Celery v4.4.5 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1215 页 | 1.44 MB | 1 年前3 Celery 4.4.0 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1185 页 | 1.42 MB | 1 年前3 Celery 4.4.3 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1209 页 | 1.44 MB | 1 年前3 Celery 4.4.1 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1188 页 | 1.42 MB | 1 年前3 Celery v4.3.0 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1174 页 | 1.41 MB | 1 年前3 Celery 4.4.2 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1188 页 | 1.42 MB | 1 年前3 Celery v4.4.4 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1215 页 | 1.44 MB | 1 年前3 Celery v4.4.6 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1216 页 | 1.44 MB | 1 年前3 Celery v4.4.7 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 1219 页 | 1.44 MB | 1 年前3
Celery v4.3.0 Documentationadditional components can be defined by the user. The worker is built up using “bootsteps” — a dependency graph enabling fine grained control of the worker’s internals. Framework Integration Celery is easy to be called when all of the tasks in a group have finished executing. This is often required for algorithms that aren’t embarrassingly parallel: >>> from celery import chord >>> res = chord((add.s(i, i) children[0].get() 64 The result instance also has a collect() method that treats the result as a graph, enabling you to iterate over the results: >>> list(res.collect()) [(0 码力 | 790 页 | 2.84 MB | 1 年前3共 45 条- 1
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