Refactor (#1847)

Co-authored-by: Fred Lefévère-Laoide <Fred.Lefevere-Laoide@Taipy.io>

doc/gui/examples/blocks/pane_anchor/builder.py

@@ -28,4 +28,4 @@ with tgb.Page() as page:
 
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Anchor")

doc/gui/examples/blocks/pane_anchor/markdown.py

@@ -28,4 +28,4 @@ This is the content of the page.
 """
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Anchor")

doc/gui/examples/blocks/pane_as_page/builder.py

@@ -53,9 +53,10 @@ def on_change(state, var_name: str):
     state.final_amount = state.initial_investment * progress
 
 
+pages = {
+    "main": page,
+    "_rate_pane": rate_page,
+}
+
 if __name__ == "__main__":
-    pages = {
-        "main": page,
-        "_rate_pane": rate_page,
-    }
-    Gui(pages=pages).run()
+    Gui(pages=pages).run(title="Pane - As page")

doc/gui/examples/blocks/pane_as_page/markdown.py

@@ -50,9 +50,11 @@ def on_change(state, var_name: str):
     state.final_amount = state.initial_investment * progress
 
 
+pages = {
+    "main": page,
+    "_rate_pane": rate_page,
+}
+
+
 if __name__ == "__main__":
-    pages = {
-        "main": page,
-        "_rate_pane": rate_page,
-    }
-    Gui(pages=pages).run()
+    Gui(pages=pages).run(title="Pane - As page")

doc/gui/examples/blocks/pane_persistent/builder.py

@@ -27,4 +27,4 @@ with tgb.Page() as page:
             tgb.text("Here is the content of the page.")
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Persistent")

doc/gui/examples/blocks/pane_persistent/markdown.py

@@ -30,4 +30,4 @@ Here is the content of the page.
 """
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Persistent")

doc/gui/examples/blocks/pane_simple/builder.py

@@ -35,4 +35,4 @@ with tgb.Page() as page:
     tgb.button("Show pane")
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Simple")

doc/gui/examples/blocks/pane_simple/markdown.py

@@ -36,4 +36,4 @@ This is the content of the page.
 """
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Simple")

doc/gui/examples/blocks/pane_simple_lambda/builder.py

@@ -29,4 +29,4 @@ with tgb.Page() as page:
     tgb.button("Show pane", on_action=lambda s: s.assign("show_pane", True))
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Lambda")

doc/gui/examples/blocks/pane_simple_lambda/markdown.py

@@ -30,4 +30,4 @@ This is the content of the page.
 """
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Pane - Lambda")

doc/gui/examples/broadcast.py

@@ -54,21 +54,19 @@ def start_or_stop(state: State):
     state.assign("button_text", button_texts[1 if thread else 0])
 
 
-if __name__ == "__main__":
-    button_texts = ["Start", "Stop"]
-    # Text in the start/stop button (initially "Start")
-    button_text = button_texts[0]
-
-    page = """
-# Broadcasting values
+button_texts = ["Start", "Stop"]
+# Text in the start/stop button (initially "Start")
+button_text = button_texts[0]
 
+page = """
 Counter: <|{counter}|>
 
 Timer: <|{button_text}|button|on_action=start_or_stop|>
-    """
+"""
 
+if __name__ == "__main__":
     # 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(title="Broadcasting values")

doc/gui/examples/broadcast_callback.py

@@ -38,16 +38,16 @@ def update_time(gui):
         sleep(1)
 
 
-if __name__ == "__main__":
-    current_time = datetime.now()
-    update = False
+current_time = datetime.now()
+update = False
 
-    page = """
+page = """
 Current time is: <|{current_time}|format=HH:mm:ss|>
 
 Update: <|{update}|toggle|>
-    """
+"""
 
+if __name__ == "__main__":
     gui = Gui(page)
 
     # Run thread that regularly updates the current time
@@ -55,4 +55,4 @@ Update: <|{update}|toggle|>
     thread.daemon = True
     thread.start()
 
-    gui.run()
+    gui.run(title="Broadcast - Callback")

doc/gui/examples/broadcast_change.py

@@ -32,13 +32,13 @@ def update_time(gui):
         sleep(1)
 
 
-if __name__ == "__main__":
-    current_time = datetime.now()
+current_time = datetime.now()
 
-    page = """
+page = """
 Current time is: <|{current_time}|format=HH:mm:ss|>
-    """
+"""
 
+if __name__ == "__main__":
     gui = Gui(page)
 
     # Run thread that regularly updates the current time
@@ -46,4 +46,4 @@ Current time is: <|{current_time}|format=HH:mm:ss|>
     thread.daemon = True
     thread.start()
 
-    gui.run()
+    gui.run(title="Broadcast - Change")

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

@@ -53,11 +53,9 @@ if __name__ == "__main__":
     mean_value = 0.0
 
     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(title="Chart - Advanced - Selection")

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

@@ -21,45 +21,44 @@ def f(x):
     return x * x * x / 3 - x
 
 
-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],
-    }
+# x values: [-2.2, ..., 2.2]
+x = [(x - 10) / 4.5 for x in range(0, 21)]
 
-    shape_size = 0.1
+data = {
+    "x": x,
+    # y: [f(-2.2), ..., f(2.2)]
+    "y": [f(x) for x in x],
+}
 
-    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,
-            },
-        ]
-    }
+shape_size = 0.1
 
-    page = """
-# Advanced - Annotations
+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 = """
 <|{data}|chart|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Advanced - Annotations")

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

@@ -15,27 +15,25 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 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)]
 
-    # 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]},
-    ]
+# 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)]
 
