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python开源工具列表【持续更新】

以下是个人在工作中整理的一些python wheel,供参考。这个列表包含与网页抓取和数据处理的Python库 网络 通用urllib-网络库(stdlib)。requests-网络库。grab–网络库(基于pycurl)。pycurl–网络库(绑定libcurl)。urllib3–Python HTTP库,安全连接池、支持文件post、可用性高。httplib2–网络库。RoboBrowser–一个简单的、极具Python风格的Python库,无需独立的浏览器即可浏览网页。MechanicalSoup-一个与网站自动交互Python库。mechanize-有状态、可编程的Web浏览库。socket–底层网络接口(stdlib)。Unirest for Python–Unirest是一套可用于多种语

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任务调度工具Quartz入门笔记

一,导包 1)官网下载:http://www.quartz-scheduler.org/downloads/ 2)Maven <dependency> <groupId>org.quartz-scheduler</groupId> <artifactId>quartz</artifactId> <version>2.2.1</version> </dependency> 二,实例 1.先定义一个作业任务类,写我们的执行代码 package cn.zyzpp.quartz.demo; import java.text.SimpleDateFormat; import java.util.Date; import org.quartz.Job; import org.quartz.JobDataMap; import org.quartz.JobDetail; import org.quartz.JobExecutionContext; import org.quartz.JobExecutionException; import org.quartz.JobKey; import org.quartz.Trigger; /** * Created by yster@foxmail.com * 2018年4月9日 下午11:00:52 */ public class HelloJob implements Job { //第(2)种获取传入的参数的方法:setter方法 属性对应key的值 private String setKey; public void execute(JobExecutionContext context) throws JobExecutionException { //获取JobDetail对象 String now = new SimpleDateFormat("yyyy-mm-dd hh:mm:ss").format(new Date()); JobDetail detail = context.getJobDetail(); String group = detail.getKey().getGroup(); String value = detail.getJobDataMap().getString("key"); //获取Trigger对象 Trigger trigger = context.getTrigger(); value= trigger.getJobDataMap().getString("key"); //获取JobDataMap对象 //第(1)种获取传入的参数的方法 JobDataMap data = context.getMergedJobDataMap(); value = data.getString("key");//相同key 调用trigger的value //System.out.println(group + ":" + value + " at " + now + setKey); //获取Jobkey对象 JobKey jobKey = trigger.getJobKey(); String name = jobKey.getName(); group = jobKey.getGroup(); try { Thread.sleep(5000l); } catch (InterruptedException e) { e.printStackTrace(); } System.out.println(now + ":" + name + " " +group); } public String getSetKey() { return setKey; } public void setSetKey(String setKey) { this.setKey = setKey; } } 2. package cn.zyzpp.quartz.demo; import java.text.SimpleDateFormat; import java.util.Date; import org.quartz.CronScheduleBuilder; import org.quartz.CronTrigger; import org.quartz.JobBuilder; import org.quartz.SimpleScheduleBuilder; import org.quartz.SimpleTrigger; import org.quartz.TriggerBuilder; import org.quartz.JobDetail; import org.quartz.Scheduler; import org.quartz.Trigger; import org.quartz.impl.StdSchedulerFactory; /** * Created by yster@foxmail.com 2018年4月9日 下午10:57:14 */ public class QuartzTest { public static void main(String[] args) { SimpleDateFormat sf =new SimpleDateFormat("yyyy-mm-dd hh:mm:ss"); try { // Quartz 作业:定义一个JobDetail:为Job类设置属性 JobDetail jobDetail = JobBuilder.newJob(HelloJob.class) // 定义Job类为HelloQuartz类,这是真正的执行逻辑所在 .withIdentity("job1", "group1") // 定义name/group .usingJobData("key", "job-value") // 自定义参数 .usingJobData("setKey", "setValue").build(); // System.out.println(jobDetail.getKey().getName()); // System.out.println(jobDetail.getKey().getGroup()); // System.out.println(jobDetail.getJobClass()); // 定义任务开始时间以及结束时间 Date startDate = new Date(); System.out.println("scheduler开始:" + sf.format(new Date())); startDate.setTime(new Date().getTime() + 2000); Date endDate = new Date(); endDate.setTime(startDate.getTime() + 4000); // Quartz触发器:定义一个Trigger Trigger trigger = TriggerBuilder.newTrigger() .withIdentity("trigger1", "group1") // 定义name/group // .startNow()//一旦加入scheduler,立即生效 .startAt(startDate) .endAt(endDate) .withSchedule(SimpleScheduleBuilder.simpleSchedule() .withIntervalInSeconds(1) // 每隔一秒执行一次 .repeatForever()) // 一直执行,奔腾到老不停歇 .usingJobData("key", "trigger-value") .build(); //SimpleTrigger 在一个指定时间段内执行一次作业任务 或者在指定时间间隔内多次执行作业任务 SimpleTrigger simpleTrigger = (SimpleTrigger) TriggerBuilder .newTrigger() .withIdentity("trigger1", "group1") // 定义name/group .startAt(startDate) .withSchedule(SimpleScheduleBuilder.simpleSchedule() .withIntervalInSeconds(2) .withRepeatCount(3)) //执行第1次后再执行3次(SimpleTrigger.REPEAT_INDEFINITELY) .build(); //CronTrigger 基于 cron 表达式,更常用 CronTrigger cronTrigger = (CronTrigger) TriggerBuilder .newTrigger() .withIdentity("trigger1", "group1") // 定义name/group .startAt(startDate) .withSchedule( //Cron表达式:[秒][分][时][日][月][周][年] (周日1-周六7,年可不写) *每 ?