dictionary. popitem() is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictio- nary is empty, calling popitem() raises a KeyError. setdefault(key[, default]) 放大从而导致损失有效位。Knuth 提供了两个指导性示例， 其中出现了精度不足的浮点算术舍入，导致加法的交换律和分配律被打破： # Examples from Seminumerical Algorithms, Section 4.2.2. >>> from decimal import Decimal, getcontext >>> getcontext().prec = 8 >>> u, v The modules described in this chapter support data compression with the zlib, gzip, and bzip2 algorithms, and the creation of ZIP- and tar-format archives. See also 归档操作 provided by the shutil module

dictionary. popitem() is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictio- nary is empty, calling popitem() raises a KeyError. setdefault(key[, default]) 放大从而导致损失有效位。Knuth 提供了两个指导性示例， 其中出现了精度不足的浮点算术舍入，导致加法的交换律和分配律被打破： # Examples from Seminumerical Algorithms, Section 4.2.2. >>> from decimal import Decimal, getcontext >>> getcontext().prec = 8 >>> u, v The modules described in this chapter support data compression with the zlib, gzip, and bzip2 algorithms, and the creation of ZIP- and tar-format archives. See also 归档操作 provided by the shutil module

dictionary. popitem() is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictio- nary is empty, calling popitem() raises a KeyError. setdefault(key[, default]) 放大从而导致损失有效位。Knuth 提供了两个指导性示例， 其中出现了精度不足的浮点算术舍入，导致加法的交换律和分配律被打破： # Examples from Seminumerical Algorithms, Section 4.2.2. >>> from decimal import Decimal, getcontext >>> getcontext().prec = 8 >>> u, v The modules described in this chapter support data compression with the zlib, gzip, and bzip2 algorithms, and the creation of ZIP- and tar-format archives. See also 归档操作 provided by the shutil module

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), make up the Celery calling API, which is also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), make up the Celery calling API, which is also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), make up the Celery calling API, which is also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), make up the Celery calling API, which is also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), make up the Celery calling API, which is also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), represents the Celery calling API, that’s also used for signatures. A

the task To call our task you can use the delay() method. This is a handy shortcut to the apply_async() method that gives greater control of the task execution (see Calling Tasks): >>> from tasks import apply_async(): >>> add.apply_async((2, 2)) The latter enables you to specify execution options like the time to run (countdown), the queue it should be sent to, and so on: >>> add.apply_async((2, 2) current process, so that no message is sent: >>> add(2, 2) 4 These three methods - delay(), apply_async(), and applying (__call__), represents the Celery calling API, that’s also used for signatures. A