-    page = """
-# Advanced - Unbalanced data sets
+# 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 = """
 <|{data}|chart|x[1]=0/x|y[1]=0/Coarse|x[2]=1/x|y[2]=1/Fine|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Advanced - Unbalanced data sets")

doc/gui/examples/charts/advanced_annotations.py

@@ -42,10 +42,8 @@ layout = {
 }
 
 page = """
-# Advanced - Annotations
-
 <|{data}|chart|layout={layout}|>
 """
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Chart - Advanced - Annotations")

doc/gui/examples/charts/advanced_python_lib.py

@@ -48,4 +48,4 @@ page = """
 
 
 if __name__ == "__main__":
-    Gui(page).run()
+    Gui(page).run(title="Chart - Advanced - Python lib")

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

@@ -18,69 +18,67 @@ import numpy
 
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    n_years = 10
-
-    proportions_female = numpy.zeros(n_years)
-    proportions_male = numpy.zeros(n_years)
+n_years = 10
 
-    # 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))
+proportions_female = numpy.zeros(n_years)
+proportions_male = numpy.zeros(n_years)
 
-    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)
+# 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))
 
-        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))
+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)
 
-    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,
-    }
+    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))
 
-    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},
-        },
-    }
+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,
+}
 
-    page = """
-# Bar - Facing
+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 = """
 <|{data}|chart|type=bar|properties={properties}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bar facing")

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

@@ -18,38 +18,36 @@ import pandas
 
 from taipy.gui import Gui
 
-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 = """
-# Bar - Multiple
+# 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 = """
 <|{data}|chart|type=bar|x=Year|y[1]=Won|y[2]=Lost|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bar multiple")

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

@@ -17,59 +17,57 @@ import pandas
 
 from taipy.gui import Gui
 
-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 = """
-# Bar - Simple
+# 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 = """
 <|{data}|chart|type=bar|x=Year|y=%|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bar simple")

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

@@ -17,42 +17,40 @@ import pandas
 
 from taipy.gui import Gui
 
-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
-
+# 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 = """
 <|{data}|chart|type=bar|x=Year|y[1]=Won|y[2]=Lost|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bar stacked")

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

@@ -15,23 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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],
-    }
+# x values are [-10..10]
+x_range = range(-10, 11)
 
-    page = """
-# Basics - Multiple traces
+# 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 = """
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Multiple traces")

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

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

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

@@ -18,17 +18,15 @@ import pandas
 
 from taipy.gui import Gui
 
-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 = """
-# Basics - Timeline
+# 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 = """
 <|{data}|chart|x=Date|y=Value|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Timeline")

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

@@ -15,18 +15,16 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    layout = {
-        "xaxis": {
-            # Force the title of the x axis
-            "title": "Values for x"
-        }
+layout = {
+    "xaxis": {
+        # Force the title of the x axis
+        "title": "Values for x"
     }
+}
 
-    page = """
-# Basics - Title
-
+page = """
 <|{[x*x for x in range(0, 11)]}|chart|title=Plotting x squared|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Title")

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

@@ -15,42 +15,40 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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],
-    }
+# x values are [-10..10]
+x_range = range(-10, 11)
 
-    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"
-        },
-    }
+# 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],
+}
 
-    page = """
-# Basics - Multiple axis
+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 = """
 Shared axis:
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|height=300px|>
 
 With two axis:
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|yaxis[2]=y2|layout={layout}|height=300px|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Multiple axis")

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

@@ -15,17 +15,15 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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]}
+# x values are [-10..10]
+x_range = range(-10, 11)
 
-    page = """
-# Basics - 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 = """
 <|{data}|chart|x=X|y=Y|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - X range")

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

@@ -15,25 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"}
+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)",
+    ],
+}
 
-    page = """
-# Bubble - Hover text
+marker = {"size": "Sizes", "color": "Colors"}
 
+page = """
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|text=Texts|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bubble - Hover text")

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

@@ -16,21 +16,19 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"}
+data = {
+    "x": [1, 2, 3],
+    "y": [1, 2, 3],
+    "Colors": ["blue", "green", "red"],
+    "Sizes": [20, 40, 30],
+    "Opacities": [1, 0.4, 1],
+}
 
-    page = """
-# Bubble - Simple
+marker = {"color": "Colors", "size": "Sizes", "opacity": "Opacities"}
 
+page = """
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bubble - Simple")

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

@@ -16,24 +16,22 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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",
-    }
+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"],
+}
 
-    page = """
-# Bubble - Symbols
+marker = {
+    "color": "#77A",
+    "size": "Sizes",
+    "symbol": "Symbols",
+}
 
+page = """
 <|{data}|chart|mode=markers|x=x|y=y|marker={marker}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Bubble - Symbols")

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

@@ -18,19 +18,17 @@ import yfinance
 
 from taipy import Gui
 
-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 = """
-# Candlestick - Simple
+# 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 = """
 <|{stock}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Candlestick - Simple")

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

@@ -18,33 +18,31 @@ import yfinance
 
 from taipy.gui import Gui
 
-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
+# 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 = """
-# Candlestick - Styling
-
+page = """
 <|{stock}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Candlestick - Styling")

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

@@ -17,47 +17,45 @@ import datetime
 
 from taipy.gui import Gui
 
-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],
-    }
+# 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
 
-    md = """
-# Candlestick - Timeline
+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 = """
 <|{data}|chart|type=candlestick|x=Date|open=Open|close=Close|low=Low|high=High|>
-    """
+"""
 
-    Gui(md).run()
+if __name__ == "__main__":
+    Gui(md).run(title="Chart - Candlestick - Timeline")

