plotly · bmaranville · Mar 25, 2025 · Mar 25, 2025 · Mar 25, 2025 · Mar 25, 2025
diff --git a/doc/python/getting-started.md b/doc/python/getting-started.md
@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.1
+      jupytext_version: 1.16.4
   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: 3.11.10
   plotly:
     description: Getting Started with Plotly for Python.
     has_thumbnail: false
@@ -41,7 +41,7 @@ The [`plotly` Python library](/python/) is an interactive, [open-source](/python
 
 Built on top of the Plotly JavaScript library ([plotly.js](https://plotly.com/javascript/)), `plotly` enables Python users to create beautiful interactive web-based visualizations that can be displayed in Jupyter notebooks, saved to standalone HTML files, or served as part of pure Python-built web applications using Dash. The `plotly` Python library is sometimes referred to as "plotly.py" to differentiate it from the JavaScript library.
 
-Thanks to deep integration with our [Kaleido](https://medium.com/plotly/introducing-kaleido-b03c4b7b1d81) image export utility, `plotly` also provides great support for non-web contexts including desktop editors (e.g. QtConsole, Spyder, PyCharm) and static document publishing (e.g. exporting notebooks to PDF with high-quality vector images).
+Thanks to deep integration with our [Kaleido](https://github.com/plotly/Kaleido) image export utility, `plotly` also provides great support for non-web contexts including desktop editors (e.g. QtConsole, Spyder, PyCharm) and static document publishing (e.g. exporting notebooks to PDF with high-quality vector images).
 
 This Getting Started guide explains how to install `plotly` and related optional pages. Once you've installed, you can use our documentation in three main ways:
 
@@ -183,17 +183,15 @@ See [_Displaying Figures in Python_](/python/renderers/) for more information on
 ### Static Image Export
 
 plotly.py supports [static image export](https://plotly.com/python/static-image-export/),
-using the either the [`kaleido`](https://github.com/plotly/Kaleido)
-package (recommended, supported as of `plotly` version 4.9) or the [orca](https://github.com/plotly/orca)
-command line utility (legacy as of `plotly` version 4.9).
+using the [`kaleido`](https://github.com/plotly/Kaleido) package. (Support for the legacy [`orca`](https://github.com/plotly/orca) image export utility is deprecated and will be removed after September 2025.)
 
 #### Kaleido
 
 The [`kaleido`](https://github.com/plotly/Kaleido) package has no dependencies and can be installed
 using pip...
 
 ```
-$ pip install -U kaleido
+$ pip install --upgrade kaleido
 ```
 
 or conda.
@@ -202,28 +200,6 @@ or conda.
 $ conda install -c plotly python-kaleido
 ```
 
-#### Orca
-
-While Kaleido is now the recommended image export approach because it is easier to install
-and more widely compatible, [static image export](https://plotly.com/python/static-image-export/)
-can also be supported
-by the legacy [orca](https://github.com/plotly/orca) command line utility and the
- [`psutil`](https://github.com/giampaolo/psutil) Python package.
-
-These dependencies can both be installed using conda:
-
-```
-conda install -c plotly plotly-orca==1.3.1 psutil
-```
-
-Or, `psutil` can be installed using pip...
-
-```
-pip install psutil
-```
-
-and orca can be installed according to the instructions in the [orca README](https://github.com/plotly/orca).
-
 #### Extended Geo Support
 
 Some plotly.py features rely on fairly large geographic shape files. The county

diff --git a/doc/python/orca-management.md b/doc/python/orca-management.md
@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.1'
-      jupytext_version: 1.1.6
+      format_version: '1.3'
+      jupytext_version: 1.16.4
   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: 3.7.3
+    version: 3.11.10
   plotly:
     description: This section covers the low-level details of how plotly.py uses orca
       to perform static image generation.
@@ -33,11 +33,11 @@ jupyter:
     thumbnail: thumbnail/orca-management.png
 ---
 
+> Orca support in Plotly.py is deprecated and will be removed after September 2025. See the [Static Image Export page](/python/static-image-export/) for details on using Kaleido for static image generation.
+
 ### Overview
 This section covers the lower-level details of how plotly.py can use orca to perform static image generation.
 
-> As of `plotly` version 4.9, Orca is no longer the recommended way to do static image export.  We now recommend Kaleido, as described in the [Static Image Export](/python/static-image-export/) section .
-
 Please refer to the [Static Image Export](/python/static-image-export/) section for general information on creating static images from plotly.py figures.
 
 ### What is orca?
@@ -50,26 +50,26 @@ There are 3 general approaches to installing orca and its Python dependencies.
 
 ##### conda
 Using the [conda](https://conda.io/docs/) package manager, you can install these dependencies in a single command:
-```
+<!-- #raw -->
 $ conda install -c plotly plotly-orca==1.2.1 psutil requests
-```
+<!-- #endraw -->
 
 **Note:** Even if you do not want to use conda to manage your Python dependencies, it is still useful as a cross platform tool for managing native libraries and command-line utilities (e.g. git, wget, graphviz, boost, gcc, nodejs, cairo, etc.).  For this use-case, start with [Miniconda](https://conda.io/miniconda.html) (~60MB) and tell the installer to add itself to your system `PATH`.  Then run `conda install plotly-orca==1.2.1` and the orca executable will be available system wide.
 
 ##### npm + pip
 You can use the [npm](https://www.npmjs.com/get-npm) package manager to install `orca` (and its `electron` dependency), and then use pip to install `psutil`:
 
-```
+<!-- #raw -->
 $ npm install -g electron@1.8.4 orca
 $ pip install psutil requests
-```
+<!-- #endraw -->
 
 ##### Standalone Binaries + pip
 If you are unable to install conda or npm, you can install orca as a precompiled binary for your operating system. Follow the instructions in the orca [README](https://github.com/plotly/orca) to install orca and add it to your system `PATH`. Then use pip to install `psutil`.
 
-```
+<!-- #raw -->
 $ pip install psutil requests
-```
+<!-- #endraw -->
 
 <!-- #region -->
 ### Install orca on Google Colab
@@ -263,4 +263,4 @@ In addition to the `executable` property, the `plotly.io.orca.config` object can
 
 
 ### Saving Configuration Settings
-Configuration options can optionally be saved to the `~/.plotly/` directory by calling the `plotly.io.config.save()` method.  Saved setting will be automatically loaded at the start of future sessions.
+Configuration options can optionally be saved to the `~/.plotly/` directory by calling the `plotly.io.config.save()` method.  Saved setting will be automatically loaded at the start of future sessions.