta[2]": "1/a",
+        "r[2]": "1/r",
+        # Data for the seconds
+        "theta[3]": "2/a",
+        "r[3]": "2/r",
+        # Options for the three traces
+        "options[1]": hours_opts,
+        "options[2]": minutes_opts,
+        "options[3]": seconds_opts,
+        "line": {"color": "black"},
+        "layout": layout,
+    }
+
+    page = """
 # Polar - Tick texts
 
 <|{data}|chart|type=scatterpolar|properties={properties}|>
-"""
-Gui(page).run()
+    """
+    Gui(page).run()

doc/gui/examples/charts/radar-multiple.py

@@ -17,39 +17,40 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-# Skill categories
-skills = ["HTML", "CSS", "Java", "Python", "PHP", "JavaScript", "Photoshop"]
-data: List[Dict[str, List]] = [
-    # Proportion of skills used for Backend development
-    {"Backend": [10, 10, 80, 70, 90, 30, 0], "Skills": skills},
-    # Proportion of skills used for Frontend development
-    {"Frontend": [90, 90, 0, 10, 20, 80, 60], "Skills": skills},
-]
-
-# Append first elements to all arrays for a nice stroke
-skills.append(skills[0])
-data[0]["Backend"].append(data[0]["Backend"][0])
-data[1]["Frontend"].append(data[1]["Frontend"][0])
-
-layout = {
-    # Force the radial axis displayed range
-    "polar": {"radialaxis": {"range": [0, 100]}}
-}
-
-# Fill the trace
-options = {"fill": "toself"}
-
-# Reflected in the legend
-names = ["Backend", "Frontend"]
-
-# To shorten the chart control definition
-r = ["0/Backend", "1/Frontend"]
-theta = ["0/Skills", "1/Skills"]
-
-page = """
+if __name__ == "__main__":
+    # Skill categories
+    skills = ["HTML", "CSS", "Java", "Python", "PHP", "JavaScript", "Photoshop"]
+    data: List[Dict[str, List]] = [
+        # Proportion of skills used for Backend development
+        {"Backend": [10, 10, 80, 70, 90, 30, 0], "Skills": skills},
+        # Proportion of skills used for Frontend development
+        {"Frontend": [90, 90, 0, 10, 20, 80, 60], "Skills": skills},
+    ]
+
+    # Append first elements to all arrays for a nice stroke
+    skills.append(skills[0])
+    data[0]["Backend"].append(data[0]["Backend"][0])
+    data[1]["Frontend"].append(data[1]["Frontend"][0])
+
+    layout = {
+        # Force the radial axis displayed range
+        "polar": {"radialaxis": {"range": [0, 100]}}
+    }
+
+    # Fill the trace
+    options = {"fill": "toself"}
+
+    # Reflected in the legend
+    names = ["Backend", "Frontend"]
+
+    # To shorten the chart control definition
+    r = ["0/Backend", "1/Frontend"]
+    theta = ["0/Skills", "1/Skills"]
+
+    page = """
 # Radar - Multiple
 
 <|{data}|chart|type=scatterpolar|name={names}|r={r}|theta={theta}|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/radar-simple.py

@@ -17,40 +17,41 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-# Source: www.statista.com (Most used programming languages in 2022)
-data: Dict[str, List] = {
-    # List of programming languages
-    "Language": ["JavaScript", "HTML/CSS", "SQL", "Python", "Typescript", "Java", "Bash/Shell"],
-    # Percentage of usage, per language
-    "%": [65.36, 55.08, 49.43, 48.07, 34.83, 33.27, 29.07],
-}
-
-# Close the shape for a nice-looking stroke
-# If the first point is *not* appended to the end of the list,
-# then the shape does not look as it is closed.
-data["%"].append(data["%"][0])
-data["Language"].append(data["Language"][0])
-
-layout = {
-    "polar": {
-        "radialaxis": {
-            # Force the radial range to 0-100
-            "range": [0, 100],
-        }
-    },
-    # Hide legend
-    "showlegend": False,
-}
-
-options = {
-    # Fill the trace
-    "fill": "toself"
-}
-
-md = """
+if __name__ == "__main__":
+    # Source: www.statista.com (Most used programming languages in 2022)
+    data: Dict[str, List] = {
+        # List of programming languages
+        "Language": ["JavaScript", "HTML/CSS", "SQL", "Python", "Typescript", "Java", "Bash/Shell"],
+        # Percentage of usage, per language
+        "%": [65.36, 55.08, 49.43, 48.07, 34.83, 33.27, 29.07],
+    }
+
+    # Close the shape for a nice-looking stroke
+    # If the first point is *not* appended to the end of the list,
+    # then the shape does not look as it is closed.
+    data["%"].append(data["%"][0])
+    data["Language"].append(data["Language"][0])
+
+    layout = {
+        "polar": {
+            "radialaxis": {
+                # Force the radial range to 0-100
+                "range": [0, 100],
+            }
+        },
+        # Hide legend
+        "showlegend": False,
+    }
+
+    options = {
+        # Fill the trace
+        "fill": "toself"
+    }
+
+    md = """
 # Radar - Simple
 