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

@@ -20,98 +20,96 @@ import dateutil.relativedelta
 
 from taipy.gui import Gui
 
-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 is collected from January 1st, 2010, every month
+start_date = datetime.datetime(year=2010, month=1, day=1)
+period = dateutil.relativedelta.relativedelta(months=1)
 
-    # Create monthly time series
-    months = [start_date + n * period for n in range(0, len(prices["apples"]))]
+# 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 = [
-        # 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"])),
-        },
-    ]
+# Create monthly time series
+months = [start_date + n * period for n in range(0, len(prices["apples"]))]
 
-    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",
-    }
+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"])),
+    },
+]
 
-    page = """
-# Continuous Error - Multiple traces
+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 = """
 <|{data}|chart|properties={properties}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Continuous Error - Multiple traces")

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

@@ -17,59 +17,57 @@ import random
 
 from taipy.gui import Gui
 
-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]
+# 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]
 
-    # 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)]
+# 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]
 
-    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)),
-        },
-    ]
+# 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)]
 
-    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",
-    }
+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)),
+    },
+]
 
-    page = """
-# Continuous Error - Simple
+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 = """
 <|{data}|chart|properties={properties}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Continuous Error - Simple")

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

@@ -17,36 +17,34 @@ import random
 
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # Number of samples
-    n_samples = 10
-    # y values: [0..n_samples-1]
-    y = range(0, n_samples)
+# 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 = """
-# Error bars - Asymmetric
-
+page = """
 <|{data}|chart|type=bar|x=x|y=y|orientation=h|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Error bars - Asymmetric")

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

@@ -18,35 +18,33 @@ import random
 
 from taipy.gui import Gui
 
-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,
-    }
+# 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]
 
-    options = {
-        # Create the error bar information:
-        "error_y": {"type": "data", "array": error_ranges}
-    }
+# The chart data is made of the three series
+data = {
+    "x": x,
+    "y1": y,
+    "y2": perfect_y,
+}
 
-    page = """
-# Error bars - Simple
+options = {
+    # Create the error bar information:
+    "error_y": {"type": "data", "array": error_ranges}
+}
 
+page = """
 <|{data}|chart|x=x|y[1]=y1|y[2]=y2|options[1]={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Error bars - Simple")

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

@@ -17,18 +17,18 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # x values: [-10..10]
-    x_range = range(-10, 11)
-    data = {"X": x_range, "Y": [x * x for x in x_range]}
+# 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()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Rebuild")

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

@@ -15,48 +15,46 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"]
+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],
+}
 
-    options = [
-        # For the USA
-        {"stackgroup": "one", "groupnorm": "percent"},
-        # For China
-        {"stackgroup": "one"},
-        # For the EU
-        {"stackgroup": "one"},
-        # For Africa
-        {"stackgroup": "one"},
-    ]
+# Order the different traces
+ys = ["USA", "China", "EU", "Africa"]
 
-    layout = {
-        # Show all values when hovering on a data point
-        "hovermode": "x unified"
-    }
+options = [
+    # For the USA
+    {"stackgroup": "one", "groupnorm": "percent"},
+    # For China
+    {"stackgroup": "one"},
+    # For the EU
+    {"stackgroup": "one"},
+    # For Africa
+    {"stackgroup": "one"},
+]
 
-    page = """
-# Filled Area - Stacked Normalized
+layout = {
+    # Show all values when hovering on a data point
+    "hovermode": "x unified"
+}
 
+page = """
 <|{data}|chart|mode=none|x=Products|y={ys}|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Filled Area - Stacked Normalized")

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

@@ -15,25 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"},
-    ]
+data = {
+    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+    "Items": [32, 25, 86, 60, 70],
+    "Price": [80, 50, 140, 10, 70],
+}
 
-    page = """
-# Filled Area - Overlay
+options = [
+    # For items
+    {"fill": "tozeroy"},
+    # For price
+    # Using "tonexty" not to cover the first trace
+    {"fill": "tonexty"},
+]
 
+page = """
 <|{data}|chart|mode=none|x=Day|y[1]=Items|y[2]=Price|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Filled Area - Overlay")

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

@@ -15,21 +15,19 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    data = {
-        "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
-        "Items": [32, 25, 86, 60, 70],
-    }
-
-    options = {
-        # Fill to x axis
-        "fill": "tozeroy"
-    }
+data = {
+    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+    "Items": [32, 25, 86, 60, 70],
+}
 
-    page = """
-# Filled Area - Simple
+options = {
+    # Fill to x axis
+    "fill": "tozeroy"
+}
 
+page = """
 <|{data}|chart|x=Day|y=Items|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Filled Area - Simple")

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

@@ -15,26 +15,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"]
+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],
+}
 
-    options = {
-        # Group all traces in the same stack group
-        "stackgroup": "first_group"
-    }
+# Name of the three sets to trace
+items = ["Milk", "Bread", "Apples"]
 
-    page = """
-# Filled Area - Stacked
+options = {
+    # Group all traces in the same stack group
+    "stackgroup": "first_group"
+}
 
+page = """
 <|{data}|chart|mode=none|x=Month|y={items}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Filled Area - Stacked")

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

@@ -15,80 +15,78 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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],
-    }
+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."
-            },
-            # Lower-left corner
-            "domain": {"x": [0, 0.5], "y": [0, 0.5]},
+options = [
+    # For John/US
+    {
+        "scalegroup": "first",
+        "textinfo": "value",
+        "title": {
+            # "position": "top",
+            "text": "John in the U.S."
         },
-        # 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]},
+        # 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 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]},
+        # 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/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]},
+        # 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."
         },
-    ]
-
-    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},
-        ],
-    }
+        # Upper-right corner
+        "domain": {"x": [0.51, 1], "y": [0.51, 1]},
+    },
+]
 
