Merge branch 'plotly:main' into master

Author: sthagen

CHANGELOG.md

@@ -4,12 +4,17 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
 
+## [6.3.0] - 2025-08-12
+
 ### Updated
-- Updated Plotly.js from version 3.0.1 to version 3.0.3. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#303----2025-07-23) for more information.
+- Updated Plotly.js from version 3.0.1 to version 3.1.0. See the plotly.js [release notes](https://github.com/plotly/plotly.js/releases) for more information. [[#5318](https://github.com/plotly/plotly.py/pull/5318)]
 
 ### Added
 - Exposed `plotly.io.get_chrome()` as a function which can be called from within a Python script. [[#5282](https://github.com/plotly/plotly.py/pull/5282)]
 
+### Fixed
+- Resolved issue causing extraneous engine deprecation warnings [[#5287](https://github.com/plotly/plotly.py/pull/5287)], with thanks to @jdbeel for the contribution!
+
 ## [6.2.0] - 2025-06-26
 
 ### Added

codegen/datatypes.py

@@ -10,6 +10,10 @@
     "choroplethmapbox",
     "densitymapbox",
 ]
+locationmode_traces = [
+    "choropleth",
+    "scattergeo",
+]
 
 
 def get_typing_type(plotly_type, array_ok=False):
@@ -100,6 +104,7 @@ def build_datatype_py(node):
 
     if (
         node.name_property in deprecated_mapbox_traces
+        or node.name_property in locationmode_traces
         or node.name_property == "template"
     ):
         buffer.write("import warnings\n")
@@ -341,6 +346,27 @@ def __init__(self"""
 constructor must be a dict or
 an instance of :class:`{class_name}`\"\"\")
 
+        """
+    )
+
+    # Add warning for 'country names' locationmode
+    if node.name_property in locationmode_traces:
+        buffer.write(
+            f"""
+        if locationmode == "country names" and kwargs.get("_validate"):
+            warnings.warn(
+                "The library used by the *country names* `locationmode` option is changing in an upcoming version. "
+                "Country names in existing plots may not work in the new version. "
+                "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.",
+                DeprecationWarning,
+                stacklevel=5,
+            )
+
+            """
+        )
+
+    buffer.write(
+        f"""
         self._skip_invalid = kwargs.pop("skip_invalid", False)
         self._validate = kwargs.pop("_validate", True)
         """

codegen/resources/plot-schema.json

@@ -24,7 +24,7 @@
 # The short X.Y version
 version = ""
 # The full version, including alpha/beta/rc tags
-release = "6.2.0"
+release = "6.3.0"
 
 
 # -- General configuration ---------------------------------------------------

doc/apidoc/conf.py

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.3
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.14
+    version: 3.9.0
   plotly:
     description: How to adjust axes properties in Python - axes titles, styling and
       coloring axes and grid lines, ticks, tick labels and more.
@@ -619,6 +619,38 @@ fig.update_yaxes(zeroline=True, zerolinewidth=2, zerolinecolor='LightPink')
 fig.show()
 ```
 
+##### Controlling Zero Line Layer
+
+*New in 6.3*
+
+By default, zero lines are displayed below traces. Set `zerolinelayer="above traces"` on an axis to display its zero line above traces:
+
+```python
+import plotly.graph_objects as go
+
+x = ['A', 'B', 'C', 'D', 'A']
+y = [2, 0, 4, -3, 2]
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=x,
+            y=y,
+            fill='toself',
+            mode='none',
+            fillcolor='lightpink'
+        )
+    ],
+    layout=dict(
+        yaxis=dict(
+            zerolinelayer="above traces"  # Change to "below traces" to see the difference
+        ),
+    )
+)
+
+fig.show()
+```
+
 #### Setting the Range of Axes Manually
 
 The visible x and y axis range can be configured manually by setting the `range` axis property to a list of two values, the lower and upper bound.

doc/python/axes.md

@@ -208,15 +208,16 @@ fig.show()
 Plotly comes with two built-in geometries which do not require an external GeoJSON file:
 
 1. USA States
-2. Countries as defined in the Natural Earth dataset.
+2. Countries
 
-**Note and disclaimer:** cultural (as opposed to physical) features are by definition subject to change, debate and dispute. Plotly includes data from Natural Earth "as-is" and defers to the [Natural Earth policy regarding disputed borders](https://www.naturalearthdata.com/downloads/50m-cultural-vectors/50m-admin-0-countries-2/) which read:
+In **Plotly.py 6.3 and later**, the built-in countries geometry is created from the following sources:
+- [UN data](https://geoportal.un.org/arcgis/sharing/rest/content/items/d7caaff3ef4b4f7c82689b7c4694ad92/data) for country borders, coastlines, land, and ocean layers.
+- Natural Earth data for lakes, rivers, and subunits layers.
 
-> Natural Earth Vector draws boundaries of countries according to defacto status. We show who actually controls the situation on the ground.
+In **earlier versions of Plotly.py**, the built-in countries geometry is based on Natural Earth data only. Plotly includes data from Natural Earth "as-is". This dataset draws boundaries of countries according to de facto status. See the [Natural Earth page for more details](https://www.naturalearthdata.com/downloads/50m-cultural-vectors/50m-admin-0-countries-2/).
 
 To use the built-in countries geometry, provide `locations` as [three-letter ISO country codes](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3).
 
