Add release version 1.0

Author: joowani

.gitignore

@@ -87,3 +87,4 @@ ENV/
 
 # Rope project settings
 .ropeproject
+.idea*

.travis.yml

@@ -0,0 +1,16 @@
+language: python
+sudo: false
+python:
+    - 2.7
+    - 3.4
+    - 3.5
+install:
+    - pip install coverage
+    - pip install pytest
+    - pip install pytest-cov
+    - pip install python-coveralls
+    - python setup.py install
+script:
+    - py.test --cov-report= --cov=binarytree tests.py
+after_success:
+    - coveralls

README.md

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+BinaryTree: Python Library for Learning Binary Trees
+----------------------------------------------------
+
+.. image:: https://travis-ci.org/joowani/binarytree.svg?branch=master
+    :target: https://travis-ci.org/joowani/binarytree
+    :alt: Build Status
+
+.. image:: https://badge.fury.io/py/binarytree.svg
+    :target: https://badge.fury.io/py/binarytree
+    :alt: Package Version
+
+.. image:: https://img.shields.io/badge/python-2.7%2C%203.4%2C%203.5-blue.svg
+    :target: https://github.com/joowani/binarytree
+    :alt: Python Versions
+
+.. image:: https://coveralls.io/repos/github/joowani/binarytree/badge.svg?branch=master
+    :target: https://coveralls.io/github/joowani/binarytree?branch=master
+    :alt: Test Coverage
+
+.. image:: https://img.shields.io/github/issues/joowani/binarytree.svg
+    :target: https://github.com/joowani/binarytree/issues
+    :alt: Issues Open
+
+.. image:: https://img.shields.io/badge/license-MIT-blue.svg
+    :target: https://raw.githubusercontent.com/joowani/binarytree/master/LICENSE
+    :alt: MIT License
+
+|
+
+.. image:: https://cloud.githubusercontent.com/assets/2701938/19216253/5063b602-8d82-11e6-9f54-977bee2147a0.gif
+    :alt: Demo GIF
+
+Introduction
+============
+
+Are you studying binary trees for your next exam, assignment or technical interview?
+
+**BinaryTree** is a minimal Python library which provides you with a simple API
+to generate, visualize and inspect binary trees so you can skip the tedious
+work of mocking up test trees, and dive right into practising your algorithms!
+Heaps and BSTs (binary search trees) are also supported.
+
+
+Installation
+============
+
+To install a stable version from PyPi_:
+
+.. code-block:: bash
+
+    ~$ pip install binarytree
+
+
+To install the latest version directly from GitHub_:
+
+.. code-block:: bash
+
+    ~$ git clone https://github.com/joowani/binarytree.git
+    ~$ python binarytree/setup.py install
+
+You may need to use ``sudo`` depending on your environment setup.
+
+.. _PyPi: https://pypi.python.org/pypi/binarytree
+.. _GitHub: https://github.com/joowani/binarytree
+
+
+Getting Started
+===============
+
+**BinaryTree** uses the following class to represent a tree node:
+
+.. code-block:: python
+
+    class Node(object):
+
+        def __init__(self, value):
+            self.value = value
+            self.left = None
+            self.right = None
+
+
+Generate and pretty-print binary trees:
+
+.. code-block:: python
+
+    from binarytree import tree, bst, heap, pprint
+
+    # Generate random binary trees
+    my_tree = tree(height=5, balanced=False)
+
+    # Generate random binary search trees
+    my_bst = bst(height=5)
+
+    # Generate random min and max heaps
+    my_heap = heap(height=1, max=True)
+
+    # Pretty print the binary trees in stdout
+    pprint(my_tree)
+    pprint(my_bst)
+    pprint(my_heap)
+
+
+`List representations`_ are also supported:
+
+.. _List representations:
+    https://en.wikipedia.org/wiki/Binary_tree#Arrays
+
+
+.. code-block:: python
+
+    from heapq import heapify
+    from binarytree import tree, convert, pprint
+
+    my_list = [7, 3, 2, 6, 9, 4, 1, 5, 8]
+
+    # Convert the list into a tree structure
+    my_tree = convert(my_list)
+
+    # Convert the list into a heap structure
+    heapify(my_list)
+    my_tree = convert(my_list)
+
+    # Convert the tree back to a list
+    my_list = convert(my_tree)
+
+    # Pretty-printing also works on lists
+    pprint(my_list)
+
+
+Inspect a tree to quickly see its various properties:
+
+.. code-block:: python
+
+    from binarytree import tree, inspect
+
+    my_tree = tree(height=10)
+
+    result = inspect(my_tree)
+    print(result['height'])
+    print(result['is_bst'])
+    print(result['is_height_balanced'])
+    print(result['is_max_heap'])
+    print(result['is_min_heap'])
+    print(result['is_weight_balanced'])
+    print(result['leaf_count'])
+    print(result['max_leaf_depth'])
+    print(result['max_value'])
+    print(result['min_leaf_depth'])
+    print(result['min_value'])
+    print(result['node_count'])
+
+
+Import the `Node` class directly to build your own trees:
+
+.. code-block:: python
+
+    from binarytree import Node, pprint
+
+    root = Node(1)
+    root.left = Node(2)
+    root.right = Node(3)
+    root.left.left = Node(4)
+    root.left.right = Node(5)
+
+    pprint(root)
+
+
+If the default `Node` class does not meet your requirements, you can define
+and use your own custom node specification:
+
+.. code-block:: python
+
+    from binarytree import setup, tree, pprint
+
+    # Define your own null/sentinel value (default: None)
+    null = -1
+
+    # Define own node class (default: binarytree.Node)
+    class MyNode(object):
+
+        def __init__(self, data, left, right):
+            self.data = data
+            self.l_child = left
+            self.r_child = right
+
+    # Call setup in the beginning to apply the custom specification
+    setup(
+        node_init_func=lambda v: MyNode(v, null, null),
+        node_class=MyNode,
+        null_value=null,
+        value_attr='data',
+        left_attr='l_child',
+        right_attr='r_child'
+    )
+    my_custom_tree = tree()
+    pprint(my_custom_tree)