 <|{data}|chart|type=scatterpolar|r=%|theta=Language|options={options}|layout={layout}|>
-"""
+    """
 
-Gui(md).run()
+    Gui(md).run()

doc/gui/examples/charts/scatter-classification.py

@@ -20,21 +20,26 @@ from sklearn.datasets import make_classification
 
 from taipy.gui import Gui
 
-# Let scikit-learn generate a random 2-class classification problem
-features, label = make_classification(n_samples=1000, n_features=2, n_informative=2, n_redundant=0)
+if __name__ == "__main__":
+    # Let scikit-learn generate a random 2-class classification problem
+    features, label = make_classification(n_samples=1000, n_features=2, n_informative=2, n_redundant=0)
 
-random_data = pandas.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
+    random_data = pandas.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
 
-data_x = random_data["x"]
-class_A = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 0 else numpy.nan for i in range(len(random_data))]
-class_B = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 1 else numpy.nan for i in range(len(random_data))]
+    data_x = random_data["x"]
+    class_A = [
+        random_data.loc[i, "y"] if random_data.loc[i, "label"] == 0 else numpy.nan for i in range(len(random_data))
+    ]
+    class_B = [
+        random_data.loc[i, "y"] if random_data.loc[i, "label"] == 1 else numpy.nan for i in range(len(random_data))
+    ]
 
-data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
+    data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
 
-page = """
+    page = """
 # Scatter - Classification
 
 <|{data}|chart|mode=markers|x=x|y[1]=Class A|y[2]=Class B|width=60%|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/scatter-more-styling.py

@@ -15,62 +15,63 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-data = [
-    {
-        "x": [1, 2, 3, 4],
-        "y": [10, 11, 12, 13],
-    },
-    {
-        "x": [1, 2, 3, 4],
-        "y": [11, 12, 13, 14],
-    },
-    {
-        "x": [1, 2, 3, 4],
-        "y": [12, 13, 14, 15],
-    },
-]
+if __name__ == "__main__":
+    data = [
+        {
+            "x": [1, 2, 3, 4],
+            "y": [10, 11, 12, 13],
+        },
+        {
+            "x": [1, 2, 3, 4],
+            "y": [11, 12, 13, 14],
+        },
+        {
+            "x": [1, 2, 3, 4],
+            "y": [12, 13, 14, 15],
+        },
+    ]
 
-options = [
-    # First data set is represented by increasingly large
-    # disks, getting more and more opaque
-    {"marker": {"color": "red", "size": [12, 22, 32, 42], "opacity": [0.2, 0.5, 0.7, 1]}},
-    # Second data set is represented with a different symbol
-    # for each data point
-    {
-        "marker": {"color": "blue", "size": 18, "symbol": ["circle", "square", "diamond", "cross"]},
-    },
-    # Third data set is represented with green disks surrounded
-    # by a red circle that becomes thicker and thicker
-    {
-        "marker": {"color": "green", "size": 20, "line": {"color": "red", "width": [2, 4, 6, 8]}},
-    },
-]
+    options = [
+        # First data set is represented by increasingly large
+        # disks, getting more and more opaque
+        {"marker": {"color": "red", "size": [12, 22, 32, 42], "opacity": [0.2, 0.5, 0.7, 1]}},
+        # Second data set is represented with a different symbol
+        # for each data point
+        {
+            "marker": {"color": "blue", "size": 18, "symbol": ["circle", "square", "diamond", "cross"]},
+        },
+        # Third data set is represented with green disks surrounded
+        # by a red circle that becomes thicker and thicker
+        {
+            "marker": {"color": "green", "size": 20, "line": {"color": "red", "width": [2, 4, 6, 8]}},
+        },
+    ]
 