-
 ```python
 import plotly.express as px
 

doc/python/choropleth-maps.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.4.2
+      format_version: '1.3'
+      jupytext_version: 1.17.2
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.7
+    version: 3.12.4
   plotly:
     description: How to set the configuration options of figures using the Plotly
       Python graphing library.
@@ -323,6 +323,42 @@ fig.update_layout(xaxis={'type': 'date'})
 fig.show(config=config)
 ```
 
+### Disabling Buttons for Specific Axes
+
+*New in 6.3*
+
+Disabling the zoom in, zoom out, and autoscale buttons for specific axes is supported on cartesian axes using the `modebardisable` attribute. In the following example, the zoom in and zoom out buttons are disabled on the `xaxis`, meaning these buttons only zoom in and out on the `yaxis`. Disable the autoscale button using `modebardisable='autoscale'`. You can also disable the zoom and autoscale buttons using `modebardisable='zoominout+autoscale'`.
+
+```python
+import plotly.graph_objects as go
+import plotly.data
+
+df = plotly.data.stocks()
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=df['date'],
+            y=df['GOOG'],
+            mode='lines+markers',
+            name='Google Stock Price'
+        )
+    ],
+    layout=go.Layout(
+        title='Google Stock Price Over Time with Mode Bar Disabled',
+        xaxis=dict(
+            title='Date',
+            # Try zooming in or out using the modebar buttons. These only apply to the yaxis in this exampe.
+            modebardisable='zoominout'
+        ),
+        yaxis=dict(
+            title='Stock Price (USD)',
+        )
+    )
+)
+fig.show()
+```
+
 ### Configuring Figures in Dash Apps
 
 The same configuration dictionary that you pass to the `config` parameter of the `show()` method can also be passed to the [`config` property of a `dcc.Graph` component](https://dash.plotly.com/dash-core-components/graph).

doc/python/configuration-options.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.1
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.11
+    version: 3.12.4
   plotly:
     description: How to use hover text and formatting in Python with Plotly.
     display_as: file_settings
@@ -83,6 +83,57 @@ fig.update_layout(hovermode="x unified")
 fig.show()
 ```
 
+#### Customize Title in Unified Hovermode
+
+*New in 6.3*
+
+Customize the title shown in unified hovermode, by specifing `unifiedhovertitle.text`.
+
+The unified hover title is a template string that supports using variables from the data. Numbers are formatted using d3-format's syntax `%{variable:d3-format}`, for `example \"Price: %{y:$.2f}\"`. Dates are formatted using d3-time-format's syntax `%{variable|d3-time-format}`, for example `\"Day: %{2019-01-01|%A}\"`.
+
+The following example uses `'x unified'` hover and specifies a unified hover title that shows the full weekday, month, day, and year.
+
+```python
+import plotly.graph_objects as go
+import plotly.express as px
+
+df = px.data.stocks()
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=df['date'],
+            y=df['GOOG'],
+            mode='lines',
+            name='Google'
+        ),
+        go.Scatter(
+            x=df['date'],
+            y=df['AAPL'],
+            mode='lines',
+            name='Apple'
+        )
+    ],
+    layout=go.Layout(
+        title_text="Stock Prices with Custom Unified Hover Title",
+        hovermode='x unified',
+        xaxis=dict(
+            title_text='Date',
+            unifiedhovertitle=dict(
+                text='<b>%{x|%A, %B %d, %Y}</b>'
+            )
+        ),
+        yaxis=dict(
+            title_text='Price (USD)',
+            tickprefix='$'
+        )
+    )
+)
+
+fig.show()
+
+```
+
 #### Control hovermode with Dash
 
 [Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.

doc/python/hover-text-and-formatting.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.1
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.11
+    version: 3.9.0
   plotly:
     description: How to configure and style the legend in Plotly with Python.
     display_as: file_settings
@@ -254,6 +254,46 @@ fig.update_layout(legend=dict(
 fig.show()
 ```
 
+#### Legend Max Height
+
+*New in 6.3*
+
+By default, a legend can expand to fill up to half of the layout area height for a horizontal legend and the full height for a vertical legend. You can change this by specifying a `maxheight` for the legend. `maxheight` is interpreted as a ratio if it is 1 or less, and as an exact pixel value if it is greater than 1. In the following plot with many legend items, we set `maxheight` to a ratio of 0.10, giving the plot more space.
+
+```python
+import plotly.express as px
+from plotly import data
+
+df = data.gapminder().query("year==2007 and continent == 'Europe'")
+
+fig = px.scatter(df,
+                 x="gdpPercap",
+                 y="lifeExp",
+                 color="country",
+                 size="pop",
+                 size_max=45,
+                 title="Life Expectancy vs. GDP per Capita in 2007 (by Country)",
+                 labels={"gdpPercap": "GDP per Capita"},
+                )
+
+fig.update_layout(
+    xaxis=dict(
+        side="top"
+    ),
+    legend=dict(
+        orientation="h",
+        yanchor="bottom",
+        y=-0.35,
+        xanchor="center",
+        x=0.5,
+        maxheight=0.1, # Comment maxheight to see legend take up 0.5 of plotting area
+        title_text="Country"
+    ),
+)
+
+fig.show()
+```
+
 #### Styling Legends
 
 Legends support many styling options.