version 1.2.2

Author: Daniel Nyga

Diff for: _version/__init__.py

@@ -20,7 +20,7 @@
 
 VERSION_MAJOR = 1
 VERSION_MINOR = 2
-VERSION_PATCH = 1
+VERSION_PATCH = 2
 
 VERSION_STRING_FULL = '%s.%s.%s' % (VERSION_MAJOR, VERSION_MINOR, VERSION_PATCH)
 VERSION_STRING_SHORT = '%s.%s' % (VERSION_MAJOR, VERSION_MINOR)

Diff for: doc/source/conf.py

@@ -14,6 +14,9 @@
 import sys
 import os
 import datetime
+import pip
+pip.main(['install', 'sphinx', 'sphinx_bootstrap_theme', 'sphinxcontrib-bibtex'])
+
 import sphinx_bootstrap_theme
 
 # If extensions (or modules to document with autodoc) are in another directory,
@@ -24,6 +27,7 @@
 sys.path.insert(0, os.path.abspath('../..'))
 import _version
 
+
 sys.path.insert(0, os.path.abspath(os.path.join('..', '..',  _version.__basedir__)))
 
 print('using', _version.__basedir__)

Diff for: doc/source/index.rst

@@ -42,7 +42,7 @@ your own scripts, see :doc:`apidoc`.
 Release notes
 ^^^^^^^^^^^^^
 
-  * Release 1.2.1 (18.12.2017)
+  * Release 1.2.2 (18.12.2017)
 
     * Support for Python 2 and Python 3
     * Release a ``pip``-compliant package

Diff for: setup.py

@@ -51,6 +51,13 @@ def datapath():
         return appdirs.user_data_dir(appname, appauthor)
 
 
+def description():
+    try:
+        with open('README.md') as f:
+            return f.read()
+    except:
+        return 'Markov logic networks in Python. Please visit http://www.pracmln.org'
+
 class myinstall(distutils.command.install.install):
 
     def __init__(self, *args, **kwargs):
@@ -70,9 +77,10 @@ def __init__(self, *args, **kwargs):
     data_files=datafiles('examples') + datafiles('3rdparty') + datafiles('libpracmln') + datafiles('etc'),
     version=__version__,
     description='Markov logic networks in Python',
+    long_description=description(),
     author='Daniel Nyga',
     author_email='[email protected]',
-    url='https://pracmln.org',
+    url='http://www.pracmln.org',
     download_url='https://github.com/danielnyga/pracmln/archive/%s.tar.gz' % __version__,
     keywords=['statistical relational learning', 'mln', 'Markov logic networks', 'reasoning', 'probcog'],
     classifiers=[