Merge branch 'master' into doc-prod-v5.18.0

Author: LiamConnors

CHANGELOG.md

@@ -2,6 +2,21 @@
 All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
+## [5.18.0] - 2023-10-25
+
+### Updated
+- Updated Plotly.js from version 2.26.0 to version 2.27.0. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2270----2023-10-20) for more information. These changes are reflected in the auto-generated `plotly.graph_objects` module. Notable changes include:
+  - Add `insiderange` to cartesian axes to help avoid overlap between visible grid lines and tick labels of the counter axis when they are positioned inside [[#6735](https://github.com/plotly/plotly.js/pull/6735)], this feature was anonymously sponsored: thank you to our sponsor!
+  - Fix column order changes on hover [[#6718](https://github.com/plotly/plotly.js/pull/6718)],
+   with thanks to @bhavinpatel1109 for the contribution!
+  - Fix hover at timestamp '1970-01-01 00:00:00' [[#6752](https://github.com/plotly/plotly.js/pull/6752)],
+   with thanks to @adamjhawley for the contribution!
+  - Fix clearing empty `candlestick` using react [[#6757](https://github.com/plotly/plotly.js/pull/6757)]
+
+### Fixed
+- Repair crash on Matplotlib 3.8 related to get_offset_position [[#4372](https://github.com/plotly/plotly.py/pull/4372)],
+- Handle deprecation of `pandas.Series.dt.to_pydatetime()` calls and suppress the `FutureWarning` they currently emit. [[#4379](https://github.com/plotly/plotly.py/pull/4379)]
+
 ## [5.17.0] - 2023-09-15
 
 ### Updated

README.md

@@ -33,7 +33,7 @@
 
 ## Quickstart
 
-`pip install plotly==5.17.0`
+`pip install plotly==5.18.0`
 
 Inside [Jupyter](https://jupyter.org/install) (installable with `pip install "jupyterlab>=3" "ipywidgets>=7.6"`):
 
@@ -78,13 +78,13 @@ Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is
 plotly.py may be installed using pip...
 
 ```
-pip install plotly==5.17.0
+pip install plotly==5.18.0
 ```
 
 or conda.
 
 ```
-conda install -c plotly plotly=5.17.0
+conda install -c plotly plotly=5.18.0
 ```
 
 ### JupyterLab Support
@@ -106,7 +106,7 @@ The instructions above apply to JupyterLab 3.x. **For JupyterLab 2 or earlier**,
 
 ```
 # JupyterLab 2.x renderer support
-jupyter labextension install jupyterlab-plotly@5.17.0 @jupyter-widgets/jupyterlab-manager
+jupyter labextension install jupyterlab-plotly@5.18.0 @jupyter-widgets/jupyterlab-manager
 ```
 
 Please check out our [Troubleshooting guide](https://plotly.com/python/troubleshooting/) if you run into any problems with JupyterLab.

contributing.md

@@ -271,11 +271,11 @@ pytest plotly/tests/test_plotly/test_plot.py::test_function
 
 Running tests with tox is much more powerful, but requires a bit more setup.
 
-You'll need to export an environment variable for *each* tox environment you wish to test with. For example, if you want to test with `Python 2.7` and
+You'll need to export an environment variable for *each* tox environment you wish to test with. For example, if you want to test with `Python 3.9` and
 `Python 3.6`, but only care to check the `core` specs, you would need to ensure that the following variables are exported:
 
 ```
-export PLOTLY_TOX_PYTHON_27=<python binary>
+export PLOTLY_TOX_PYTHON_39=<python binary>
 export PLOTLY_TOX_PYTHON_36=<python binary>
 ```
 
@@ -286,15 +286,15 @@ Where the `<python binary` is going to be specific to your development setup. As
 # tox envs #
 ############
 
-export PLOTLY_TOX_PYTHON_27=python2.7
-export PLOTLY_TOX_PYTHON_34=python3.4
-export TOXENV=py27-core,py34-core
+export PLOTLY_TOX_PYTHON_39=python3.9
+export PLOTLY_TOX_PYTHON_36=python3.6
+export TOXENV=py39-core,py36-core
 ```
 
 Where `TOXENV` is the environment list you want to use when invoking `tox` from the command line. Note that the `PLOTLY_TOX_*` pattern is used to pass in variables for use in the `tox.ini` file. Though this is a little setup, intensive, you'll get the following benefits:
 
 * `tox` will automatically manage a virtual env for each environment you want to test in.
-* You only have to run `tox` and know that the module is working in both `Python 2` and `Python 3`.
+* You only have to run `tox` and know that the module is working in all included Python versions.
 
 Finally, `tox` allows you to pass in additional command line arguments that are formatted in (by us) in the `tox.ini` file, see `{posargs}`. This is setup to help with our configuration of [pytest markers](http://doc.pytest.org/en/latest/example/markers.html), which are set up in `packages/python/plotly/pytest.ini`. To run only tests that are *not* tagged with `nodev`, you could use the following command:
 

doc/apidoc/conf.py

@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-#
 # Configuration file for the Sphinx documentation builder.
 #
 # This file does only contain a selection of the most common options. For a

doc/python/axes.md

@@ -559,6 +559,25 @@ fig.update_yaxes(range=[3, 9])
 fig.show()
 ```
 