不关心 -至 #第 /递增 ,和 L最后 W最近工作日 CronScheduleBuilder.cronSchedule("0/2 * * * * ? * ") ) .build(); // 调度类链接“工作”和“触发器”到一起,并执行它 // 创建scheduler StdSchedulerFactory sfact = new StdSchedulerFactory(); Scheduler scheduler = sfact.getScheduler(); // 加入这个调度 返回第一次执行时间 scheduler.scheduleJob(jobDetail, cronTrigger); //System.out.println("调度器:" + sf.format(scheduler.scheduleJob(jobDetail, cronTrigger))); // 启动之 scheduler.start(); // 运行一段时间后暂停 可再次start 当前主线程不终止 Thread.sleep(10000l); // scheduler.standby(); // System.out.println("暂停:三秒后再次开启"); // Thread.sleep(3000l); // scheduler.start(); // Thread.sleep(5000l); scheduler.shutdown(true);//true等待执行的job完成后关闭scheduler,false直接关闭 System.out.println("scheduler终止" + sf.format(new Date())); } catch (Exception e) { e.printStackTrace(); } } } 三,干货 1)Cron表达式 2)/org/quartz/quartz.properties 3)集成Spring <!-- JobDetail --> <!-- (1)simpleJobDetail : 定义任务类和任务方法--> <bean id="simpleJobDetail" class="org.springframework.scheduling.quartz.MethodInvokingJobDetailFactoryBean"> <property name="targetObject" ref="myBean" /> <property name="targetMethod" value="printMessage" /> </bean> <!--(2)继承 QuartzJobBean 传参--> <bean id="firstComplexJobDetail" class="org.springframework.scheduling.quartz.JobDetailFactoryBean"> <property name="jobClass" value="com.imooc.springquartz.quartz.FirstScheduledJob" /> <property name="jobDataMap"> <map> <entry key="anotherBean" value-ref="anotherBean" /> </map> </property> <property name="durability" value="true"/> </bean> <!--Trigger--> <!-- (1)距离当前时间1秒之后执行,之后每隔两秒钟执行一次 --> <bean id="mySimpleTrigger" class="org.springframework.scheduling.quartz.SimpleTriggerFactoryBean"> <property name="jobDetail" ref="simpleJobDetail"/> <property name="startDelay" value="1000"/> <property name="repeatInterval" value="2000"/> </bean> <!-- (2)每隔5秒钟执行一次 --> <bean id="myCronTrigger" class="org.springframework.scheduling.quartz.CronTriggerFactoryBean"> <property name="jobDetail" ref="firstComplexJobDetail"/> <property name="cronExpression" value="0/5 * * ? * *"/> </bean> <!-- (3)Scheduler --> <bean class="org.springframework.scheduling.quartz.SchedulerFactoryBean"> <property name="jobDetails"> <list> <ref bean="simpleJobDetail"/> <ref bean="firstComplexJobDetail"/> </list> </property> <property name="triggers"> <list> <ref bean="mySimpleTrigger"/> <ref bean="myCronTrigger"/> </list> </property> </bean> 1.MyBean.java import java.text.SimpleDateFormat; import java.util.Date; import org.springframework.stereotype.Component; @Component("myBean") public class MyBean { public void printMessage() { // 打印当前的执行时间,格式为2017-01-01 00:00:00 Date date = new Date(); SimpleDateFormat sf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); System.out.println("MyBean Executes!" + sf.format(date)); } } 2.AnotherBean.java import org.springframework.stereotype.Component; @Component("anotherBean") public class AnotherBean { public void printAnotherMessage() { System.out.println("AnotherMessage"); } } 3.FirstScheduledJob.java import java.text.SimpleDateFormat; import java.util.Date; import org.quartz.JobExecutionContext; import org.quartz.JobExecutionException; import org.springframework.scheduling.quartz.QuartzJobBean; public class FirstScheduledJob extends QuartzJobBean{ private AnotherBean anotherBean; public void setAnotherBean(AnotherBean anotherBean){ this.anotherBean = anotherBean; } @Override protected void executeInternal(JobExecutionContext arg0) throws JobExecutionException { Date date = new Date(); SimpleDateFormat sf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); System.out.println("FirstScheduledJob Executes!" + sf.format(date)); this.anotherBean.printAnotherMessage(); } }

