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python的settimeout

有时候写python关于网络的程序。比如用urllib2等module发http请求的时候,发现有时候会有死掉的情况,就是程序没任何反应,也不是cpu,内存没资源的问题。具体情况还没搞明白那里出的问题,但是找到一个解决办法。就是设置socket time out,即:如果一个请求超过一定的时间没有完成,就终止,再次发起请求。 这个是从2.3有的功能用法如下: settimeout( value) Set a timeout on blocking socket operations. The value argument can be a nonnegative float expressing seconds, or None. If a float is given, subsequent socket operations will raise an timeout exception if the timeout period value has elapsed before the operation has completed. Setting a timeout of None disables timeouts on socket operations. s.settimeout(0.0) is equivalent to s.setblocking(0); s.settimeout(None) is equivalent to s.setblocking(1). New in version 2.3. 就是settimeout()里面填一个数值。小心别太小,别正常的请求也不能完成。

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一行代码, Java 怎样把List 转成 Map 的方法( Java 8 中的Stream API )

java.util.stream public interface Collector<T, A, R> A mutable reduction operation that accumulates input elements into a mutable result container, optionally transforming the accumulated result into a final representation after all input elements have been processed. Reduction operations can be performed either sequentially or in parallel. Examples of mutable reduction operations include: accumulating elements into a Collection; concatenating strings using a StringBuilder; computing summary information about elements such as sum, min, max, or average; computing "pivot table" summaries such as "maximum valued transaction by seller", etc. The class Collectors provides implementations of many common mutable reductions. A Collector is specified by four functions that work together to accumulate entries into a mutable result container, and optionally perform a final transform on the result. They are: creation of a new result container (supplier()) incorporating a new data element into a result container (accumulator()) combining two result containers into one (combiner()) performing an optional final transform on the container (finisher()) Collectors also have a set of characteristics, such as Collector.Characteristics.CONCURRENT, that provide hints that can be used by a reduction implementation to provide better performance. A sequential implementation of a reduction using a collector would create a single result container using the supplier function, and invoke the accumulator function once for each input element. A parallel implementation would partition the input, create a result container for each partition, accumulate the contents of each partition into a subresult for that partition, and then use the combiner function to merge the subresults into a combined result. To ensure that sequential and parallel executions produce equivalent results, the collector functions must satisfy an identity and an associativity constraints. The identity constraint says that for any partially accumulated result, combi

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