Start building Wheels alongside sdist

CONTRIBUTING.rst

@@ -119,13 +119,13 @@ Ready to publish a new version to PyPi? Here's how the workflow to follow.
     (pyLDAvis) $ tox
 
     -- TestPyPi
-    (pyLDAvis) $ python setup.py sdist
+    (pyLDAvis) $ python setup.py sdist bdist_wheel
     (pyLDAvis) $ twine check dist/*
     (pyLDAvis) $ twine upload --repository testpypi dist/*
 
     -- Publish
     (pyLDAvis) $ twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
-    (pyLDAvis) $ rm dist/*.tar.gz
+    (pyLDAvis) $ rm dist/*
 
 Note: MacOS Big Sur is both 10.16 and 11.0 – it’s official (https://eclecticlight.co/2020/07/21/big-sur-is-both-10-16-and-11-0-its-official/) ::
 

Pipfile

@@ -10,7 +10,6 @@ scipy = "*"
 pandas = "*"
 joblib = "*"
 numexpr = "*"
-future = "*"
 funcy = "*"
 sklearn = "*"
 scikit-learn = "*"

notebooks/sklearn.ipynb

@@ -9,15 +9,6 @@
     "pyLDAvis now also supports LDA application from scikit-learn. Let's take a look into this in more detail. We will be using the 20 newsgroups dataset as provided by scikit-learn."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from __future__ import print_function"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -1057,7 +1048,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.9.2"
   }
  },
  "nbformat": 4,

pyLDAvis/_prepare.py

@@ -4,7 +4,6 @@
 Main transformation functions for preparing LDAdata to the visualization's data structures
 """
 
-from past.builtins import basestring
 from collections import namedtuple
 import json
 import logging
@@ -382,7 +381,7 @@ def prepare(topic_term_dists, doc_topic_dists, doc_lengths, vocab, term_frequenc
         plot_opts = {'xlab': 'PC1', 'ylab': 'PC2'}
 
     # parse mds
-    if isinstance(mds, basestring):
+    if isinstance(mds, str):
         mds = mds.lower()
         if mds == 'pcoa':
             mds = js_PCoA

requirements.txt

@@ -4,7 +4,6 @@ pandas>=1.2.0
 joblib
 jinja2
 numexpr
-future
 funcy
 sklearn
 scikit-learn

setup.py

@@ -24,10 +24,11 @@
     author='Ben Mabey',
     author_email='ben@benmabey.com',
     url='https://github.com/bmabey/pyLDAvis',
-    download_url = 'https://github.com/bmabey/pyLDAvis/tarball/3.3.1',
+    download_url='https://github.com/bmabey/pyLDAvis/tarball/3.3.1',
     packages=['pyLDAvis'],
     package_dir={'pyLDAvis': 'pyLDAvis'},
     tests_require=['pytest'],
+    python_requires=">=3.7",
     include_package_data=True,
     install_requires=requirements,
     license='MIT',