python3学习手册
import time print("当前时间戳",time.time()) print(type(time.time())) ②时间结构体,有9个字段 import time localtime=time.localtime(time.time()) print(localtime) print(type(localtime)) #结果如下 time.struct_time(tm_year=2022 tm_yday=95, tm_isdst=0)time.struct_time'> ③格式化时间 import time print(time.strftime("%Y-%m-%d %H:%M:%S",time.localtime())) print(time.strftime("%a %b %d %H:%M:%S %Y",time.localtime())) # %a表示周几 import time print(time.ctime(time.time())) print(time.asctime(time.localtime())) #同 time.ctime() #日期就一个 5 ④时间字符串转为时间结构体 import time timestr="Tue Apr 05 22:22:15 2022" t=time.strptime(timestr 0 码力 | 213 页 | 3.53 MB | 1 年前3Celery 2.1 Documentation
source asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently remotely. Moni- toring You can capture everything happening with the workers in real-time by subscribing to events. A real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or again – but this time we’ll keep track of the task by holding on to the AsyncResult: >>> result = add.delay(4, 4) >>> result.ready() # returns True if the task has finished processing. False >>> result0 码力 | 285 页 | 1.19 MB | 1 年前3Scrapy 2.6 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 5.9 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 5.10 Deploying structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through a0 码力 | 384 页 | 1.63 MB | 1 年前3Scrapy 1.0 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 5.9 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 5.10 Ubuntu packages structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also com/questions/11227809/why-is-processing-a-sorted- ˓→array-faster-than-an-unsorted-array", "tags": ["java", "c++", "performance", "optimization"], "title": "Why is processing a sorted array faster than0 码力 | 244 页 | 1.05 MB | 1 年前3Scrapy 2.10 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 5.9 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 5.10 Deploying structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through a0 码力 | 419 页 | 1.73 MB | 1 年前3Celery 2.1 Documentation
source asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently remotely. Monitoring You can capture everything happening with the workers in real-time by subscribing to events. A real-time web monitor is in development. Serialization Supports Pickle, JSON, YAML, or again – but this time we’ll keep track of the task by holding on to the AsyncResult: >>> result = add.delay(4, 4) >>> result.ready() # returns True if the task has finished processing. False >>> result0 码力 | 463 页 | 861.69 KB | 1 年前3Celery 2.2 Documentation
source asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently only) Moni- toring You can capture everything happening with the workers in real-time by subscribing to events. A real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or again – but this time we’ll keep track of the task by holding on to the AsyncResult: >>> result = add.delay(4, 4) >>> result.ready() # returns True if the task has finished processing. False >>> result0 码力 | 314 页 | 1.26 MB | 1 年前3Scrapy 1.2 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 5.9 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 5.10 Deploying structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through a0 码力 | 266 页 | 1.10 MB | 1 年前3Scrapy 1.3 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 5.9 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 5.10 Deploying structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through a0 码力 | 272 页 | 1.11 MB | 1 年前3Scrapy 1.6 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 i 5.8 Downloading and processing files and images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 5.9 Deploying structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival. Even though Scrapy was originally designed for web scraping, it can also While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through a0 码力 | 295 页 | 1.18 MB | 1 年前3
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