-    page = """
-# Funnel Area - Multiple Charts
+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 = """
 <|{data}|chart|type=funnelarea|values={values}|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Funnel Area - Multiple Charts")

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

@@ -15,23 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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,
-    }
+data = {
+    "Types": ["Visits", "Downloads", "Prospects", "Invoiced", "Closed"],
+    "Visits": [13873, 10533, 5443, 2703, 908],
+}
 
-    page = """
-# Funnel - Area
+layout = {
+    # Stack the areas
+    "funnelmode": "stack",
+    # Hide the legend
+    "showlegend": False,
+}
 
+page = """
 <|{data}|chart|type=funnelarea|values=Visits|text=Types|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Funnel - Area")

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

@@ -15,24 +15,22 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"]
+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],
+}
 
-    # Legend text for each trace
-    names = ["US", "EU", "AP"]
+# Columns for each trace
+x = ["Visits_us", "Visits_eu", "Visits_ap"]
 
-    page = """
-# Funnel - Multiple traces
+# Legend text for each trace
+names = ["US", "EU", "AP"]
 
+page = """
 <|{data}|chart|type=funnel|x={x}|y=Types|name={names}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Funnel - Multiple traces")

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

@@ -15,14 +15,12 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # Data set
-    data = {"Opps": ["Hot leads", "Doc sent", "Quote", "Closed Won"], "Visits": [316, 238, 125, 83]}
-
-    page = """
-# Funnel Chart - Simple
+# Data set
+data = {"Opps": ["Hot leads", "Doc sent", "Quote", "Closed Won"], "Visits": [316, 238, 125, 83]}
 
+page = """
 <|{data}|chart|type=funnel|x=Visits|y=Opps|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Funnel - Simple")

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

@@ -15,28 +15,26 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"]},
-    }
+data = {
+    "Types": ["Website visit", "Downloads", "Prospects", "Invoice sent", "Closed"],
+    "Visits": [13873, 10533, 5443, 2703, 908],
+}
 
-    options = {
-        # Lines connecting boxes are thick, dotted and green
-        "connector": {"line": {"color": "green", "dash": "dot", "width": 4}}
-    }
+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"]},
+}
 
-    page = """
-# Funnel Chart - Custom markers
+options = {
+    # Lines connecting boxes are thick, dotted and green
+    "connector": {"line": {"color": "green", "dash": "dot", "width": 4}}
+}
 
+page = """
 <|{data}|chart|type=funnel|x=Visits|y=Types|marker={marker}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Funnel - Custom markers")

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

@@ -17,43 +17,41 @@ import datetime
 
 from taipy.gui import Gui
 
-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
-
+# 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 = """
 <|{data}|chart|type=bar|orientation=h|y=Task|x=Date|base=start|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Gantt - Simple")

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

@@ -17,57 +17,55 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-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": " "},
-    }
+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"],
+}
 
-    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]
+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": " "},
+}
 
-    page = """
-## Heatmap - Annotated
+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 = """
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Annotated")

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

@@ -15,24 +15,22 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"}
+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 = """
-# Heatmap - Colorscale
+options = {"colorscale": "Portland"}
 
+page = """
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Colorscale")

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

@@ -26,67 +26,65 @@ def spiral(th):
     return (r * numpy.cos(th), r * numpy.sin(th))
 
 
-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 Golden spiral data as a parametric curve
+(x, y) = spiral(numpy.linspace(-numpy.pi / 13, 4 * numpy.pi, 1000))
 
-    # 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]]
+# 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,
+]
 
-    # 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],
-        },
-    ]
+# 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]]
 
-    # Axis template: hide all ticks, lines and labels
-    axis = {
-        "range": [0, 2.0],
-        "showgrid": False,
-        "zeroline": False,
-        "showticklabels": False,
-        "ticks": "",
-        "title": "",
-    }
+# 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],
+    },
+]
 
-    layout = {
-        # Use the axis template for both x and y axes
-        "xaxis": axis,
-        "yaxis": axis,
-    }
+# Axis template: hide all ticks, lines and labels
+axis = {
+    "range": [0, 2.0],
+    "showgrid": False,
+    "zeroline": False,
+    "showticklabels": False,
+    "ticks": "",
+    "title": "",
+}
 
-    options = {
-        # Hide the color scale of the heatmap
-        "showscale": False
-    }
+layout = {
+    # Use the axis template for both x and y axes
+    "xaxis": axis,
+    "yaxis": axis,
+}
 
-    # 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"]
+options = {
+    # Hide the color scale of the heatmap
+    "showscale": False
+}
 
-    page = """
-## Heatmap - Drawing on top
+# 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 = """
 <|{data}|chart|type={types}|z[1]=0/z|x={xs}|y={ys}|layout={layout}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Drawing on top")

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

@@ -15,22 +15,20 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# Heatmap - Basic
+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 = """
 <|{data}|chart|type=heatmap|z=Temperatures|x=Seasons|y=Cities|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Basic")

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

@@ -15,25 +15,23 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# Heatmap - Unbalanced
+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 = """
 <|{data}|chart|type=heatmap|z=0/Temperatures|x=1/Seasons|y=0/Cities|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Unbalanced")

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

@@ -19,48 +19,46 @@ import numpy as np
 
 from taipy.gui import Gui
 
-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,
-    }
+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))),
+    },
+]
 
-    layout = {"xaxis": axis_template, "yaxis": axis_template}
+# 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,
+}
 
-    options = {
-        # Remove the color scale display
-        "showscale": False
-    }
+layout = {"xaxis": axis_template, "yaxis": axis_template}
 