-markers = [
-    # First data set is represented by increasingly large
-    # disks, getting more and more opaque
-    {"color": "red", "size": [12, 22, 32, 42], "opacity": [0.2, 0.5, 0.7, 1]},
-    # Second data set is represented with a different symbol
-    # for each data point
-    {"color": "blue", "size": 18, "symbol": ["circle", "square", "diamond", "cross"]},
-    # Third data set is represented with green disks surrounded
-    # by a red circle that becomes thicker and thicker
-    {"color": "green", "size": 20, "line": {"color": "red", "width": [2, 4, 6, 8]}},
-]
+    markers = [
+        # First data set is represented by increasingly large
+        # disks, getting more and more opaque
+        {"color": "red", "size": [12, 22, 32, 42], "opacity": [0.2, 0.5, 0.7, 1]},
+        # Second data set is represented with a different symbol
+        # for each data point
+        {"color": "blue", "size": 18, "symbol": ["circle", "square", "diamond", "cross"]},
+        # Third data set is represented with green disks surrounded
+        # by a red circle that becomes thicker and thicker
+        {"color": "green", "size": 20, "line": {"color": "red", "width": [2, 4, 6, 8]}},
+    ]
 
-layout = {
-    # Hide the chart legend
-    "showlegend": False,
-    # Remove all ticks from the x axis
-    "xaxis": {"showticklabels": False},
-    # Remove all ticks from the y axis
-    "yaxis": {"showticklabels": False},
-}
+    layout = {
+        # Hide the chart legend
+        "showlegend": False,
+        # Remove all ticks from the x axis
+        "xaxis": {"showticklabels": False},
+        # Remove all ticks from the y axis
+        "yaxis": {"showticklabels": False},
+    }
 
-page = """
+    page = """
 ## Scatter - Customize markers
 
 <|{data}|chart|mode=markers|layout={layout}|marker={markers}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/scatter-regression.py

@@ -20,22 +20,23 @@ from sklearn.linear_model import LinearRegression
 
 from taipy.gui import Gui
 
-# Let scikit-learn generate a random regression problem
-n_samples = 300
-X, y, coef = make_regression(n_samples=n_samples, n_features=1, n_informative=1, n_targets=1, noise=25, coef=True)
+if __name__ == "__main__":
+    # Let scikit-learn generate a random regression problem
+    n_samples = 300
+    X, y, coef = make_regression(n_samples=n_samples, n_features=1, n_informative=1, n_targets=1, noise=25, coef=True)
 
-model = LinearRegression().fit(X, y)
+    model = LinearRegression().fit(X, y)
 
-x_data = X.flatten()
-y_data = y.flatten()
-predict = model.predict(X)
+    x_data = X.flatten()
+    y_data = y.flatten()
+    predict = model.predict(X)
 
-data = {"x": x_data, "y": y_data, "Regression": predict}
+    data = {"x": x_data, "y": y_data, "Regression": predict}
 
-page = """
+    page = """
 # Scatter - Regression
 
 <|{data}|chart|x=x|y[1]=y|mode[1]=markers|y[2]=Regression|mode[2]=line|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/scatter-styling.py

@@ -20,23 +20,24 @@ from sklearn.datasets import make_classification
 
 from taipy.gui import Gui
 
-# Let scikit-learn generate a random 2-class classification problem
-n_samples = 100
-features, label = make_classification(n_samples=n_samples, n_features=2, n_informative=2, n_redundant=0)
+if __name__ == "__main__":
+    # Let scikit-learn generate a random 2-class classification problem
+    n_samples = 100
+    features, label = make_classification(n_samples=n_samples, n_features=2, n_informative=2, n_redundant=0)
 
-random_data = pd.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
+    random_data = pd.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
 
