Merge pull request #18 from edx/vik/make-package

Vik/make package

.gitignore

@@ -5,3 +5,8 @@ models/
 *~
 tests/
 _build/
+build/
+dist/
+machine_learning.egg-info/
+*.egg
+

apt-packages.txt

 python-pip
-python-scipy
-python-mysqldb
-ipython
-nginx
-git
-redis-server
-libmysqlclient-dev
 gfortran
 libblas3gf
 libblas-dev
@@ -14,9 +7,5 @@ liblapack-dev
 libatlas-base-dev
 libxml2-dev
 libxslt1-dev
-libreadline6
-libreadline6-dev
-build-essential
-curl
 aspell
 python
\ No newline at end of file

docs/installation/installation_overview.rst

@@ -11,5 +11,6 @@ Notes on how to install:
 5. Activate your virtual env (if you have one)
 6. pip install -r pre-requirements.txt
 7. pip install -r requirements.txt
-8. python -m nltk.downloader maxent_treebank_pos_tagger wordnet
-9. sudo mv /path/to/nltk_data /usr/share
+8. python setup.py install
+9. python -m nltk.downloader maxent_treebank_pos_tagger wordnet
+10. sudo mv /path/to/nltk_data /usr/share

full_requirements.txt

+-r pre-requirements.txt
+-r requirements.txt
\ No newline at end of file

create.py → machine_learning/create.py

@@ -11,7 +11,7 @@ import numpy
 #Define base path and add to sys path
 base_path = os.path.dirname(__file__)
 sys.path.append(base_path)
-one_up_path = os.path.abspath(os.path.join(os.path.dirname(__file__),'..'))
+one_up_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..//'))
 sys.path.append(one_up_path)
 
 #Import modules that are dependent on the base path

machine_learning/external_code/fisher/__init__.py

+__author__ = 'vik'

requirements.txt

@@ -11,3 +11,5 @@ pip
 pylint==0.26.0
 pytz==2012h
 scikit-learn==0.12.1
+sphinx
+django-sphinx-autodoc

setup.py

+from setuptools import setup, find_packages
+
+with open('requirements.txt') as f:
+    required = f.read().splitlines()
+
+setup(
+    name = "machine-learning",
+    version = "0.1",
+    packages=['machine_learning', 'machine_learning.external_code', 'machine_learning.data', 'machine_learning.external_code.fisher'],
+    package_data = {
+        '': ['*.txt', '*.rst', '*.p'],
+        },
+    author = "Vik Paruchuri",
+    author_email = "vik@edx.org",
+    description = "Machine learning based automated text classification for essay scoring.",
+    license = "AGPL",
+    keywords = "ml machine learning nlp essay education",
+    url = "https://github.com/edx/machine-learning",
+    include_package_data = True,
+    )
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