update documents

docs/index.rst

@@ -15,12 +15,30 @@ Installation (need to upload to PYPI later)::
 
    pip install rltk
 
-Example::
+Example 1::
 
    >>> import rltk
    >>> rltk.levenshtein_distance('abc', 'abd')
    1
 
+In RLTK, you can simply load the the resource you need and give it name, then reuse it by name in later methods.
+
+Example 2::
+
+   >>> import rltk
+   >>>
+   >>> edit_distance_cost = {'insert': {'c':50}, 'insert_default':100, 'delete_default':100, 'substitute_default':100}
+   >>>
+   >>> tk = rltk.init()
+   >>> tk.load_edit_distance_table('A1', edit_distance_cost) # load resource
+   >>> tk.levenshtein_distance('a', 'abc')
+   >>> 2
+   >>> tk.levenshtein_distance('a', 'abc', name='A1')
+   >>> 150
+   >>> tk.normalized_levenshtein_distance('a', 'abc', name='A1')
+   >>> 50.0
+
+
 API Reference
 --------------
 

docs/modules.rst

@@ -1,7 +1,7 @@
-similarity
+RLTK
 =================
 
 .. toctree::
    :maxdepth: 4
 
-   similarity
+   rltk

docs/rltk.rst

@@ -0,0 +1,9 @@
+rltk package
+=========================
+
+.. automodule:: __init__
+   :members:
+
+.. automodule:: core
+.. autoclass:: Core
+   :members:

rltk/__init__.py

@@ -1,32 +1,10 @@
 from core import *
 
 def init():
-    return RLTK()
+    """
+    Initialization method.
 
-# def init(init_dict):
-#     """
-#     This is the method for loading all configurations into memory. Once initialized, invoke methods without passing
-#     those gigantic structure again and again.
-#
-#     Args:
-#         init_dict (dict):
-#             'levenshtein.insert'
-#             'levenshtein.delete'
-#             'levenshtein.substitute'
-#             'levenshtein.insert_default'
-#             'levenshtein.delete_default'
-#             'levenshtein.substitute_default'
-#             'tf_idf.corpus_list'
-#
-#     Returns:
-#         object: wrapped object
-#
-#     Examples:
-#         >>> import rltk
-#         >>> tk = rltk.init({'tf_idf.corpus_list': [['a', 'b', 'a'], ['a', 'c'], ['a']]})
-#         >>> tk.levenshtein_distance('a', 'ab')
-#         0.5
-#         >>> tk.tf_idf(['a', 'b', 'a'], ['a', 'c'])
-#         0.17541160386140586
-#     """
-#     return RLTK(init_dict)
+    Returns:
+        object: RLTK object
+    """
+    return Core()