From 22f3da1832ff69e8fae7b9a6e0d0ff3994b3a334 Mon Sep 17 00:00:00 2001
From: Vincent Driessen <vincent@3rdcloud.com>
Date: Tue, 15 Nov 2011 22:45:51 +0100
Subject: [PATCH] Update README (and example).

---
 README.md               | 28 ++++++++++++++++++----------
 examples/fib.py         |  3 ---
 examples/run_example.py | 22 ++++++++++++++--------
 examples/run_worker.py  | 11 ++++++-----
 4 files changed, 38 insertions(+), 26 deletions(-)

diff --git a/README.md b/README.md
index 9a6be36d..22c1c5e5 100644
--- a/README.md
+++ b/README.md
@@ -7,28 +7,36 @@
 
 # Putting jobs on queues
 
-To put jobs on queues, first declare a Python function call as a job, like so:
+To put jobs on queues, first declare a Python function to be called on
+a background process:
 
-    @job('default')
     def slow_fib(n):
         if n <= 1:
             return 1
         else:
             return slow_fib(n-1) + slow_fib(n-2)
 
-You can still call the function synchronously:
+Notice anything?  There's nothing special about a job!  Any Python function can
+be put on an RQ queue, as long as the function is in a module that is
+accessible from the worker process.
 
+To calculate the 36th Fibonacci number in the background, simply do this:
+
+    from rq import Queue
     from fib import slow_fib
-    slow_fib(4)
+    
+    # Calculate the 36th Fibonacci number in the background
+    q = Queue()
+    q.enqueue(slow_fib, 36)
 
-You can find an example implementation in the `examples/` directory.  To run
-it, open two terminal windows and run the following commands in them:
+If you want to put the work on a specific queue, simply specify its name:
 
-1. `python example/run_worker.py`
-1. `python example/run_example.py`
+    q = Queue('math')
+    q.enqueue(slow_fib, 36)
 
-This starts two workers and starts crunching the fibonacci calculations in the
-background, while the script shows the crunched data updates every second.
+You can use any queue name, so you can quite flexibly distribute work to your
+own desire.  Common patterns are to name your queues after priorities (e.g.
+`high`, `medium`, `low`).
 
 
 # Installation
diff --git a/examples/fib.py b/examples/fib.py
index 521e06d2..2130b3cb 100644
--- a/examples/fib.py
+++ b/examples/fib.py
@@ -1,6 +1,3 @@
-from rq import job
-
-@job('default')
 def slow_fib(n):
     if n <= 1:
         return 1
diff --git a/examples/run_example.py b/examples/run_example.py
index f3414d35..d1b273c6 100644
--- a/examples/run_example.py
+++ b/examples/run_example.py
@@ -1,23 +1,29 @@
 import os
 import time
-from rq import conn
-from redis import Redis
+from rq import Queue
 from fib import slow_fib
 
-# Tell rq what Redis connection to use
+# Tell RQ what Redis connection to use
+from redis import Redis
+from rq import conn
 conn.push(Redis())
 
+# Range of Fibonacci numbers to compute
+fib_range = range(20, 34)
+
 # Kick off the tasks asynchronously
 async_results = {}
-for x in range(20, 30):
-    async_results[x] = slow_fib.delay(x)
+q = Queue()
+for x in fib_range:
+    async_results[x] = q.enqueue(slow_fib, x)
 
+start_time = time.time()
 done = False
 while not done:
     os.system('clear')
-    print 'Asynchronously: (now = %s)' % time.time()
+    print 'Asynchronously: (now = %.2f)' % (time.time() - start_time)
     done = True
-    for x in range(20, 30):
+    for x in fib_range:
         result = async_results[x].return_value
         if result is None:
             done = False
@@ -26,6 +32,6 @@ while not done:
     print ''
     print 'To start the actual in the background, run a worker:'
     print '    python examples/run_worker.py'
-    time.sleep(1)
+    time.sleep(0.2)
 
 print 'Done'
diff --git a/examples/run_worker.py b/examples/run_worker.py
index 3efc4721..e87ec89e 100644
--- a/examples/run_worker.py
+++ b/examples/run_worker.py
@@ -1,9 +1,10 @@
-from redis import Redis
-from rq import conn
-from rq.daemon import run_daemon
+from rq import Queue, Worker
 
 # Tell rq what Redis connection to use
+from redis import Redis
+from rq import conn
 conn.push(Redis())
 
-listen_on_queues = ['default']
-run_daemon(listen_on_queues)
+if __name__ == '__main__':
+    q = Queue()
+    Worker(q).work_forever()