-data_x = random_data["x"]
-class_A = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 0 else np.nan for i in range(n_samples)]
-class_B = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 1 else np.nan for i in range(n_samples)]
+    data_x = random_data["x"]
+    class_A = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 0 else np.nan for i in range(n_samples)]
+    class_B = [random_data.loc[i, "y"] if random_data.loc[i, "label"] == 1 else np.nan for i in range(n_samples)]
 
-data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
-marker_A = {"symbol": "circle-open", "size": 16}
-marker_B = {"symbol": "triangle-up-dot", "size": 20, "opacity": 0.7}
-page = """
+    data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
+    marker_A = {"symbol": "circle-open", "size": 16}
+    marker_B = {"symbol": "triangle-up-dot", "size": 20, "opacity": 0.7}
+    page = """
 # Scatter - Styling
 
 <|{data}|chart|mode=markers|x=x|y[1]=Class A|y[2]=Class B|width=60%|marker[1]={marker_A}|marker[2]={marker_B}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/treemap-hierarchical-values.py

@@ -15,68 +15,69 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Major countries and their surface (in km2), for every continent
-# Source: https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_area
-continents = {
-    "Africa": [
-        {"name": "Algeria", "surface": 2381741},
-        {"name": "Dem. Rep. Congo", "surface": 2344858},
-        {"name": "Sudan", "surface": 1886068},
-        {"name": "Libya", "surface": 1759540},
-        {"name": "Chad", "surface": 1284000},
-    ],
-    "Asia": [
-        {"name": "Russia-Asia", "surface": 17098246},
-        {"name": "China", "surface": 9596961},
-        {"name": "India", "surface": 3287263},
-        {"name": "Kazakhstan", "surface": 2724900},
-        {"name": "Saudi Arabia", "surface": 2149690},
-    ],
-    "Europe": [
-        {"name": "Russia-Eur", "surface": 3972400},
-        {"name": "Ukraine", "surface": 603628},
-        {"name": "France", "surface": 551695},
-        {"name": "Spain", "surface": 498980},
-        {"name": "Sweden", "surface": 450295},
-    ],
-    "Americas": [
-        {"name": "Canada", "surface": 9984670},
-        {"name": "U.S.A.", "surface": 9833517},
-        {"name": "Brazil", "surface": 8515767},
-        {"name": "Argentina", "surface": 2780400},
-        {"name": "Mexico", "surface": 1964375},
-    ],
-    "Oceania": [
-        {"name": "Australia", "surface": 7692024},
-        {"name": "Papua New Guinea", "surface": 462840},
-        {"name": "New Zealand", "surface": 270467},
-        {"name": "Solomon Islands", "surface": 28896},
-        {"name": "Fiji", "surface": 18274},
-    ],
-    "Antarctica": [{"name": "Whole", "surface": 14200000}],
-}
+if __name__ == "__main__":
+    # Major countries and their surface (in km2), for every continent
+    # Source: https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_area
+    continents = {
+        "Africa": [
+            {"name": "Algeria", "surface": 2381741},
+            {"name": "Dem. Rep. Congo", "surface": 2344858},
+            {"name": "Sudan", "surface": 1886068},
+            {"name": "Libya", "surface": 1759540},
+            {"name": "Chad", "surface": 1284000},
+        ],
+        "Asia": [
+            {"name": "Russia-Asia", "surface": 17098246},
+            {"name": "China", "surface": 9596961},
+            {"name": "India", "surface": 3287263},
+            {"name": "Kazakhstan", "surface": 2724900},
+            {"name": "Saudi Arabia", "surface": 2149690},
+        ],
+        "Europe": [
+            {"name": "Russia-Eur", "surface": 3972400},
+            {"name": "Ukraine", "surface": 603628},
+            {"name": "France", "surface": 551695},
+            {"name": "Spain", "surface": 498980},
+            {"name": "Sweden", "surface": 450295},
+        ],
+        "Americas": [
+            {"name": "Canada", "surface": 9984670},
+            {"name": "U.S.A.", "surface": 9833517},
+            {"name": "Brazil", "surface": 8515767},
+            {"name": "Argentina", "surface": 2780400},
+            {"name": "Mexico", "surface": 1964375},
+        ],
+        "Oceania": [
+            {"name": "Australia", "surface": 7692024},
+            {"name": "Papua New Guinea", "surface": 462840},
+            {"name": "New Zealand", "surface": 270467},
+            {"name": "Solomon Islands", "surface": 28896},
+            {"name": "Fiji", "surface": 18274},
+        ],
+        "Antarctica": [{"name": "Whole", "surface": 14200000}],
+    }
 
