small README update

README.md

@@ -4,7 +4,7 @@ sparklanes
 [![PyPI version](https://badge.fury.io/py/sparklanes.svg)](https://badge.fury.io/py/sparklanes)
 [![Build Status](https://travis-ci.org/ksbg/sparklanes.svg?branch=master)](https://travis-ci.org/ksbg/sparklanes?branch=master)
 [![Coverage Status](https://coveralls.io/repos/github/ksbg/sparklanes/badge.svg?branch=master)](https://coveralls.io/github/ksbg/sparklanes?branch=master)
-[![Doc status](https://sparklanes.readthedocs.io/en/latest/?badge=latest)](https://sparklanes.readthedocs.io)
+[![Doc status](https://readthedocs.org/projects/sparklanes/badge/?version=latest)](https://sparklanes.readthedocs.io)
 ![pylint Score](https://mperlet.github.io/pybadge/badges/9.88.svg)
 ![license](https://img.shields.io/github/license/ksbg/sparklanes.svg)
 
@@ -25,7 +25,31 @@ to then be packaged and submitted to spark using a single command.
 Alternatively, the same can be achieved manually by using the framework's
 API.
 
-Documentation
--------------
+Usage
+-----
 
-Find the documentation on [sparklanes.readthedocs.io](https://sparklanes.readthedocs.io)
+Check out the documentation at
+[sparklanes.readthedocs.io](https://sparklanes.readthedocs.io), as well
+as the [example Jupyter notebook](example/iris_example.ipynb)
+
+Installation
+------------
+
+Using pip:
+
+    pip install sparklanes
+
+Tests & Docs
+------------
+
+Install the development requirements:
+
+    pip install -r requirements-dev.txt
+
+Run the test suite from the project root using:
+
+    python -m tests
+
+Build the documentation:
+
+    cd docs && make html

setup.py

@@ -1,9 +1,6 @@
 import os
 from setuptools import setup
 
-with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'README.md')) as readme_file:
-    long_description = readme_file.read()
-
 setup(
     name='sparklanes',
     version='0.2.1',
@@ -15,7 +12,21 @@
     author_email='kevin@ksbg.io',
     description='A lightweight framework to build and execute data processing pipelines in pyspark '
                 '(Apache Spark\'s python API)',
-    long_description=long_description,
+    long_description='sparklanes is a lightweight data processing framework for Apache Spark'
+                     'written in Python. It was built with the intention to make building'
+                     'complex spark processing pipelines simpler, by shifting the focus'
+                     'towards writing data processing code without having to spent much time'
+                     'on the surrounding application architecture.'
+                     '\n'
+                     'Data processing pipelines, or *lanes*, are built by stringing together'
+                     'encapsulated processor classes, which allows creation of lane definitions'
+                     'with an arbitrary processor order, where processors can be easily'
+                     'removed, added or swapped.'
+                     '\n'
+                     'Processing pipelines can be defined using *lane configuration YAML files*,'
+                     'to then be packaged and submitted to spark using a single command.'
+                     'Alternatively, the same can be achieved manually by using the framework'
+                     'API.',
     long_description_content_type='text/markdown',
     packages=['sparklanes', 'sparklanes._submit', 'sparklanes._framework'],
     install_requires=[