Merge pull request #16 from eth-cscs/release-0.2.1

Release 0.2.1

.travis.yml

@@ -1,22 +1,32 @@
 dist: trusty
-
 language: python
-
 python:
-  - "3.5"
-
+- '3.5'
 addons:
   apt:
     packages:
-      - gfortran
-      - libboost-random-dev
-      - libpython3.4-dev
-      - python3-numpy
-      - swig
-
+    - gfortran
+    - libboost-random-dev
+    - libpython3.4-dev
+    - python3-numpy
+    - swig
 install:
-  - pip install -r requirements.txt
-
+- pip install -r requirements.txt
 script:
-  - make test
-
+- make test
+deploy:
+- provider: pypi
+  server: https://pypi.python.org/pypi
+  user: mschoengens
+  password:
+    secure: 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
+  distributions: "sdist bdist_wheel"
+  on:
+    tags: true
+    branch: master
+- provider: releases
+  api_key: $GITHUB_OAUTH_TOKEN
+  skip_cleanup: true
+  on:
+    tags: true
+    branch: master

Makefile

@@ -1,6 +1,7 @@
-whl_file = abcpy-0.1-py3-none-any.whl
+VERSION=$(shell cat VERSION)
 UNITTESTS=$(shell find tests -type f -name '*_tests.py')
 MAKEDIRS=$(shell find examples -name Makefile -exec dirname {} \;)
+whl_file = abcpy-${VERSION}-py3-none-any.whl
 
 .DEFAULT: help
 .PHONY: help clean doc doctest exampletest package test uninstall unittest install reinstall $(MAKEDIRS)

README.md

@@ -25,10 +25,12 @@ You are very welcome to contribute to ABCpy.
 
 If you want to contribute code, there are a few things to consider:
 * a good start is to fork the repository
+* know our [branching strategy](http://nvie.com/posts/a-successful-git-branching-model/)
 * use GitHub pull requests to merge your contribution
 * consider documenting your code according to the [NumPy documentation style guide](https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt)
 * consider writing reasonable [unit tests](https://docs.python.org/3.5/library/unittest.html)
 
+
 In case of any questions, feel free to contact one of us:
 * Ritabrata Dutta, University of Lugano
 * Marcel Schoengens, CSCS, ETH Zurich

VERSION

@@ -1 +1 @@
-0.2
+0.2.1

setup.cfg

@@ -0,0 +1,4 @@
+# PyPI config file
+
+[metadata]
+description-file = README.md

setup.py

@@ -1,17 +1,17 @@
 # Always prefer setuptools over distutils
 from setuptools import setup, find_packages
+from pip.req import parse_requirements
+from pip.download import PipSession
 from os import path
-here = path.abspath(path.dirname(__file__))
 
-# Get the long description from the README file
-with open(path.join(here, 'README.md'), encoding='utf-8') as f:
-    long_description = f.read()
+here = path.abspath(path.dirname(__file__))
 
-with open(path.join(here, 'requirements.txt')) as f:
-    dependencies = f.readlines()
+install_reqs_raw = parse_requirements('requirements.txt', session=PipSession())
+install_reqs = [str(ir.req) for ir in install_reqs_raw]
 
 with open(path.join(here, 'VERSION')) as f:
-    version = f.read()
+    version = f.readline().strip()
+    file_tgz = 'v' + version + '.tar.gz'
 
 setup(
     name='abcpy',
@@ -21,18 +21,19 @@
     # https://packaging.python.org/en/latest/single_source_version.html
     version=version,
 
-    description='An framework for parallel approximate bayesian computation.',
-    long_description=long_description,
+    description='A framework for approximate Bayesian computation (ABC) that speeds up inference by parallelizing computation on single computers or whole clusters.',
+    long_description='ABCpy is a highly modular, scientific library for approximate Bayesian computation (ABC) written in Python using the parallel computation framework Apache SPARK. The modularity helps domain scientists to easily apply ABC to their research without being ABC experts; using ABCpy they can easily run large parallel simulations without much knowledge about parallelization, even without much additional effort to parallelize their code. Further, ABCpy enables ABC experts to easily develop new inference schemes and evaluate them in a standardized environment, and to extend the library with new algorithms. These benefits come mainly from the modularity of ABCpy.',
 
     # The project's main homepage.
-    url='https://bitbucket.org/statrita/abcpy',
-
+    url='https://github.com/eth-cscs/abcpy',
+    download_url = 'https://github.com/eth-cscs/abcpy/archive/' + file_tgz,
+
     # Author details
     author='The abcpy authors',
     author_email='',
 
     # Choose your license
-    license='GPL',
+    license='BSD-3',
 
     # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
     classifiers=[
@@ -43,7 +44,6 @@
         'Development Status :: 4 - Beta',
 
         'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.3',
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
     ],
@@ -64,7 +64,7 @@
     # requirements files see:
     # https://packaging.python.org/en/latest/requirements.html
     # install_requires=['numpy', 'scipy'],
-    # install_requires=dependencies,
+    install_requires=install_reqs,
 
 
     # List additional groups of dependencies here (e.g. development