-name: list = []
-surface: list = []
-continent: list = []
+    name: list = []
+    surface: list = []
+    continent: list = []
 
-for continent_name, countries in continents.items():
-    # Create continent in root rectangle
-    name.append(continent_name)
-    surface.append(0)
-    continent.append("")
-    # Create countries in that continent rectangle
-    for country in countries:
-        name.append(country["name"])
-        surface.append(country["surface"])
-        continent.append(continent_name)
+    for continent_name, countries in continents.items():
+        # Create continent in root rectangle
+        name.append(continent_name)
+        surface.append(0)
+        continent.append("")
+        # Create countries in that continent rectangle
+        for country in countries:
+            name.append(country["name"])
+            surface.append(country["surface"])
+            continent.append(continent_name)
 
-data = {"names": name, "surfaces": surface, "continent": continent}
+    data = {"names": name, "surfaces": surface, "continent": continent}
 
-page = """
+    page = """
 # TreeMap - Hierarchical values
 
 <|{data}|chart|type=treemap|labels=names|values=surfaces|parents=continent|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/treemap-hierarchical.py

@@ -15,61 +15,62 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Partial family tree of the British House of Windsor
-# Source: https://en.wikipedia.org/wiki/Family_tree_of_the_British_royal_family
-tree = {
-    "name": [
-        "Queen Victoria",
-        "Princess Victoria",
-        "Edward VII",
-        "Alice",
-        "Alfred",
-        "Wilhelm II",
-        "Albert Victor",
-        "George V",
-        "Louise",
-        "Ernest Louis",
-        "Alfred (2)",
-        "Marie",
-        "Victoria Melita",
-        "Edward VIII",
-        "George VI",
-        "Mary",
-        "Elizabeth II",
-        "Margaret",
-        "Charles III",
-        "Anne",
-        "Andrew",
-    ],
-    "parent": [
-        "",
-        "Queen Victoria",
-        "Queen Victoria",
-        "Queen Victoria",
-        "Queen Victoria",
-        "Princess Victoria",
-        "Edward VII",
-        "Edward VII",
-        "Edward VII",
-        "Alice",
-        "Alfred",
-        "Alfred",
-        "Alfred",
-        "George V",
-        "George V",
-        "George V",
-        "George VI",
-        "George VI",
-        "Elizabeth II",
-        "Elizabeth II",
-        "Elizabeth II",
-    ],
-}
+if __name__ == "__main__":
+    # Partial family tree of the British House of Windsor
+    # Source: https://en.wikipedia.org/wiki/Family_tree_of_the_British_royal_family
+    tree = {
+        "name": [
+            "Queen Victoria",
+            "Princess Victoria",
+            "Edward VII",
+            "Alice",
+            "Alfred",
+            "Wilhelm II",
+            "Albert Victor",
+            "George V",
+            "Louise",
+            "Ernest Louis",
+            "Alfred (2)",
+            "Marie",
+            "Victoria Melita",
+            "Edward VIII",
+            "George VI",
+            "Mary",
+            "Elizabeth II",
+            "Margaret",
+            "Charles III",
+            "Anne",
+            "Andrew",
+        ],
+        "parent": [
+            "",
+            "Queen Victoria",
+            "Queen Victoria",
+            "Queen Victoria",
+            "Queen Victoria",
+            "Princess Victoria",
+            "Edward VII",
+            "Edward VII",
+            "Edward VII",
+            "Alice",
+            "Alfred",
+            "Alfred",
+            "Alfred",
+            "George V",
+            "George V",
+            "George V",
+            "George VI",
+            "George VI",
+            "Elizabeth II",
+            "Elizabeth II",
+            "Elizabeth II",
+        ],
+    }
 
-page = """
+    page = """
 # TreeMap - Hierarchical
 
 <|{tree}|chart|type=treemap|labels=name|parents=parent|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/treemap-simple.py

