Merge pull request #4357 from plotly/no-universal

remove py2 from build

Author: alexcjohnson

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/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/python/plotly/_plotly_utils/basevalidators.py

@@ -1,5 +1,3 @@
-from __future__ import absolute_import
-
 import base64
 import numbers
 import textwrap
@@ -146,7 +144,7 @@ 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:

packages/python/plotly/_plotly_utils/colors/__init__.py

@@ -73,8 +73,6 @@
 Be careful! If you have a lot of unique numbers in your color column you will
 end up with a colormap that is massive and may slow down graphing performance.
 """
-from __future__ import absolute_import
-
 import decimal
 from numbers import Number
 

packages/python/plotly/_plotly_utils/optional_imports.py

@@ -2,8 +2,6 @@
 Stand-alone module to provide information about whether optional deps exist.
 
 """
-from __future__ import absolute_import
-
 from importlib import import_module
 import logging
 import sys
@@ -30,7 +28,7 @@ def get_module(name, should_load=True):
             return import_module(name)
         except ImportError:
             _not_importable.add(name)
-        except Exception as e:
+        except Exception:
             _not_importable.add(name)
             msg = f"Error importing optional module {name}"
             logger.exception(msg)

packages/python/plotly/_plotly_utils/utils.py

@@ -8,9 +8,6 @@
 from _plotly_utils.basevalidators import ImageUriValidator
 
 
-PY36_OR_LATER = sys.version_info >= (3, 6)
-
-
 def cumsum(x):
     """
     Custom cumsum to avoid a numpy import.

packages/python/plotly/plotly/__init__.py

@@ -25,7 +25,6 @@
 - exceptions: defines our custom exception classes
 
 """
-from __future__ import absolute_import
 import sys
 from typing import TYPE_CHECKING
 from _plotly_utils.importers import relative_import

packages/python/plotly/plotly/_subplots.py

@@ -1,6 +1,3 @@
-# -*- coding: utf-8 -*-
-from __future__ import absolute_import, unicode_literals
-
 # Constants
 # ---------
 # Subplot types that are each individually positioned with a domain