Merge branch 'main' into plt-import

Author: emilykl

.github/workflows/check-js-build.yml

@@ -29,6 +29,7 @@ jobs:
         cd js
         npm ci
         npm run build
+        npm ls
     - name: Check JupyterLab build artifacts
       run: |
         # 1. Hash contents of all static files, sort by content hash

CITATION.cff

@@ -9,7 +9,8 @@ authors:
 - family-names: "Parmer"
   given-names: "Chris"
 title: "An interactive, open-source, and browser-based graphing library for Python"
-version: 5.24.1
+version: 6.3.0
 doi: 10.5281/zenodo.14503524
-date-released: 2024-09-12
+date-released: 2025-08-12
 url: "https://github.com/plotly/plotly.py"
+

CONTRIBUTING.md

@@ -120,6 +120,20 @@ you can install all packages with:
 pip install -e '.[dev]'
 ```
 
+If you're testing local changes in Jupyter Lab or Jupyter Notebook, you'll want to run these commands when you're setting up your development environment:
+```bash
+pip install jupyter
+jupyter labextension develop .
+```
+If you don't run that command, your figure will not render in the Jupyter Lab/ Jupyter Notebook editors. 
+
+If you're changing any of the code under the `js/` directory, you'll also want to run these commands:
+```
+cd js/
+npm ci
+npm run build
+```
+
 These commands also create an *editable install* of plotly.py
 so that you can test your changes iteratively without having to rebuild the plotly.py package explicitly;
 for more information please see

codegen/resources/plot-schema.json

@@ -4008,7 +4008,7 @@
         "valType": "string"
        },
        "type": {
-        "description": "Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to *geojson*, the following values are allowed: *circle*, *line*, *fill* and *symbol*. but note that *line* and *fill* are not compatible with Point GeoJSON geometries. With `sourcetype` set to *vector*, the following values are allowed:  *circle*, *line*, *fill* and *symbol*. With `sourcetype` set to *raster* or `*image*`, only the *raster* value is allowed.",
+        "description": "Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to *geojson*, the following values are allowed: *circle*, *line*, *fill* and *symbol*. but note that *line* and *fill* are not compatible with Point GeoJSON geometries. With `sourcetype` set to *vector*, the following values are allowed:  *circle*, *line*, *fill* and *symbol*. With `sourcetype` set to *raster* or *image*, only the *raster* value is allowed.",
         "dflt": "circle",
         "editType": "plot",
         "valType": "enumerated",
@@ -4414,7 +4414,7 @@
         "valType": "string"
        },
        "type": {
-        "description": "Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to *geojson*, the following values are allowed: *circle*, *line*, *fill* and *symbol*. but note that *line* and *fill* are not compatible with Point GeoJSON geometries. With `sourcetype` set to *vector*, the following values are allowed:  *circle*, *line*, *fill* and *symbol*. With `sourcetype` set to *raster* or `*image*`, only the *raster* value is allowed.",
+        "description": "Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to *geojson*, the following values are allowed: *circle*, *line*, *fill* and *symbol*. but note that *line* and *fill* are not compatible with Point GeoJSON geometries. With `sourcetype` set to *vector*, the following values are allowed:  *circle*, *line*, *fill* and *symbol*. With `sourcetype` set to *raster* or *image*, only the *raster* value is allowed.",
         "dflt": "circle",
         "editType": "plot",
         "valType": "enumerated",
@@ -47932,7 +47932,7 @@
      "valType": "number"
     },
     "source": {
-     "description": "Specifies the data URI of the image to be visualized. The URI consists of \"data:image/[<media subtype>][;base64],<data>\"",
+     "description": "Specifies the data URI of the image to be visualized. The URI consists of \"data:image/[<media subtype\\\\>][;base64\\\\],<data\\\\>\"",
      "editType": "calc",
      "valType": "string"
     },
@@ -53288,7 +53288,7 @@
      ]
     },
     "hovertemplate": {
-     "description": "Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example \"y: %{y}\" as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When showing info for several points, *xother* will be added to those with different x positions from the first point. An underscore before or after *(x|y)other* will add a space on that side, only when this field is shown. Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example \"Price: %{y:$.2f}\". https://github.com/d3/d3-format/tree/v1.4.5#d3-format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example \"Day: %{2019-01-01|%A}\". https://github.com/d3/d3-time-format/tree/v2.2.3#locale_format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plotly.com/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available.  This value here applies when hovering over dimensions. Note that `*categorycount`, *colorcount* and *bandcolorcount* are only available when `hoveron` contains the *color* flagFinally, the template string has access to variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `<extra>` is displayed in the secondary box, for example `<extra>%{fullData.name}</extra>`. To hide the secondary box completely, use an empty tag `<extra></extra>`.",
+     "description": "Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example \"y: %{y}\" as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When showing info for several points, *xother* will be added to those with different x positions from the first point. An underscore before or after *(x|y)other* will add a space on that side, only when this field is shown. Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example \"Price: %{y:$.2f}\". https://github.com/d3/d3-format/tree/v1.4.5#d3-format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example \"Day: %{2019-01-01|%A}\". https://github.com/d3/d3-time-format/tree/v2.2.3#locale_format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plotly.com/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available.  This value here applies when hovering over dimensions. Note that *categorycount*, *colorcount* and *bandcolorcount* are only available when `hoveron` contains the *color* flag. Finally, the template string has access to variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `<extra>` is displayed in the secondary box, for example `<extra>%{fullData.name}</extra>`. To hide the secondary box completely, use an empty tag `<extra></extra>`.",
      "dflt": "",
      "editType": "plot",
      "valType": "string"

commands.py

@@ -296,8 +296,8 @@ def update_plotlyjs_dev(args, outdir):
     perform_codegen(outdir)
 
 
-def parse_args():
-    """Parse command-line arguments."""
+def make_parser():
+    """Make argument parser."""
 
     parser = argparse.ArgumentParser()
     subparsers = parser.add_subparsers(dest="cmd", help="Available subcommands")
@@ -322,6 +322,11 @@ def parse_args():
 
     subparsers.add_parser("updateplotlyjs", help="update plotly.js")
 
+    return parser
+
+
+def parse_args(parser: argparse.ArgumentParser):
+    """Parse command line arguments."""
     return parser.parse_args()
 
 
@@ -331,7 +336,8 @@ def main():
     project_root = os.path.dirname(os.path.realpath(__file__))
     outdir = os.path.join(project_root, "plotly")
 
-    args = parse_args()
+    parser = make_parser()
+    args = parse_args(parser)
 
     if args.cmd == "codegen":
         perform_codegen(outdir, noformat=args.noformat)
@@ -350,6 +356,10 @@ def main():
         print(version)
         update_plotlyjs(version, outdir)
 
+    elif args.cmd is None:
+        parser.print_help()
+        sys.exit(1)
+
     else:
         print(f"unknown command {args.cmd}", file=sys.stderr)
         sys.exit(1)

doc/python/3d-mesh.md

@@ -154,6 +154,8 @@ Whereas the previous example used the default `intensitymode='vertex'`, we plot
 
