Celery 3.1 Documentationcomplete, but there’s also support for a myriad of other experimental solutions, including using SQLite for local development. Celery can run on a single machine, on multiple machines, or even across usual SQLAlchemy connection string, but with ‘sqla+’ prepended to it: BROKER_URL = 'sqla+sqlite:///celerydb.sqlite' This transport uses only the BROKER_URL setting, which have to be an SQLAlchemy database examples using a selection of other SQLAlchemy Connection Strings: # sqlite (filename) BROKER_URL = 'sqla+sqlite:///celerydb.sqlite' # mysql 16 Chapter 2. Contents Celery Documentation, Release 3.10 码力 | 607 页 | 2.27 MB | 1 年前3
Celery 3.1 Documentationseries 2.2. but there’s also support for a myriad of other experimental solutions, including using SQLite for local development. Celery can run on a single machine, on multiple machines, or even across usual SQLAlchemy connection string, but with ‘sqla+’ prepended to it: BROKER_URL = 'sqla+sqlite:///celerydb.sqlite' This transport uses only the BROKER_URL setting, which have to be an SQLAlchemy database [http://www.sqlalchemy.org/docs/core/engines.html#database-urls]: # sqlite (filename) BROKER_URL = 'sqla+sqlite:///celerydb.sqlite' # mysql BROKER_URL = 'sqla+mysql://scott:tiger@localhost/foo' # postgresql0 码力 | 887 页 | 1.22 MB | 1 年前3
Celery 2.5 Documentationusual SQLAlchemy connection string, but with ‘sqla+’ prepended to it: BROKER_URL = "sqla+sqlite:///celerydb.sqlite" This transport uses only the BROKER_URL setting, which have to be an SQLAlchemy database examples using a selection of other SQLAlchemy Connection String‘s: # sqlite (filename) BROKER_URL = "sqla+sqlite:///celerydb.sqlite" # mysql BROKER_URL = "sqla+mysql://scott:tiger@localhost/foo" # postgresql $ djcelerymon Database tables will be created the first time the monitor is run. By default an sqlite3 database file named djcelerymon.db is used, so make sure this file is writeable by the user running0 码力 | 400 页 | 1.40 MB | 1 年前3
Celery 2.3 Documentation$ djcelerymon Database tables will be created the first time the monitor is run. By default an sqlite3 database file named djcelerymon.db is used, so make sure this file is writeable by the user running ("myapp.tasks", ) ## Result store settings. CELERY_RESULT_BACKEND = "database" CELERY_RESULT_DBURI = "sqlite:///mydatabase.db" 71 Celery Documentation, Release 2.3.5 ## Broker settings. BROKER_HOST = "localhost" to configure it with an Connection String, some examples include: # sqlite (filename) CELERY_RESULT_DBURI = "sqlite:///celerydb.sqlite" # mysql CELERY_RESULT_DBURI = "mysql://scott:tiger@localhost/foo"0 码力 | 334 页 | 1.25 MB | 1 年前3
Celery 2.5 Documentationusual SQLAlchemy connection string, but with ‘sqla+’ prepended to it: BROKER_URL = "sqla+sqlite:///celerydb.sqlite" This transport uses only the BROKER_URL setting, which have to be an SQLAlchemy database [http://www.sqlalchemy.org/docs/core/engines.html#database-urls]‘s: # sqlite (filename) BROKER_URL = "sqla+sqlite:///celerydb.sqlite" # mysql BROKER_URL = "sqla+mysql://scott:tiger@localhost/foo" # postgresql $ djcelerymon Database tables will be created the first time the monitor is run. By default an sqlite3 database file named djcelerymon.db is used, so make sure this file is writeable by the user running0 码力 | 647 页 | 1011.88 KB | 1 年前3
Celery 2.1 Documentation$ djcelerymon Database tables will be created the first time the monitor is run. By default an sqlite3 database file named djcelerymon.db is used, so make sure this file is writeable by the user running ("myapp.tasks", ) ## Result store settings. CELERY_RESULT_BACKEND = "database" CELERY_RESULT_DBURI = "sqlite:///mydatabase.db" 63 Celery Documentation, Release 2.1.4 ## Broker settings. BROKER_HOST = "localhost" to configure it with an Connection String, some examples include: # sqlite (filename) CELERY_RESULT_DBURI = "sqlite:///celerydb.sqlite" # mysql CELERY_RESULT_DBURI = "mysql://scott:tiger@localhost/foo"0 码力 | 285 页 | 1.19 MB | 1 年前3
Celery 2.3 Documentation$ djcelerymon Database tables will be created the first time the monitor is run. By default an sqlite3 database file named djcelerymon.db is used, so make sure this file is writeable by the user running ("myapp.tasks", ) ## Result store settings. CELERY_RESULT_BACKEND = "database" CELERY_RESULT_DBURI = "sqlite:///mydatabase.db" ## Broker settings. BROKER_HOST = "localhost" BROKER_PORT = 5672 BROKER_VHOST org/docs/core/engines.html#database-urls], some examples include: # sqlite (filename) CELERY_RESULT_DBURI = "sqlite:///celerydb.sqlite" # mysql CELERY_RESULT_DBURI = "mysql://scott:tiger@localhost/foo"0 码力 | 530 页 | 900.64 KB | 1 年前3
Celery v4.1.0 Documentationcomplete, but there’s also support for a myriad of other experimental solutions, including using SQLite for local development. Celery can run on a single machine, on multiple machines, or even across org/pypi/django-celery-beat/] extension that stores the schedule in the Django database, and presents a convenient admin interface to manage periodic tasks at runtime. To install and use this extension: 1. Use pip to the celery.bin package. This is how the Flower [https://pypi.python.org/pypi/Flower/] monitoring extension adds the celery flower command, by adding an entry-point in setup.py: setup( name='flower'0 码力 | 1057 页 | 1.35 MB | 1 年前3
Celery v4.0.1 Documentationcomplete, but there’s also support for a myriad of other experimental solutions, including using SQLite for local development. Celery can run on a single machine, on multiple machines, or even across org/pypi/django-celery-beat/] extension that stores the schedule in the Django database, and presents a convenient admin interface to manage periodic tasks at runtime. To install and use this extension: 1. Use pip to the celery.bin package. This is how the Flower [https://pypi.python.org/pypi/Flower/] monitoring extension adds the celery flower command, by adding an entry-point in setup.py: setup( name='flower'0 码力 | 1040 页 | 1.37 MB | 1 年前3
Celery v4.0.2 Documentationcomplete, but there’s also support for a myriad of other experimental solutions, including using SQLite for local development. Celery can run on a single machine, on multiple machines, or even across org/pypi/django-celery-beat/] extension that stores the schedule in the Django database, and presents a convenient admin interface to manage periodic tasks at runtime. To install and use this extension: 1. Use pip to the celery.bin package. This is how the Flower [https://pypi.python.org/pypi/Flower/] monitoring extension adds the celery flower command, by adding an entry-point in setup.py: setup( name='flower'0 码力 | 1042 页 | 1.37 MB | 1 年前3
共 51 条
- 1
- 2
- 3
- 4
- 5
- 6