-    page = """
-## Heatmap - Unequal block sizes
+options = {
+    # Remove the color scale display
+    "showscale": False
+}
 
+page = """
 <|{data}|chart|type=heatmap|z=0/z|x=1/x|y=1/y|layout={layout}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Heatmap - Unequal block sizes")

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

@@ -15,42 +15,40 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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]
+# Initial data set. y = count_of(x)
+samples = {"x": ["Apples", "Apples", "Apples", "Oranges", "Bananas", "Oranges"], "y": [5, 10, 3, 8, 5, 2]}
 
-    # 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"}},
-    }
+# Create a data set array to allow for two traces
+data = [samples, samples]
 
-    page = """
-# Histogram - Binning function
+# 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 = """
 <|{data}|chart|type=histogram|properties={properties}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - Binning function")

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

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

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

@@ -17,14 +17,12 @@ import random
 
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # Random data set
-    data = {"Count": [random.random() for _ in range(100)]}
-
-    page = """
-# Histograms - Horizontal
+# Random data set
+data = {"Count": [random.random() for _ in range(100)]}
 
+page = """
 <|{data}|chart|type=histogram|y=Count|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histograms - Horizontal")

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

@@ -17,30 +17,29 @@ import random
 
 from taipy.gui import Gui
 
-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]
+# Random set of 100 samples
+samples = {"x": [random.gauss(mu=0.0, sigma=1.0) for _ in range(100)]}
 
-    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},
-    ]
+# Use the same data for both traces
+data = [samples, samples]
 
-    layout = {
-        # Overlay the two histograms
-        "barmode": "overlay",
-        # Hide the legend
-        "showlegend": False,
-    }
+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},
+]
 
-    page = """
-# Histogram - NBins
+layout = {
+    # Overlay the two histograms
+    "barmode": "overlay",
+    # Hide the legend
+    "showlegend": False,
+}
 
+page = """
 <|{data}|chart|type=histogram|options={options}|layout={layout}|>
-    """
-    Gui(page).run()
+"""
+
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - NBins")

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

@@ -17,17 +17,15 @@ import random
 
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # Random data set
-    data = [random.random() for _ in range(100)]
-
-    # Normalize to show bin probabilities
-    options = {"histnorm": "probability"}
+# Random data set
+data = [random.random() for _ in range(100)]
 
-    page = """
-# Histogram - Normalized
+# Normalize to show bin probabilities
+options = {"histnorm": "probability"}
 
+page = """
 <|{data}|chart|type=histogram|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - Normalized")

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

@@ -17,27 +17,27 @@ import random
 
 from taipy.gui import Gui
 
-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)]}]
+# 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 = """
-# Histogram - Overlay
+page = """
 
 <|{data}|chart|type=histogram|options={options}|layout={layout}|>
-    """
-    Gui(page).run()
+"""
+
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - Overlay")

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

@@ -17,14 +17,12 @@ import random
 
 from taipy import Gui
 
-if __name__ == "__main__":
-    # Random data set
-    data = [random.gauss(0, 5) for _ in range(1000)]
-
-    page = """
-# Histogram - Simple
+# Random data set
+data = [random.gauss(0, 5) for _ in range(1000)]
 
+page = """
 <|{data}|chart|type=histogram|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - Simple")

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

@@ -17,22 +17,20 @@ import random
 
 from taipy.gui import Gui
 
-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"]
+# Data set made of two series of random numbers
+data = {"A": [random.random() for _ in range(200)], "B": [random.random() for _ in range(200)]}
 
-    layout = {
-        # Make the histogram stack the data sets
-        "barmode": "stack"
-    }
+# Names of the two traces
+names = ["A samples", "B samples"]
 
-    page = """
-# Histogram - Stacked
+layout = {
+    # Make the histogram stack the data sets
+    "barmode": "stack"
+}
 
+page = """
 <|{data}|chart|type=histogram|x[1]=A|x[2]=B|name={names}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Histogram - Stacked")

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

@@ -17,1118 +17,1116 @@ import pandas
 
 from taipy.gui import Gui
 
-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,
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-
-    start = 50
-    size = 100
-    data = {"Date": dates[start:size], "Temp°C": temp[start:size], "Min": min[start:size], "Max": max[start:size]}
+dates = pandas.date_range("2023-01-01", periods=365, freq="D")
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+    23.25555556,
+    15.75555556,
+    18.66666667,
+    18.4,
+    12.52222222,
+    20.07777778,
+    28.62222222,
+    17.23333333,
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+    13.34444444,
+    10.98888889,
+    9.522222222,
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+    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,
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+    19.73333333,
+    13.02222222,
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+    8.933333333,
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+    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,
+]
 
-    page = """
-# Line - Style
+start = 50
+size = 100
+data = {"Date": dates[start:size], "Temp°C": temp[start:size], "Min": min[start:size], "Max": max[start:size]}
 
+page = """
 <|{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()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Line - Style")

