Updated README

README.rst

@@ -2,12 +2,21 @@
  celery - Distributed Task Queue
 =================================
 
-:Version: 0.9.4
+:Version: 1.0.0
 
 Introduction
 ============
 
-Celery is a distributed task queue.
+Keywords: task queue, job queue, asynchronous, rabbitmq, amqp, redis.
+
+Celery is a task queue/job queue based on distributed message passing.
+It is focused on real-time operation, but has support for scheduling as well.
+
+The execution units, called tasks, are executed concurrently on one or more
+worker servers, asynchronously (in the background) or synchronously
+(wait until ready).
+
+Celery is already used in production to process millions of tasks a day.
 
 It was first created for Django, but is now usable from Python.
 It can also operate with other languages via HTTP+JSON.
@@ -21,9 +30,6 @@ languages see `Executing tasks on a remote web server`_.
 
 .. _`Executing tasks on a remote web server`: http://bit.ly/CgXSc
 
-It is used for executing tasks *asynchronously*, routed to one or more
-worker servers, running concurrently using multiprocessing.
-
 Overview
 ========
 
@@ -85,9 +91,6 @@ Features
       You can find out how many, or if all of the sub-tasks has been executed.
       Excellent for progress-bar like functionality.
 
-    * Has a ``map`` like function that uses tasks,
-      called ``celery.task.dmap``.
-
     * However, you rarely want to wait for these results in a web-environment.
       You'd rather want to use Ajax to poll the task status, which is
       available from a URL like ``celery/<task_id>/status/``. This view

docs/introduction.rst

@@ -2,12 +2,21 @@
  celery - Distributed Task Queue
 =================================
 
-:Version: 0.9.4
+:Version: 1.0.0
 
 Introduction
 ============
 
-Celery is a distributed task queue.
+Keywords: task queue, job queue, asynchronous, rabbitmq, amqp, redis.
+
+Celery is a task queue/job queue based on distributed message passing.
+It is focused on real-time operation, but has support for scheduling as well.
+
+The execution units, called tasks, are executed concurrently on one or more
+worker servers, asynchronously (in the background) or synchronously
+(wait until ready).
+
+Celery is already used in production to process millions of tasks a day.
 
 It was first created for Django, but is now usable from Python.
 It can also operate with other languages via HTTP+JSON.
@@ -21,9 +30,6 @@ languages see `Executing tasks on a remote web server`_.
 
 .. _`Executing tasks on a remote web server`: http://bit.ly/CgXSc
 
-It is used for executing tasks *asynchronously*, routed to one or more
-worker servers, running concurrently using multiprocessing.
-
 Overview
 ========
 
@@ -85,9 +91,6 @@ Features
       You can find out how many, or if all of the sub-tasks has been executed.
       Excellent for progress-bar like functionality.
 
-    * Has a ``map`` like function that uses tasks,
-      called :func:`celery.task.dmap`.
-
     * However, you rarely want to wait for these results in a web-environment.
       You'd rather want to use Ajax to poll the task status, which is
       available from a URL like ``celery/<task_id>/status/``. This view