* Improving docs

docs/api/python.rst

@@ -1,5 +1,45 @@
 Python API
 ==========
 
-Cheat Sheet
+.. py:currentmodule:: spacy.en
------------
+
+To and from unicode strings
+---------------------------
+
+.. autofunction:: tokenize
+.. autofunction:: lookup
+.. autofunction:: unhash
+
+Access (Hashed) String Views
+----------------------------
+
+.. autofunction:: lex_of
+.. autofunction:: norm_of
+.. autofunction:: shape_of
+.. autofunction:: last3_of
+
+Access String Properties
+------------------------
+
+.. autofunction:: length_of
+.. autofunction:: first_of
+
+Check Orthographic Flags
+-------------------------
+
+.. autofunction:: is_alpha
+.. autofunction:: is_digit
+.. autofunction:: is_punct
+.. autofunction:: is_space
+.. autofunction:: is_lower
+.. autofunction:: is_upper
+.. autofunction:: is_title
+.. autofunction:: is_ascii
+
+Access Distributional Information
+---------------------------------
+
+.. autofunction:: prob_of
+.. autofunction:: cluster_of
+.. autofunction:: check_tag_flag
+.. autofunction:: check_dist_flag

docs/conf.py

@@ -15,6 +15,7 @@
 import sys
 import os
 import os.path
+import sphinx_rtd_theme
 
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
 # If extensions (or modules to document with autodoc) are in another directory,
@@ -105,7 +106,8 @@ pygments_style = 'sphinx'
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
-html_theme = 'default'
+
+html_theme = 'sphinx_rtd_theme'
 
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
@@ -113,7 +115,7 @@ html_theme = 'default'
 #html_theme_options = {}
 
 # Add any paths that contain custom themes here, relative to this directory.
-#html_theme_path = []
+html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
 
 # The name for this set of Sphinx documents.  If None, it defaults to
 # "<project> v<release> documentation".
@@ -166,7 +168,7 @@ html_static_path = ['_static']
 #html_split_index = False
 
 # If true, links to the reST sources are added to the pages.
-#html_show_sourcelink = True
+html_show_sourcelink = False
 
 # If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
 #html_show_sphinx = True

docs/guide/install.rst

@@ -0,0 +1,16 @@
+Installation
+============
+
+Installation via pip::
+
+    pip install spacy
+
+Installation From source via `GitHub <https://github.com/honnibal/spaCy>`_, using virtualenv::
+
+    $ git clone http://github.com/honnibal/spaCy.git
+    $ cd spaCy
+    $ virtualenv .env
+    $ source .env/bin/activate
+    $ pip install -r requirements.txt
+    $ fab make
+    $ fab test

docs/index.rst

@@ -3,81 +3,28 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-spaCy API Reference
+spaCy Natural Language Tokenizer
-=================================
+================================
 
 .. toctree::
-    :maxdepth: 2
+    :maxdepth: 3
     
-    api/python
+    guide/overview
-    api/cython
+    guide/install
-    api/extending
+    api/languages/index.rst
+    api/modules/index.rst
 
-Overview
+Project Home
---------
-
-spaCy is a tokenizer for natural languages, tightly coupled to a global
-vocabulary store.
-
-Instead of a list of strings, spaCy returns references to lexical types. All
-of the string-based features you might need are pre-computed for you:
-
-::
-
-    >>> from spacy import en
-    >>> example = u"Apples aren't oranges..."
-    >>> apples, are, nt, oranges, ellipses = en.tokenize(example)
-    >>> en.is_punct(ellipses)
-    True
-    >>> en.get_string(en.word_shape(apples))
-    'Xxxx'
-
-You also get lots of distributional features, calculated from a large
-sample of text:
-
-::
-
-    >>> en.prob_of(are) > en.prob_of(oranges)
-    True
-    >>> en.can_noun(are)
-    False
-    >>> en.is_oft_title(apples)
-    False
-
-Pros and Cons
--------------
-
-Pros:
-
-- All tokens come with indices into the original string
-- Full unicode support
-- Extensible to other languages
-- Batch operations computed efficiently in Cython
-- Cython API
-- numpy interoperability
-
-Cons:
-
-- It's new (released September 2014)
-- Higher memory usage (up to 1gb)
-- More conceptually complicated
-- Tokenization rules expressed in code, not as data
-
-Installation
 ------------
 
-Installation via pip:
+http://honnibal.github.io/spaCy/
 
-    pip install spacy
+Source (GitHub)
+----------------
 
-From source, using virtualenv:
+http://github.com/honnibal/spaCy
 
-::
+License
+-------
 
-    $ git clone http://github.com/honnibal/spaCy.git
+TODO
-    $ cd spaCy
-    $ virtualenv .env
-    $ source .env/bin/activate
-    $ pip install -r requirements.txt
-    $ fab make
-    $ fab test