No longer supports Microsoft Windows

README.rst

@@ -49,12 +49,22 @@ What do I need?
 Celery version 3.0 runs on,
 
 - Python (2.7, 3.4, 3.5)
-- PyPy (1.8, 1.9)
-- Jython (2.5, 2.7).
+- PyPy (5.1, 2.4)
 
-This is the last version to support Python 2.5,
-and from Celery 3.1, Python 2.6 or later is required.
-The last version to support Python 2.4 was Celery series 2.2.
+
+This is the last version to support Python 2.7,
+and from the next version (Celery 5.x) Python 3.6 or newer is required.
+
+If you are running an older version of Python, you need to be running
+an older version of Celery:
+
+- Python 2.6: Celery series 3.1 or earlier.
+- Python 2.5: Celery series 3.0 or earlier.
+- Python 2.4 was Celery series 2.2 or earlier.
+
+Celery is a project with minimal funding,
+so we do not support Microsoft Windows.
+Please do not open any issues related to that platform.
 
 *Celery* is usually used with a message broker to send and receive messages.
 The RabbitMQ, Redis transports are feature complete,

docs/configuration.rst

@@ -2104,10 +2104,8 @@ can disable this behavior by setting
 
 Enables/disables colors in logging output by the Celery apps.
 
-By default colors are enabled if
-
-    1) the app is logging to a real terminal, and not a file.
-    2) the app is not running on Windows.
+By default colors are enabled if the app is logging to a real
+terminal, and not a file.
 
 .. setting:: worker_log_format
 

docs/django/first-steps-with-django.rst

@@ -85,8 +85,7 @@ becomes ``CELERY_TASK_ALWAYS_EAGER``, and the :setting:`broker_url`
 setting becomes ``CELERY_BROKER_URL``.
 
 You can pass the object directly here, but using a string is better since
-then the worker doesn't have to serialize the object when using Windows
-or execv:
+then the worker doesn't have to serialize the object.
 
 .. code-block:: python
 

docs/faq.rst

@@ -907,7 +907,8 @@ Windows
 
 .. _faq-windows-worker-embedded-beat:
 
-The `-B` / `--beat` option to worker doesn't work?
+Does Celery support Windows?
 ----------------------------------------------------------------
-**Answer**: That's right. Run `celery beat` and `celery worker` as separate
-services instead.
+**Answer**: No.
+
+Since Celery 4.x, Windows is no longer supported due to lack of resources.

docs/getting-started/introduction.rst

@@ -41,12 +41,21 @@ What do I need?
     :subtitle: Celery version 4.0 runs on
 
     - Python ❨2.7, 3.4, 3.5❩
-    - PyPy ❨1.8, 1.9❩
-    - Jython ❨2.5, 2.7❩.
+    - PyPy ❨5.1, 2.4❩
 
-    This is the last version to support Python 2.5,
-    and from the next version Python 2.6 or newer is required.
-    The last version to support Python 2.4 was Celery series 2.2.
+    This is the last version to support Python 2.7,
+    and from the next version (Celery 5.x) Python 3.6 or newer is required.
+
+    If you are running an older version of Python, you need to be running
+    an older version of Celery:
+
+    - Python 2.6: Celery series 3.1 or earlier.
+    - Python 2.5: Celery series 3.0 or earlier.
+    - Python 2.4 was Celery series 2.2 or earlier.
+
+    Celery is a project with minimal funding,
+    so we do not support Microsoft Windows.
+    Please do not open any issues related to that platform.
 
 *Celery* requires a message transport to send and receive messages.
 The RabbitMQ and Redis broker transports are feature complete,

docs/includes/introduction.txt

@@ -41,12 +41,22 @@ What do I need?
 Celery version 3.0 runs on,
 
 - Python (2.7, 3.4, 3.5)
-- PyPy (1.8, 1.9)
-- Jython (2.5, 2.7).
+- PyPy (5.1, 2.4)
 
-This is the last version to support Python 2.5,
-and from Celery 3.1, Python 2.6 or later is required.
-The last version to support Python 2.4 was Celery series 2.2.
+
+This is the last version to support Python 2.7,
+and from the next version (Celery 5.x) Python 3.6 or newer is required.
+
+If you are running an older version of Python, you need to be running
+an older version of Celery:
+
+- Python 2.6: Celery series 3.1 or earlier.
+- Python 2.5: Celery series 3.0 or earlier.
+- Python 2.4 was Celery series 2.2 or earlier.
+
+Celery is a project with minimal funding,
+so we do not support Microsoft Windows.
+Please do not open any issues related to that platform.
 
 *Celery* is usually used with a message broker to send and receive messages.
 The RabbitMQ, Redis transports are feature complete,

docs/tutorials/daemonizing.rst

@@ -517,13 +517,3 @@ or production environment (inadvertently) as root.
 
 .. _`extra/macOS`:
     https://github.com/celery/celery/tree/master/extra/macOS/
-
-
-.. _daemon-windows:
-
-Windows
-======================================================================
-
-See this excellent external tutorial:
-
-http://www.calazan.com/windows-tip-run-applications-in-the-background-using-task-scheduler/

docs/userguide/monitoring.rst

@@ -783,7 +783,7 @@ The worker has connected to the broker and is online.
 - `freq`: Heartbeat frequency in seconds (float).
 - `sw_ident`: Name of worker software (e.g. ``py-celery``).
 - `sw_ver`: Software version (e.g. 2.2.0).
-- `sw_sys`: Operating System (e.g. Linux, Windows, Darwin).
+- `sw_sys`: Operating System (e.g. Linux/Darwin).
 
 .. event:: worker-heartbeat
 
@@ -801,7 +801,7 @@ it is considered to be offline.
 - `freq`: Heartbeat frequency in seconds (float).
 - `sw_ident`: Name of worker software (e.g. ``py-celery``).
 - `sw_ver`: Software version (e.g. 2.2.0).
-- `sw_sys`: Operating System (e.g. Linux, Windows, Darwin).
+- `sw_sys`: Operating System (e.g. Linux/Darwin).
 - `active`: Number of currently executing tasks.
 - `processed`: Total number of tasks processed by this worker.
 

docs/userguide/security.rst

@@ -69,9 +69,9 @@ memory, file-systems and devices.
 
 An exception to this rule is when using the multiprocessing based task pool,
 which is currently the default. In this case, the task will have access to
-any memory copied as a result of the :func:`fork` call (does not apply
-under MS Windows), and access to memory contents written
-by parent tasks in the same worker child process.
+any memory copied as a result of the :func:`fork` call,
+and access to memory contents written by parent tasks in the same worker
+child process.
 
 Limiting access to memory contents can be done by launching every task
 in a subprocess (:func:`fork` + :func:`execve`).

docs/userguide/workers.rst

@@ -459,8 +459,8 @@ Time limits can also be set using the :setting:`task_time_limit` /
 
 .. note::
 
-    Time limits do not currently work on Windows and other
-    platforms that do not support the ``SIGUSR1`` signal.
+    Time limits do not currently work on platforms that do not support
+    the :sig:`SIGUSR1` signal.
 
 
 Changing time limits at run-time

examples/django/proj/celery.py

@@ -11,8 +11,8 @@ from django.conf import settings  # noqa
 
 app = Celery('proj')
 
-# Using a string here means the worker will not have to
-# pickle the object when using Windows.
+# Using a string here means the worker does not have to serialize
+# the configuration object.
 app.config_from_object('django.conf:settings', namespace='CELERY')
 
 # load task modules from all registered Django app configs.