For the greater grammar. #154

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merged 1 commit into from May 20, 2012
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10 docs/writing/structure.rst
@@ -186,14 +186,14 @@ objects, they have a type, they can be passed as function arguments, they may
have methods and properties. In this understanding, Python is an
object-oriented language.
-However, unlike Java, Python do not impose object-oriented programming as the
+However, unlike Java, Python does not impose object-oriented programming as the
main programming paradigm. It is perfectly viable for a Python project to not
be object-oriented, i.e. to use no or very few class definitions, class
inheritance, or any other mechanisms that are specific to object-oriented
programming.
Moreover, as seen in the modules_ section, the way Python handles modules and
-namespaces gives the developer a natural way to ensure
+namespaces gives the developer a natural way to ensure the
encapsulation and separation of abstraction layers, both being the most common
reasons to use object-orientation. Therefore, Python programmers have more
latitude to not use object-orientation, when it is not required by the business
@@ -208,8 +208,8 @@ In some architectures, typically web applications, multiple instances of Python
processes are spawned to respond to external requests that can
happen at the same time. In this case, holding some state into instantiated
objects, which means keeping some static information about the world, is prone
-to concurrency problems or race-conditions. Sometime between the initialization of the
-state of an object, usually done with the __init__() method, and the actual use
+to concurrency problems or race-conditions. Sometimes, between the initialization of
+the state of an object (usually done with the __init__() method) and the actual use
of the object state through one of its methods, the world may have changed, and
the retained state may be outdated. For example, a request may load an item in
memory and mark it as read by a user. If another request requires the deletion
@@ -257,7 +257,7 @@ The Python language provides a simple yet powerful syntax called 'decorators'.
A decorator is a function or a class that wraps (or decorate) a function
or a method. The 'decorated' function or method will replace the original
'undecorated' function or method. Because functions are first-class objects
-in Python it can be done 'manually' but using the @decorator syntax is
+in Python, it can be done 'manually', but using the @decorator syntax is
clearer and thus preferred.
.. code-block:: python