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

@@ -18,1124 +18,1122 @@ import pandas
 
 from taipy.gui import Gui
 
-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,
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-        -2.722222222,
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-        6.611111111,
-        -2.833333333,
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-        -1.388888889,
-        5.777777778,
-        2.166666667,
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-        1.5,
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-        6.222222222,
-        -2.5,
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-        6.111111111,
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-        2.666666667,
-        -2.5,
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-        8.222222222,
-        2.333333333,
-        -9.333333333,
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-        -6.277777778,
-        -0.611111111,
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-        6.111111111,
-        -4,
-        3.388888889,
-        9.333333333,
-        -6.333333333,
-        -15,
-        -12.94444444,
-        -8.722222222,
-        -6.222222222,
-        -2.833333333,
-        -2.5,
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-        3.444444444,
-        2.666666667,
-        0.888888889,
-        7.555555556,
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-        12.83333333,
-        1.777777778,
-        -0.111111111,
-        -1.055555556,
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-        11.16666667,
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-        2.444444444,
-        6.111111111,
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-        10.27777778,
-        5.888888889,
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-        1.222222222,
-        4.055555556,
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-        16.5,
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-        -8.666666667,
-        -8.055555556,
-        1.555555556,
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-    ]
-    min = [
-        -14.33333333,
-        -12.9,
-        -3.311111111,
-        -4.955555556,
-        -3.611111111,
-        0.555555556,
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-    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],
-    }
+dates = pandas.date_range("2023-01-01", periods=365, freq="D")
+temp = [
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+]
+week_number = [f"W{i//7}" if i % 7 == 0 else None for i in range(0, 365)]
 
-    page = """
-# Line - Texts
+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 = """
 <|{data}|chart|x=Date|y[1]=Temp°C|y[2]=Week|mode[2]=text|text[2]=WeekN|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Line - Texts")

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

@@ -18,136 +18,134 @@ import pandas
 
 from taipy.gui import Gui
 
-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)
+# 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},
+]
 
-    # 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])
+# Convert to Pandas DataFrame
+data = pandas.DataFrame(cities)
 
-    # 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 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])
 
-    marker = {
-        # Use the "size" column to set the bubble size
-        "size": "size"
-    }
+# 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)
 
-    layout = {"geo": {"showland": True, "landcolor": "4A4"}}
+marker = {
+    # Use the "size" column to set the bubble size
+    "size": "size"
+}
 
-    page = """
-# Maps - Bubbles
+layout = {"geo": {"showland": True, "landcolor": "4A4"}}
 
+page = """
 <|{data}|chart|type=scattergeo|lat=lat|lon=lon|mode=markers|marker={marker}|text=text|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Maps - Bubbles")

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

@@ -17,163 +17,161 @@ from typing import Any, Dict, List
 
 from taipy.gui import Gui
 
-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},
-    ]
+# 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},
+}
 
-    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"]
+# 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},
+]
 
-    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"}
-        },
-    }
+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"]
 
-    # 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}
+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"}
+    },
+}
 
-    page = """
-# Maps - Multiple Lines
+# 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 = """
 <|chart|properties={properties}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Maps - Multiple Lines")

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

@@ -15,40 +15,38 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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]},
-        },
-    }
+# 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],
+}
 
-    # Flight displayed as a thick, red plot
-    line = {"width": 5, "color": "red"}
+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]},
+    },
+}
 
-    page = """
-# Maps - Simple
+# Flight displayed as a thick, red plot
+line = {"width": 5, "color": "red"}
 
+page = """
 <|{data}|chart|type=scattergeo|mode=lines|lat=lat|lon=lon|line={line}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Maps - Simple")

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

@@ -15,77 +15,75 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"]
+# 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,
-        },
-    ]
+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
+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},
+    },
+]
+
+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
         {
-            # 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},
+            "text": "GHG",
+            "font": {"size": 20},
+            # Hide annotation arrow
+            "showarrow": False,
+            # Move to the center of the trace
+            "x": 0.18,
+            "y": 0.5,
         },
-        # Second pie chart
+        # Annotation for the second trace
         {
-            # 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},
+            "text": "CO2",
+            "font": {"size": 20},
+            "showarrow": False,
+            # Move to the center of the trace
+            "x": 0.81,
+            "y": 0.5,
         },
-    ]
-
-    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 = """
-# Pie - Multiple
+    ],
+    "showlegend": False,
+}
 
+page = """
 <|{data}|chart|type=pie|x[1]=0/values|x[2]=1/values|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Pie - Multiple")

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

@@ -15,28 +15,26 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# Pie - Simple
+# 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 = """
 <|{data}|chart|type=pie|values=Area|label=Country|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Pie - Simple")

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

@@ -15,31 +15,31 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    n_slices = 20
-    # List: [1..n_slices]
-    # Slices are bigger and bigger
-    values = list(range(1, n_slices + 1))
+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 = """
-# Pie - Style
+page = """
+#
 
 <|{values}|chart|type=pie|marker={marker}|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Pie - Style")

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

@@ -15,42 +15,40 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    # Create a star shape
-    data = {"r": [3, 1] * 5 + [3], "theta": list(range(0, 360, 36)) + [0]}
+# 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,
-    }
-
-    page = """
-# Polar Charts - Direction
+    },
+    # Hide the legend
+    "showlegend": False,
+}
 
+page = """
 <|{data}|chart|type=scatterpolar|layout={layout}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Polar - Direction")

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

@@ -25,33 +25,31 @@ def draw_heart(angle):
     return 2 - 2 * sa + sa * (math.sqrt(math.fabs(math.cos(a))) / (sa + 1.4))
 
 
-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"}
-
-    layout = {
-        # Hide the legend
-        "showlegend": False,
-        "polar": {
-            # Hide the angular axis
-            "angularaxis": {"visible": False},
-            # Hide the radial axis
-            "radialaxis": {"visible": False},
-        },
-    }
-
-    page = """
-# Polar - Area
-
+# 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"}
+
+layout = {
+    # Hide the legend
+    "showlegend": False,
+    "polar": {
+        # Hide the angular axis
+        "angularaxis": {"visible": False},
+        # Hide the radial axis
+        "radialaxis": {"visible": False},
+    },
+}
+
+page = """
 <|{data}|chart|type=scatterpolar|mode=none|layout={layout}|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Polar - Area")