@@ -15,18 +15,19 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Data set: the first 10 elements of the Fibonacci sequence
-n_numbers = 10
-fibonacci = [0, 1]
-for i in range(2, n_numbers):
-    fibonacci.append(fibonacci[i - 1] + fibonacci[i - 2])
+if __name__ == "__main__":
+    # Data set: the first 10 elements of the Fibonacci sequence
+    n_numbers = 10
+    fibonacci = [0, 1]
+    for i in range(2, n_numbers):
+        fibonacci.append(fibonacci[i - 1] + fibonacci[i - 2])
 
-data = {"index": list(range(1, n_numbers + 1)), "fibonacci": fibonacci}
+    data = {"index": list(range(1, n_numbers + 1)), "fibonacci": fibonacci}
 
-page = """
+    page = """
 # TreeMap - Simple
 
 <|{data}|chart|type=treemap|labels=index|values=fibonacci|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/waterfall-period_levels.py

@@ -15,22 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Data set
-data = [
-    {
-        # The quarterly periods are grouped by year
-        "Period": [["Carry", "Q1", "Q2", "Q3", "Q4", "Current"], ["N-1", "N", "N", "N", "N", "N+1"]]
-    },
-    {
-        "Cash Flow": [25, -17, 12, 18, -8, None],
-        "Measure": ["absolute", "relative", "relative", "relative", "relative", "total"],
-    },
-]
+if __name__ == "__main__":
+    # Data set
+    data = [
+        {
+            # The quarterly periods are grouped by year
+            "Period": [["Carry", "Q1", "Q2", "Q3", "Q4", "Current"], ["N-1", "N", "N", "N", "N", "N+1"]]
+        },
+        {
+            "Cash Flow": [25, -17, 12, 18, -8, None],
+            "Measure": ["absolute", "relative", "relative", "relative", "relative", "total"],
+        },
+    ]
 
-page = """
+    page = """
 # Waterfall - Period levels
 
 <|{data}|chart|type=waterfall|x=0/Period|y=1/Cash Flow|measure=1/Measure|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/waterfall-simple.py

@@ -15,17 +15,18 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Data set
-data = {
-    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
-    "Values": [10, -5, 20, -10, 30],
-    "Measure": ["absolute", "relative", "relative", "relative", "relative"],
-}
+if __name__ == "__main__":
+    # Data set
+    data = {
+        "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+        "Values": [10, -5, 20, -10, 30],
+        "Measure": ["absolute", "relative", "relative", "relative", "relative"],
+    }
 
-page = """
+    page = """
 # Waterfall - Simple
 
 <|{data}|chart|type=waterfall|x=Day|y=Values|measure=Measure|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/charts/waterfall-styling.py

@@ -15,32 +15,33 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# 9-hole course
-n_holes = 9
+if __name__ == "__main__":
+    # 9-hole course
+    n_holes = 9
 
-# Data set
-# Each entry holds an array of values. One for each hole, plus one for th
-data = {
-    # ["Hole1", "Hole2", ..., "Hole9"]
-    "Hole": [f"Hole{h}" for h in range(1, n_holes + 1)] + ["Score"],
-    # Par for each hole
-    "Par": [3, 4, 4, 5, 3, 5, 4, 5, 3] + [None],  # type: ignore
-    # Score for each hole
-    "Score": [4, 4, 5, 4, 4, 5, 4, 5, 4] + [None],  # type: ignore
-    # Represented as relative values except for the last one
-    "M": n_holes * ["relative"] + ["total"],
-}
+    # Data set
+    # Each entry holds an array of values. One for each hole, plus one for th
+    data = {
+        # ["Hole1", "Hole2", ..., "Hole9"]
+        "Hole": [f"Hole{h}" for h in range(1, n_holes + 1)] + ["Score"],
+        # Par for each hole
+        "Par": [3, 4, 4, 5, 3, 5, 4, 5, 3] + [None],  # type: ignore
+        # Score for each hole
+        "Score": [4, 4, 5, 4, 4, 5, 4, 5, 4] + [None],  # type: ignore
+        # Represented as relative values except for the last one
+        "M": n_holes * ["relative"] + ["total"],
+    }
 