+#### Exclude Inside Tick Labels from Range
+
+*New in 5.18*
+
+You can use `insiderange` instead of `range` on an axis if you have tick labels positioned on the inside of another axis and you don't want the range to overlap with those labels.
+
+In this example, we have a y axis with `ticklabelposition="inside"` and by setting `insiderange=['2018-10-01', '2019-01-01']` on the x axis, the data point of `2018-10-01` is displayed after the y axis labels.
+
+```python
+import plotly.express as px
+df = px.data.stocks(indexed=True)
+
+fig = px.line(df, df.index, y="GOOG")
+fig.update_yaxes(ticklabelposition="inside", title="Price")
+fig.update_xaxes(insiderange=['2018-10-01', '2019-01-01'], title="Date")
+
+fig.show()
+```
+
 #### Setting only a Lower or Upper Bound for Range
 
 *New in 5.17*

doc/unconverted/python/amazon-redshift.md

@@ -45,8 +45,6 @@ This notebook will go over one of the easiest ways to graph data from your [Amaz
 In this notebook we'll be using [Amazon's Sample Redshift Data](http://docs.aws.amazon.com/redshift/latest/gsg/rs-gsg-create-sample-db.html) for this notebook. Although we won't be connecting through a JDBC/ODBC connection we'll be using the [psycopg2 package](http://initd.org/psycopg/docs/index.html) with [SQLAlchemy](http://www.sqlalchemy.org/)  and [pandas](http://pandas.pydata.org/) to make it simple to query and analyze our data.
 
 ```python
-from __future__ import print_function #python 3 support
-
 import plotly.plotly as py
 import plotly.graph_objs as go
 import plotly.tools as tls

doc/unconverted/python/apache-spark.md

@@ -122,7 +122,6 @@ We can test for the Spark Context's existence with `print sc`.
 <!-- #endregion -->
 
 ```python
-from __future__ import print_function #python 3 support
 print(sc)
 ```
 

packages/javascript/jupyterlab-plotly/package-lock.json

@@ -1,6 +1,6 @@
 {
   "name": "jupyterlab-plotly",
-  "version": "5.17.0",
+  "version": "5.18.0",
   "description": "The plotly Jupyter extension",
   "author": "The plotly.py team",
   "license": "MIT",
@@ -65,7 +65,7 @@
     "@lumino/messaging": "^1.2.3",
     "@lumino/widgets": "^1.8.1",
     "lodash": "^4.17.4",
-    "plotly.js": "^2.26.0"
+    "plotly.js": "^2.27.0"
   },
   "jupyterlab": {
     "extension": "lib/jupyterlab-plugin",

packages/javascript/jupyterlab-plotly/package.json

@@ -1,5 +1,3 @@
-from __future__ import absolute_import
-
 import base64
 import numbers
 import textwrap
@@ -9,6 +7,7 @@
 import io
 import re
 import sys
+import warnings
 
 from _plotly_utils.optional_imports import get_module
 
@@ -102,7 +101,11 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
         elif v.dtype.kind == "M":
             # Convert datetime Series/Index to numpy array of datetimes
             if isinstance(v, pd.Series):
-                v = v.dt.to_pydatetime()
+                with warnings.catch_warnings():
+                    warnings.simplefilter("ignore", FutureWarning)
+                    # Series.dt.to_pydatetime will return Index[object]
+                    # https://github.com/pandas-dev/pandas/pull/52459
+                    v = np.array(v.dt.to_pydatetime())
             else:
                 # DatetimeIndex
                 v = v.to_pydatetime()
@@ -111,7 +114,13 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
         if dtype.kind in numeric_kinds:
             v = v.values
         elif dtype.kind == "M":
-            v = [row.dt.to_pydatetime().tolist() for i, row in v.iterrows()]
+            with warnings.catch_warnings():
+                warnings.simplefilter("ignore", FutureWarning)
+                # Series.dt.to_pydatetime will return Index[object]
+                # https://github.com/pandas-dev/pandas/pull/52459
+                v = [
+                    np.array(row.dt.to_pydatetime()).tolist() for i, row in v.iterrows()
+                ]
 
     if not isinstance(v, np.ndarray):
         # v has its own logic on how to convert itself into a numpy array
@@ -146,7 +155,7 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
     # --------------------------
     if force_numeric and new_v.dtype.kind not in numeric_kinds:
         raise ValueError(
-            "Input value is not numeric and" "force_numeric parameter set to True"
+            "Input value is not numeric and force_numeric parameter set to True"
         )
 
     if "U" not in kind: