optional

pandas读取csv

懵懂的女人 提交于 2020-12-03 11:57:10
参数 读取CSV(逗号分割)文件到DataFrame 也支持文件的部分导入和选择迭代 更多帮助参见: http://pandas.pydata.org/pandas-docs/stable/io.html 参数: filepath_or_buffer : str,pathlib。str, pathlib.Path, py._path.local.LocalPath or any object with a read() method (such as a file handle or StringIO) 可以是URL,可用URL类型包括:http, ftp, s3和文件。对于多文件正在准备中 本地文件读取实例:://localhost/path/to/table.csv sep : str, default ‘,’ 指定分隔符。如果不指定参数,则会尝试使用逗号分隔。分隔符长于一个字符并且不是‘\s+’,将使用python的语法分析器。并且忽略数据中的逗号。正则表达式例子:'\r\t' delimiter : str, default None 定界符,备选分隔符(如果指定该参数,则sep参数失效) delim_whitespace : boolean, default False. 指定空格(例如’ ‘或者’ ‘)是否作为分隔符使用,等效于设定sep='\s+'

Does it make sense to combine optional with reference_wrapper?

雨燕双飞 提交于 2020-12-01 01:33:48
问题 It occurred to me that in C++ it is possible to use the type std::optional<std::reference_wrapper<T>> . An object of this type is essentially a reference to an object of type T or a null value, i.e., pretty much a pointer. My questions: Is there any conceptual difference between std::optional<std::reference_wrapper<T>> and T* ? Is there any practical difference? Are there situations where it might be advisable to choose std::optional<std::reference_wrapper<T>> over T* ? 回答1: Is there any

Does it make sense to combine optional with reference_wrapper?

拥有回忆 提交于 2020-12-01 01:29:05
问题 It occurred to me that in C++ it is possible to use the type std::optional<std::reference_wrapper<T>> . An object of this type is essentially a reference to an object of type T or a null value, i.e., pretty much a pointer. My questions: Is there any conceptual difference between std::optional<std::reference_wrapper<T>> and T* ? Is there any practical difference? Are there situations where it might be advisable to choose std::optional<std::reference_wrapper<T>> over T* ? 回答1: Is there any

Pytest学习(七)

杀马特。学长 韩版系。学妹 提交于 2020-11-30 12:34:15
Pytest学习(七) - skip、skipif的使用 前言 作为一个java党,我还是觉得pytest和testng很像,有时候真的会感觉到代码语言在某种程度上是相通的,那么今天来说说这两个知识点。 skip和skipif,见名知意,就是跳过测试呗,直白的说就是用于不想执行的代码,标记后,标记的代码不执行。 skip的用法 使用示例:@pytest.mark.skip(reason="不想执行的原因,执行时会输出reason内容") 1、标记在函数方法上 示例代码如下: # 标记在函数上 @pytest.mark.skip(reason="标记在函数上,被标记函数不会被执行!!") def test_case2(): print("我是测试用例2,但我不会执行") 运行结果如下: 2、标记在类中的函数方法上 示例代码如下: class TestClass1(object): def test_case3(self): print("我是用例3") # 标记在类中的函数上 @pytest.mark.skip(reason="标记在类中的函数上,同样也不会执行哦!") def test_case4(self): print("我是测试用例4,但我不会执行") 运行结果如下: 3、标记在类上 示例代码如下: @pytest.mark.skip(reason="标记在类上

Java 8 extract first key from matching value in a Map

别说谁变了你拦得住时间么 提交于 2020-11-30 04:36:13
问题 Suppose I have a map of given name, surname pairs and I want to find the given name of the first entry in that map that has the surname matching a certain value. How would we do this in a java 8 fashion. In my test case example below I put two ways that would do it. However the first one (looking for the given name of the first person with a surname of "Donkey") will throw java.util.NoSuchElementException: No value present so it is not safe. The second one works but it is not only harder to

Concatenate Optional Lists

一笑奈何 提交于 2020-11-28 10:47:35
问题 I have three Optional> which have to be combined and returned. I tried to use Optional.map() and flatmap() but was not successful. public Optional<List<Entiy>> getRecords() { Optional<List<Entiy>> entity1 = repo.findAllByStatus("1"); Optional<List<Entiy>> entity2 = repo.findAllByStatus("2"); Optional<List<Entiy>> entity3 = repo.findAllByStatus("3"); //Need to return a concatenation of entity1, 2 and 3 } Any thoughts on how to do is efficiently? 回答1: Something like : return Optional.of(Stream

Concatenate Optional Lists

心不动则不痛 提交于 2020-11-28 10:45:42
问题 I have three Optional> which have to be combined and returned. I tried to use Optional.map() and flatmap() but was not successful. public Optional<List<Entiy>> getRecords() { Optional<List<Entiy>> entity1 = repo.findAllByStatus("1"); Optional<List<Entiy>> entity2 = repo.findAllByStatus("2"); Optional<List<Entiy>> entity3 = repo.findAllByStatus("3"); //Need to return a concatenation of entity1, 2 and 3 } Any thoughts on how to do is efficiently? 回答1: Something like : return Optional.of(Stream

Concatenate Optional Lists

我是研究僧i 提交于 2020-11-28 10:45:07
问题 I have three Optional> which have to be combined and returned. I tried to use Optional.map() and flatmap() but was not successful. public Optional<List<Entiy>> getRecords() { Optional<List<Entiy>> entity1 = repo.findAllByStatus("1"); Optional<List<Entiy>> entity2 = repo.findAllByStatus("2"); Optional<List<Entiy>> entity3 = repo.findAllByStatus("3"); //Need to return a concatenation of entity1, 2 and 3 } Any thoughts on how to do is efficiently? 回答1: Something like : return Optional.of(Stream

007 SpringBoot的@EnableAutoConfiguration注解

青春壹個敷衍的年華 提交于 2020-11-27 02:26:12
一:原理 1.   首先Spring Boot项目中都会如下启动类: @SpringBootApplication public class Application { public static void main(String[] args) { SpringApplication.run(Application. class , args); } }   其中,@SpringBootApplication中有三个重要的注解合一。 @Target(ElementType.TYPE) @Retention(RetentionPolicy.RUNTIME) @Documented @Inherited @SpringBootConfiguration @EnableAutoConfiguration @ComponentScan(excludeFilters = { @Filter(type = FilterType.CUSTOM, classes = TypeExcludeFilter. class ), @Filter(type = FilterType.CUSTOM, classes = AutoConfigurationExcludeFilter. class ) }) public @ interface SpringBootApplication {   所以,来说说

Java8 Stream:2万字20个实例,玩转集合的筛选、归约、分组、聚合

这一生的挚爱 提交于 2020-11-27 00:22:10
先贴上几个案例,水平高超的同学可以挑战一下: 从员工集合中筛选出salary大于8000的员工,并放置到新的集合里。 统计员工的最高薪资、平均薪资、薪资之和。 将员工按薪资从高到低排序,同样薪资者年龄小者在前。 将员工按性别分类,将员工按性别和地区分类,将员工按薪资是否高于8000分为两部分。 用传统的迭代处理也不是很难,但代码就显得冗余了,跟Stream相比高下立判。 1 Stream概述 Java 8 是一个非常成功的版本,这个版本新增的 Stream ,配合同版本出现的 Lambda ,给我们操作集合(Collection)提供了极大的便利。 那么什么是 Stream ? Stream 将要处理的元素集合看作一种流,在流的过程中,借助 Stream API 对流中的元素进行操作,比如:筛选、排序、聚合等。 Stream 可以由数组或集合创建,对流的操作分为两种: 中间操作,每次返回一个新的流,可以有多个。 终端操作,每个流只能进行一次终端操作,终端操作结束后流无法再次使用。终端操作会产生一个新的集合或值。 另外, Stream 有几个特性: stream不存储数据,而是按照特定的规则对数据进行计算,一般会输出结果。 stream不会改变数据源,通常情况下会产生一个新的集合或一个值。 stream具有延迟执行特性,只有调用终端操作时,中间操作才会执行。 2 Stream的创建