-# Compute difference (Score-Par)
-data["Diff"] = [data["Score"][i] - data["Par"][i] for i in range(0, n_holes)] + [None]  # type: ignore[index]
+    # Compute difference (Score-Par)
+    data["Diff"] = [data["Score"][i] - data["Par"][i] for i in range(0, n_holes)] + [None]  # type: ignore[index]
 
-# Show positive values in red, and negative values in green
-options = {"decreasing": {"marker": {"color": "green"}}, "increasing": {"marker": {"color": "red"}}}
+    # Show positive values in red, and negative values in green
+    options = {"decreasing": {"marker": {"color": "green"}}, "increasing": {"marker": {"color": "red"}}}
 
-page = """
+    page = """
 # Waterfall - Styling
 
 <|{data}|chart|type=waterfall|x=Hole|y=Diff|measure=M|options={options}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/date-min-max.py

@@ -17,12 +17,13 @@ import datetime
 
 from taipy.gui import Gui
 
-date = datetime.date(2024, 6, 15)
-start = datetime.date(2024, 5, 15)
-end = datetime.date(2024, 7, 15)
+if __name__ == "__main__":
+    date = datetime.date(2024, 6, 15)
+    start = datetime.date(2024, 5, 15)
+    end = datetime.date(2024, 7, 15)
 
-page = """
+    page = """
 <|{date}|date|min={start}|max={end}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/file_download-dynamic-temp-file.py

@@ -19,11 +19,6 @@ from tempfile import NamedTemporaryFile
 
 from taipy.gui import Gui, download
 
-# Initial precision
-precision = 10
-# Stores the path to the temporary file
-temp_path = None
-
 
 def pi(precision: int) -> list[int]:
     """Compute Pi to the required precision.
@@ -66,7 +61,13 @@ def download_pi(state):
     download(state, content=temp_file.name, name="pi.csv", on_action=clean_up)
 
 
-page = """
+if __name__ == "__main__":
+    # Initial precision
+    precision = 10
+    # Stores the path to the temporary file
+    temp_path = None
+
+    page = """
 # File Download - Dynamic content
 
 Precision:
@@ -74,6 +75,6 @@ Precision:
 <|{precision}|slider|min=2|max=10000|>
 
 <|{None}|file_download|on_action=download_pi|label=Download Pi digits|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/file_download-dynamic.py

@@ -18,9 +18,6 @@ from decimal import Decimal, getcontext
 
 from taipy.gui import Gui, download
 
-# Initial precision
-precision = 10
-
 
 def pi(precision: int) -> list[int]:
     """Compute Pi to the required precision.
@@ -57,7 +54,11 @@ def download_pi(state):
     download(state, content=bytes(buffer.getvalue(), "UTF-8"), name="pi.csv")
 
 
-page = """
+if __name__ == "__main__":
+    # Initial precision
+    precision = 10
+
+    page = """
 # File Download - Dynamic content
 
 Precision:
@@ -65,6 +66,6 @@ Precision:
 <|{precision}|slider|min=2|max=10000|>
 
 <|{None}|file_download|on_action=download_pi|label=Download Pi digits|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-color-map.py

@@ -15,23 +15,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-# Color wavelength
-color_wl = 530
-# Color ranges by wavelength
-color_map = {
-    200: None,
-    380: "violet",
-    435: "blue",
-    500: "cyan",
-    520: "green",
-    565: "yellow",
-    590: "orange",
-    625: "red",
-    740: None,
-}
+if __name__ == "__main__":
+    # Color wavelength
+    color_wl = 530
+    # Color ranges by wavelength
+    color_map = {
+        200: None,
+        380: "violet",
+        435: "blue",
+        500: "cyan",
+        520: "green",
+        565: "yellow",
+        590: "orange",
+        625: "red",
+        740: None,
+    }
 
-page = """
+    page = """
 <|{color_wl}|metric|color_map={color_map}|format=%d nm|min=200|max=800|bar_color=gray|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-formats.py

@@ -15,12 +15,12 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-speed = 60
-variation = 15
+if __name__ == "__main__":
+    speed = 60
+    variation = 15
 
-page = """
+    page = """
 <|{speed}|metric|format=%d km/h|delta={variation}|delta_format=%d %%|>
-"""
+    """
 