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

@@ -23,30 +23,28 @@ def create_rose(n_petals):
     return [math.cos(math.radians(n_petals * angle)) for angle in theta]
 
 
-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"]
-
-    layout = {
-        # Hide the legend
-        "showlegend": False,
-        "polar": {
-            # Hide the angular axis
-            "angularaxis": {"visible": False},
-            # Hide the radial axis
-            "radialaxis": {"visible": False},
-        },
-    }
-
-    page = """
-# Polar - Multiple
-
+# 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"]
+
+layout = {
+    # Hide the legend
+    "showlegend": False,
+    "polar": {
+        # Hide the angular axis
+        "angularaxis": {"visible": False},
+        # Hide the radial axis
+        "radialaxis": {"visible": False},
+    },
+}
+
+page = """
 <|{data}|chart|type=scatterpolar|mode=lines|r={r}|theta=theta|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Polar - Multiple")

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

@@ -15,36 +15,34 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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]
+# Sample small plot definition
+trace = {
+    "r": [1, 2, 3, 4, 1],
+    "theta": [0, 40, 80, 120, 160],
+}
 
-    # Naming the subplot is mandatory to get them both in
-    # the same chart
-    options = [
-        {
-            "subplot": "polar",
-        },
-        {"subplot": "polar2"},
-    ]
+# The same data is used in both traces
+data = [trace, trace]
 
-    layout = {
-        # Hide the legend
-        "showlegend": False,
-        # Restrict the angular values for second trace
-        "polar2": {"sector": [30, 130]},
-    }
+# Naming the subplot is mandatory to get them both in
+# the same chart
+options = [
+    {
+        "subplot": "polar",
+    },
+    {"subplot": "polar2"},
+]
 
-    md = """
-# Polar - Sectors
+layout = {
+    # Hide the legend
+    "showlegend": False,
+    # Restrict the angular values for second trace
+    "polar2": {"sector": [30, 130]},
+}
 
+md = """
 <|{data}|chart|type=scatterpolar|layout={layout}|options={options}|>
-    """
+"""
 
-    Gui(md).run()
+if __name__ == "__main__":
+    Gui(md).run(title="Chart - Polar - Sectors")

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

@@ -25,20 +25,18 @@ def draw_heart(angle):
     return 2 - 2 * sa + sa * (math.sqrt(math.fabs(math.cos(a))) / (sa + 1.4))
 
 
-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,
-    }
+# One data point for each degree
+theta = range(0, 360)
 
-    page = """
-# Polar - Simple
+data = {
+    # Create the heart shape
+    "r": [draw_heart(angle) for angle in theta],
+    "theta": theta,
+}
 
+page = """
 <|{data}|chart|type=scatterpolar|mode=lines|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Polar - Simple")

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

@@ -51,61 +51,60 @@ def on_navigate(state, page):
     return 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]},
+# 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"],
         },
-        "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
-
+        "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 = """
 <|{data}|chart|type=scatterpolar|properties={properties}|>
-    """
-    Gui(page).run()
+"""
+
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Polar - Tick texts")

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

@@ -17,40 +17,38 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-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
-
+# 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 = """
 <|{data}|chart|type=scatterpolar|name={names}|r={r}|theta={theta}|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Radar - Multiple")

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

@@ -17,41 +17,39 @@ from typing import Dict, List
 
 from taipy.gui import Gui
 
-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
-
+# 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 = """
 <|{data}|chart|type=scatterpolar|r=%|theta=Language|options={options}|layout={layout}|>
-    """
+"""
 
-    Gui(md).run()
+if __name__ == "__main__":
+    Gui(md).run(title="Chart - Radar - Simple")

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

@@ -20,26 +20,24 @@ from sklearn.datasets import make_classification
 
 from taipy.gui import Gui
 
-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})
+# 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)
 
-    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))
-    ]
+random_data = pandas.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
 
-    data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
+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))
+]
 
-    page = """
-# Scatter - Classification
+data = {"x": random_data["x"], "Class A": class_A, "Class B": class_B}
 
+page = """
 <|{data}|chart|mode=markers|x=x|y[1]=Class A|y[2]=Class B|width=60%|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Scatter - Classification")

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

@@ -15,63 +15,61 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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]}},
-        },
-    ]
+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],
+    },
+]
 
-    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]}},
-    ]
+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]}},
+    },
+]
 
-    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},
-    }
+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]}},
+]
 
-    page = """
-## Scatter - Customize markers
+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 = """
 <|{data}|chart|mode=markers|layout={layout}|marker={markers}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Scatter - Customize markers")

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

@@ -20,23 +20,21 @@ from sklearn.linear_model import LinearRegression
 
 from taipy.gui import Gui
 
-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)
+# 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)
 
-    x_data = X.flatten()
-    y_data = y.flatten()
-    predict = model.predict(X)
+model = LinearRegression().fit(X, y)
 
-    data = {"x": x_data, "y": y_data, "Regression": predict}
+x_data = X.flatten()
+y_data = y.flatten()
+predict = model.predict(X)
 
-    page = """
-# Scatter - Regression
+data = {"x": x_data, "y": y_data, "Regression": predict}
 
+page = """
 <|{data}|chart|x=x|y[1]=y|mode[1]=markers|y[2]=Regression|mode[2]=line|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Scatter - Regression")

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

@@ -20,24 +20,22 @@ from sklearn.datasets import make_classification
 
 from taipy.gui import Gui
 
-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})
+# 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)
 
-    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)]
+random_data = pd.DataFrame({"x": features[:, 0], "y": features[:, 1], "label": label})
 
-    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_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}|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()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Scatter - Styling")