 ```python
 import plotly.graph_objects as go
+import numpy as np
+
 fig = go.Figure(data=[
     go.Mesh3d(
         # 8 vertices of a cube

doc/python/axes.md

@@ -118,7 +118,7 @@ The PX `labels` argument can also be used without a data frame argument:
 
 ```python
 import plotly.express as px
-fig = px.bar(df, x=["Apples", "Oranges"], y=[10,20], color=["Here", "There"],
+fig = px.bar(x=["Apples", "Oranges"], y=[10,20], color=["Here", "There"],
     labels=dict(x="Fruit", y="Amount", color="Place")
 )
 fig.show()
@@ -460,6 +460,7 @@ Here, `ticklabelstandoff=15` moves the labels 15 pixels further away from the x-
 
 ```python
 import plotly.express as px
+import pandas as pd
 
 df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
 
@@ -487,6 +488,7 @@ To draw the label for the minor tick before each major tick, set `ticklabelindex
 
 ```python
 import plotly.express as px
+import pandas as pd
 
 df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
 

doc/python/box-plots.md

@@ -448,6 +448,7 @@ fig.show()
 
 ```python
 import plotly.graph_objects as go
+import numpy as np
 
 x_data = ['Carmelo Anthony', 'Dwyane Wade',
           'Deron Williams', 'Brook Lopez',

doc/python/creating-and-updating-figures.md

@@ -206,6 +206,7 @@ fig.show()
 The `plotly.subplots.make_subplots()` function produces a graph object figure that is preconfigured with a grid of subplots that traces can be added to. The `add_trace()` function will be discussed more below.
 
 ```python
+import plotly.graph_objects as go
 from plotly.subplots import make_subplots
 
 fig = make_subplots(rows=1, cols=2)
@@ -260,6 +261,7 @@ fig.show()
 If a figure was created using `plotly.subplots.make_subplots()`, then supplying the `row` and `col` arguments to `add_trace()` can be used to add a trace to a particular subplot.
 
 ```python
+import plotly.graph_objects as go
 from plotly.subplots import make_subplots
 
 fig = make_subplots(rows=1, cols=2)
@@ -274,6 +276,7 @@ This also works for figures created by Plotly Express using the `facet_row` and
 
 ```python
 import plotly.express as px
+import plotly.graph_objects as go
 
 df = px.data.iris()
 

doc/python/imshow.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: 3.12.0
   plotly:
     description: How to display image data in Python with Plotly.
     display_as: scientific
@@ -61,7 +61,7 @@ In order to create a numerical array to be passed to `px.imshow`, you can use a
 ```python
 import plotly.express as px
 from skimage import io
-img = io.imread('https://upload.wikimedia.org/wikipedia/commons/thumb/0/00/Crab_Nebula.jpg/240px-Crab_Nebula.jpg')
+img = io.imread('https://user-images.githubusercontent.com/72614349/179115668-2630e3e4-3a9f-4c88-9494-3412e606450a.jpg')
 fig = px.imshow(img)
 fig.show()
 ```
@@ -274,6 +274,7 @@ fig.show()
 ### Displaying an image and the histogram of color values
 
 ```python
+import plotly.graph_objects as go
 from plotly.subplots import make_subplots
 from skimage import data
 img = data.chelsea()