-
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-hide-value.py

@@ -15,9 +15,9 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-page = """
+if __name__ == "__main__":
+    page = """
 <|90|metric|don't show_value|>
-"""
+    """
 
-
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-layout.py

@@ -15,20 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 45
-# The layout object reference can be found in Plotly's documentation:
-#         https://plotly.com/python/reference/layout/
-layout = {
-    "paper_bgcolor": "lightblue",
-    "font": {
-        "size": 30,
-        "color": "blue",
-        "family": "Arial",
-    },
-}
+if __name__ == "__main__":
+    value = 45
+    # The layout object reference can be found in Plotly's documentation:
+    #         https://plotly.com/python/reference/layout/
+    layout = {
+        "paper_bgcolor": "lightblue",
+        "font": {
+            "size": 30,
+            "color": "blue",
+            "family": "Arial",
+        },
+    }
 
-page = """
+    page = """
 <|{value}|metric|layout={layout}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-range.py

@@ -15,11 +15,11 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 120
+if __name__ == "__main__":
+    value = 120
 
-page = """
+    page = """
 <|{value}|metric|min=50|max=150|>
-"""
+    """
 
-
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-simple.py

@@ -15,12 +15,13 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 72
-delta = 15
-threshold = 60
+if __name__ == "__main__":
+    value = 72
+    delta = 15
+    threshold = 60
 
-page = """
+    page = """
 <|{value}|metric|delta={delta}|threshold={threshold}|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/metric-type.py

@@ -15,12 +15,13 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 72
-delta = 15
-threshold = 60
+if __name__ == "__main__":
+    value = 72
+    delta = 15
+    threshold = 60
 
-page = """
+    page = """
 <|{value}|metric|threshold={threshold}|type=linear|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/number-min-max.py

@@ -15,10 +15,11 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 50
+if __name__ == "__main__":
+    value = 50
 
-page = """
+    page = """
 <|{value}|number|min=10|max=60|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/number-step.py

@@ -15,10 +15,11 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-value = 50
+if __name__ == "__main__":
+    value = 50
 
-page = """
+    page = """
 <|{value}|number|step=2|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()

doc/gui/examples/controls/slider-date-range.py

@@ -17,24 +17,6 @@ from datetime import date, timedelta
 
 from taipy.gui import Gui
 
-# Create the list of dates (all year 2000)
-all_dates = {}
-all_dates_str = []
-start_date = date(2000, 1, 1)
-end_date = date(2001, 1, 1)
-a_date = start_date
-while a_date < end_date:
-    date_str = a_date.strftime("%Y/%m/%d")
-    all_dates_str.append(date_str)
-    all_dates[date_str] = a_date
-    a_date += timedelta(days=1)
-
-# Initial selection: first and last day
-dates = [all_dates_str[1], all_dates_str[-1]]
-# These two variables are used in text controls
-start_sel = all_dates[dates[0]]
-end_sel = all_dates[dates[1]]
-
 
 def on_change(state, _, var_value):
     # Update the text controls
@@ -42,7 +24,26 @@ def on_change(state, _, var_value):
     state.end_sel = all_dates[var_value[1]]
 
 
-page = """
+if __name__ == "__main__":
+    # Create the list of dates (all year 2000)
+    all_dates = {}
+    all_dates_str = []
+    start_date = date(2000, 1, 1)
+    end_date = date(2001, 1, 1)
+    a_date = start_date
+    while a_date < end_date:
+        date_str = a_date.strftime("%Y/%m/%d")
+        all_dates_str.append(date_str)
+        all_dates[date_str] = a_date
+        a_date += timedelta(days=1)
+
+    # Initial selection: first and last day
+    dates = [all_dates_str[1], all_dates_str[-1]]
+    # These two variables are used in text controls
+    start_sel = all_dates[dates[0]]
+    end_sel = all_dates[dates[1]]
+
+    page = """
 # Slider - Date range
 
 <|{dates}|slider|lov={all_dates_str}|>
@@ -50,6 +51,6 @@ page = """
 Start: <|{start_sel}|text|format=d MMM|>
 
 End: <|{end_sel}|text|format=d MMM|>
-"""
+    """
 
-Gui(page).run()
+    Gui(page).run()