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

@@ -15,69 +15,67 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = []
+# 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}],
+}
 
-    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)
+name: list = []
+surface: list = []
+continent: list = []
 
-    data = {"names": name, "surfaces": surface, "continent": continent}
+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)
 
-    page = """
-# TreeMap - Hierarchical values
+data = {"names": name, "surfaces": surface, "continent": continent}
 
+page = """
 <|{data}|chart|type=treemap|labels=names|values=surfaces|parents=continent|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - TreeMap - Hierarchical values")

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

@@ -15,62 +15,60 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# TreeMap - Hierarchical
+# 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 = """
 <|{tree}|chart|type=treemap|labels=name|parents=parent|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - TreeMap - Hierarchical")

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

@@ -15,19 +15,17 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 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])
 
-    page = """
-# TreeMap - Simple
+data = {"index": list(range(1, n_numbers + 1)), "fibonacci": fibonacci}
 
+page = """
 <|{data}|chart|type=treemap|labels=index|values=fibonacci|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - TreeMap - Simple")

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

@@ -15,23 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# Waterfall - Period levels
+# 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 = """
 <|{data}|chart|type=waterfall|x=0/Period|y=1/Cash Flow|measure=1/Measure|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Waterfall - Period levels")

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

@@ -15,18 +15,16 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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 = """
-# Waterfall - Simple
+# Data set
+data = {
+    "Day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
+    "Values": [10, -5, 20, -10, 30],
+    "Measure": ["absolute", "relative", "relative", "relative", "relative"],
+}
 
+page = """
 <|{data}|chart|type=waterfall|x=Day|y=Values|measure=Measure|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Waterfall - Simple")

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

@@ -15,33 +15,31 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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"],
-    }
+# 9-hole course
+n_holes = 9
 
-    # Compute difference (Score-Par)
-    data["Diff"] = [data["Score"][i] - data["Par"][i] for i in range(0, n_holes)] + [None]  # type: ignore[index]
+# 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"],
+}
 
-    # Show positive values in red, and negative values in green
-    options = {"decreasing": {"marker": {"color": "green"}}, "increasing": {"marker": {"color": "red"}}}
+# Compute difference (Score-Par)
+data["Diff"] = [data["Score"][i] - data["Par"][i] for i in range(0, n_holes)] + [None]  # type: ignore[index]
 
-    page = """
-# Waterfall - Styling
+# Show positive values in red, and negative values in green
+options = {"decreasing": {"marker": {"color": "green"}}, "increasing": {"marker": {"color": "red"}}}
 
+page = """
 <|{data}|chart|type=waterfall|x=Hole|y=Diff|measure=M|options={options}|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Chart - Waterfall - Styling")

doc/gui/examples/controls/chat-calculator.py

@@ -45,4 +45,4 @@ page = """
 <|{messages}|chat|users={users}|sender_id={users[0]}|on_action=evaluate|>
 """
 
-Gui(page).run()
+Gui(page).run(title="Chat - Calculator")

doc/gui/examples/controls/chat-discuss.py

@@ -82,4 +82,4 @@ discuss_page = """
 """
 
 pages = {"register": register_page, "discuss": discuss_page}
-gui = Gui(pages=pages).run()
+gui = Gui(pages=pages).run(title="Chat - Discuss")

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

@@ -17,13 +17,13 @@ import datetime
 
 from taipy.gui import Gui
 
-if __name__ == "__main__":
-    date = datetime.date(2024, 6, 15)
-    start = datetime.date(2024, 5, 15)
-    end = datetime.date(2024, 7, 15)
+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()
+if __name__ == "__main__":
+    Gui(page).run(title="Date - Min/Max")

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

@@ -61,20 +61,18 @@ def download_pi(state):
     download(state, content=temp_file.name, name="pi.csv", on_action=clean_up)
 
 
-if __name__ == "__main__":
-    # Initial precision
-    precision = 10
-    # Stores the path to the temporary file
-    temp_path = None
-
-    page = """
-# File Download - Dynamic content
+# Initial precision
+precision = 10
+# Stores the path to the temporary file
+temp_path = None
 
+page = """
 Precision:
 
 <|{precision}|slider|min=2|max=10000|>
 
 <|{None}|file_download|on_action=download_pi|label=Download Pi digits|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="File Download - Dynamic content")

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

@@ -54,18 +54,16 @@ def download_pi(state):
     download(state, content=bytes(buffer.getvalue(), "UTF-8"), name="pi.csv")
 
 
-if __name__ == "__main__":
-    # Initial precision
-    precision = 10
-
-    page = """
-# File Download - Dynamic content
+# Initial precision
+precision = 10
 
+page = """
 Precision:
 
 <|{precision}|slider|min=2|max=10000|>
 
 <|{None}|file_download|on_action=download_pi|label=Download Pi digits|>
-    """
+"""
 
-    Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="File Download - Dynamic content")

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

@@ -15,24 +15,24 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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,
-    }
+# 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()
+if __name__ == "__main__":
+    Gui(page).run(title="Metric - Color Map")

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

@@ -25,4 +25,5 @@ page = """
 <|{co2_2024}|metric|delta={delta}|delta_color=invert|format=%.1f ppm|delta_format=%.1f ppm|min=300|max=500|>
 """
 
-Gui(page).run()
+if __name__ == "__main__":
+    Gui(page).run(title="Metric - Delta color")

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

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

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

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

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

@@ -15,21 +15,21 @@
 # -----------------------------------------------------------------------------------------
 from taipy.gui import Gui
 
-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",
-        },
-    }
+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()
+if __name__ == "__main__":
+    Gui(page).run(title="Metric - Layout")

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

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