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@@ -13,11 +13,11 @@ Quick rundown of the tutorial::
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$ celeryinit
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-2. Open up two terminals, in the first you run:
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+2. Open up two terminals. In the first, run:
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$ celeryd --loglevel=INFO
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- In the other you run the test program:
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+ In the second you run the test program:
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$ python ./test.py
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@@ -27,15 +27,15 @@ Instructions
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============
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This example uses the database as a message queue (commonly called a "ghetto
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-queue"). Excellent for testing, but not very useful for production
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+queue"). Excellent for testing, but not suitable for production
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installations.
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To try it out you have to install the `GhettoQ`_ package first::
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$ pip install ghettoq
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-This package is an add on to `Carrot`_; the messaging abstraction celery
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-uses, that enables the use of databases as message queues. Currently it
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+This package is an add-on to `Carrot`_; the messaging abstraction celery
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+uses. The add-on enables the use of databases as message queues. Currently it
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supports `Redis`_ and relational databases via the Django ORM.
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.. _`ghettoq`: http://pypi.python.org/pypi/ghettoq
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@@ -52,8 +52,8 @@ command::
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We're using SQLite3, so this creates a database file (``celery.db`` as
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specified in the config file). SQLite is great, but when used in combination
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-with Django it doesn't handle concurrency well, to protect your program from
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-lock problems, celeryd will only spawn one worker process. However -- with
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+with Django it doesn't handle concurrency well. To protect your program from
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+lock problems, celeryd will only spawn one worker process. With
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other database drivers you can specify as many worker processes as you want.
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@@ -79,7 +79,7 @@ numbers. You can also run the task manually if you want::
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Using Redis instead
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===================
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-To use redis instead you have to configure the following directives in
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+To use redis instead, you have to configure the following directives in
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``celeryconfig.py``::
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CARROT_BACKEND = "ghettoq.taproot.Redis"
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