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简介Valgrind工具包功能

我就不班门弄斧了。不过呢,有可能有些同学可能不知道Valgrind有哪些功能,那么我就从Valgrind的官方网站处,摘几段文字吧。 Memcheck Memcheck detects memory-management problems, and is aimed primarily at C and C++ programs. When a program is run under Memcheck's supervision, all reads and writes of memory are checked, and calls to malloc/new/free/delete are intercepted. As a result, Memcheck can detect if your program: Accesses memory it shouldn't (areas not yet allocated, areas that have been freed, areas past the end of heap blocks, inaccessible areas of the stack). Uses uninitialised values in dangerous ways. Leaks memory. Does bad frees of heap blocks (double frees, mismatched frees). Passes overlapping source and destination memory blocks to memcpy() and related functions. Memcheck reports these errors as soon as they occur, giving the source line number at which it occurred, and also a stack trace of the functions called to reach that line. Memcheck tracks addressability at the byte-level, and initialisation of values at the bit-level. As a result, it can detect the use of single uninitialised bits, and does not report spurious errors on bitfield operations. Memcheck runs programs about 10--30x slower than normal. Cachegrind Cachegrind is a cache profiler. It performs detailed simulation of the I1, D1 and L2 caches in your CPU and so can accurately pinpoint the sources of cache misses in your code. It identifies the number of cache misses, memory references and instructions executed for each line of source code, with per-function, per-module and whole-program summaries. It is useful with programs written in any language. Cachegrind runs programs about 20--100x slower than normal. Callgrind Callgrind, by Josef Weidendorfer, is an extension to Cachegrind . It provides all the information that Cachegrind does, plus extra information about callgraphs. It was folded into the main Valgrind distribution in version 3.2.0. Available separately is an amazing visualisation tool, KCachegrind , which gives a much better overview of the data that Callgrind collects; it can also be used to visualise Cachegrind's output. Massif Massif is a heap profiler. It performs detailed heap profiling by taking regular snapshots of a program's heap. It produces a graph showing heap usage over time, including information about which parts of the program are responsible for the most memory allocations. The graph is supplemented by a text or HTML file that includes more information for determining where the most memory is being allocated. Massif runs programs about 20x slower than normal. Helgrind Helgrind is a thread debugger which finds data races in multithreaded programs. It looks for memory locations which are accessed by more than one (POSIX p-)thread, but for which no consistently used (pthread_mutex_) lock can be found. Such locations are indicative of missing synchronisation between threads, and could cause hard-to-find timing-dependent problems. It is useful for any program that uses pthreads. It is a somewhat experimental tool, so your feedback is especially welcome here. DRD DRD is a tool for detecting errors in multithreaded C and C++ programs. The tool works for any program that uses the POSIX threading primitives or that uses threading concepts built on top of the POSIX threading primitives. While Helgrind can detect locking order violations, for most programs DRD needs less memory to perform its analysis. 原文:http://valgrind.org/info/tools.html

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