tiny doc typo and docs formatting

elastic · Apr 21, 2015 · 6cd01bb · 6cd01bb
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diff --git a/docs/persistence.rst b/docs/persistence.rst
@@ -251,7 +251,7 @@ metadata for your document:
   created from the fields on the document class itself.
 
 Any attributes on the ``Meta`` class that are instance of ``MetaField`` will be
-used to control the mapping of the mata fields (``_all``, ``_parent`` etc).
+used to control the mapping of the meta fields (``_all``, ``_parent`` etc).
 Just name the parameter (without the leading underscore) as the field you wish
 to map and pass any parameters to the ``MetaField`` class:
 

diff --git a/docs/search_dsl.rst b/docs/search_dsl.rst
@@ -83,7 +83,8 @@ Queries
 
 
 
-The library provides classes for all Elasticsearch query types. Pass all the parameters as keyword arguments:
+The library provides classes for all Elasticsearch query types. Pass all the
+parameters as keyword arguments:
 
 .. code:: python
 
@@ -201,19 +202,38 @@ To nest aggregations, you can use the ``.bucket()`` and ``.metric()`` methods:
     a = A('terms', field='category')
     # {'terms': {'field': 'category'}}
 
-    a.metric('clicks_per_category', 'sum', field='clicks').bucket('tags_per_category', 'terms', field='tags')
-    # {'terms': {'field': 'category'}, 'aggs': {'clicks_per_category': {'sum': {'field': 'clicks'}}, 'tags_per_category': {'terms': {'field': 'tags'}}}}
+    a.metric('clicks_per_category', 'sum', field='clicks')\
+        .bucket('tags_per_category', 'terms', field='tags')
+    # {
+    #   'terms': {'field': 'category'},
+    #   'aggs': {
+    #     'clicks_per_category': {'sum': {'field': 'clicks'}},
+    #     'tags_per_category': {'terms': {'field': 'tags'}}
+    #   }
+    # }
 
 To add aggregations to the ``Search`` object, use the ``.aggs`` property, which
 acts as a top-level aggregation:
 
 .. code:: python
 
     s = Search()
-    s.aggs.bucket('per_category', 'terms', field='category').metric('clicks_per_category', 'sum', field='clicks').bucket('tags_per_category', 'terms', field='tags')
+    s.aggs.bucket('per_category', 'terms', field='category')\
+        .metric('clicks_per_category', 'sum', field='clicks')\
+        .bucket('tags_per_category', 'terms', field='tags')
 
     s.to_dict()
-    # {'aggs': {'per_category': {'terms': {'field': 'category'}, 'aggs': {'clicks_per_category': {'sum': {'field': 'clicks'}}, 'tags_per_category': {'terms': {'field': 'tags'}}}}}}
+    # {
+    #   'aggs': {
+    #     'per_category': {
+    #       'terms': {'field': 'category'},
+    #       'aggs': {
+    #         'clicks_per_category': {'sum': {'field': 'clicks'}},
+    #         'tags_per_category': {'terms': {'field': 'tags'}}
+    #       }
+    #     }
+    #   }
+    # }
 
 
 You can access an existing bucket by its name: