什么是inotify:
- Inotify是一个事件驱动的通知机制,Inotify 提供一个简单的API,使用最小的文件描述符,并且允许细粒度监控。与 inotify 的通信是通过系统调用实现。可用的函数如下所示:
- inotify_init 是用于创建一个inotify实例的系统调用,并返回一个指向该实例的文件描述符。
- inotify_init1 与inotify_init相似,并带有附加标志。如果这些附加标志没有指定,将采用与inotify_init相同的值。
- inotify_add_watch 增加对文件或者目录的监控,并指定需要监控哪些事件。标志用于控制是否将事件添加到已有的监控中,是否只有路径代表一个目录才进行监控,是否要追踪符号链接,是否进行一次性监控,当首次事件出现后就停止监控。
- inotify_rm_watch 从监控列表中移出监控项目。
- read 读取包含一个或者多个事件信息的缓存。
- close 关闭文件描述符,并且移除所有在该描述符上的所有监控。当关于某实例的所有文件描述符都关闭时,资源和下层对象都将释放,以供内核再次使用。
因此,典型的监控程序需要进行如下操作:
- 使用 inotify_init 打开一个文件描述符
- 添加一个或者多个监控
- 等待事件
- 处理事件,然后返回并等待更多事件
- 当监控不再活动时,或者接到某个信号之后,关闭文件描述符,清空,然后退出。
pyinotify包的安装
git clone https://github.com/seb-m/pyinotify.git cd pyinotify/ python setup.py install
Inotify 可以监视的文件系统事件包括:
IN_ACCESS,即文件被访问
IN_MODIFY,文件被write
IN_ATTRIB,文件属性被修改,如chmod、chown、touch等
IN_CLOSE_WRITE,可写文件被close
IN_CLOSE_NOWRITE,不可写文件被close
IN_OPEN,文件被open
IN_MOVED_FROM,文件被移走,如mv
IN_MOVED_TO,文件被移来,如mv、cp
IN_CREATE,创建新文件
IN_DELETE,文件被删除,如rm
IN_DELETE_SELF,自删除,即一个可执行文件在执行时删除自己
IN_MOVE_SELF,自移动,即一个可执行文件在执行时移动自己
IN_UNMOUNT,宿主文件系统被umount
IN_CLOSE,文件被关闭,等同于(IN_CLOSE_WRITE | IN_CLOSE_NOWRITE)
IN_MOVE,文件被移动,等同于(IN_MOVED_FROM | IN_MOVED_TO)
pyinotify使用例子
#!/usr/bin/env python # encoding:utf-8 import os from pyinotify import WatchManager, Notifier, \ ProcessEvent,IN_DELETE, IN_CREATE,IN_MODIFY class EventHandler(ProcessEvent): """事件处理""" def process_IN_CREATE(self, event): print "Create file: %s " % os.path.join(event.path,event.name) def process_IN_DELETE(self, event): print "Delete file: %s " % os.path.join(event.path,event.name) def process_IN_MODIFY(self, event): print "Modify file: %s " % os.path.join(event.path,event.name) def FSMonitor(path='.'): wm = WatchManager() mask = IN_DELETE | IN_CREATE |IN_MODIFY notifier = Notifier(wm, EventHandler()) wm.add_watch(path, mask,auto_add=True,rec=True) print 'now starting monitor %s'%(path) while True: try: notifier.process_events() if notifier.check_events(): notifier.read_events() except KeyboardInterrupt: notifier.stop() break if __name__ == "__main__": FSMonitor('/home/firefoxbug')

TomergelistsinPython,youcanusethe operator,extendmethod,listcomprehension,oritertools.chain,eachwithspecificadvantages:1)The operatorissimplebutlessefficientforlargelists;2)extendismemory-efficientbutmodifiestheoriginallist;3)listcomprehensionoffersf

In Python 3, two lists can be connected through a variety of methods: 1) Use operator, which is suitable for small lists, but is inefficient for large lists; 2) Use extend method, which is suitable for large lists, with high memory efficiency, but will modify the original list; 3) Use * operator, which is suitable for merging multiple lists, without modifying the original list; 4) Use itertools.chain, which is suitable for large data sets, with high memory efficiency.

Using the join() method is the most efficient way to connect strings from lists in Python. 1) Use the join() method to be efficient and easy to read. 2) The cycle uses operators inefficiently for large lists. 3) The combination of list comprehension and join() is suitable for scenarios that require conversion. 4) The reduce() method is suitable for other types of reductions, but is inefficient for string concatenation. The complete sentence ends.

PythonexecutionistheprocessoftransformingPythoncodeintoexecutableinstructions.1)Theinterpreterreadsthecode,convertingitintobytecode,whichthePythonVirtualMachine(PVM)executes.2)TheGlobalInterpreterLock(GIL)managesthreadexecution,potentiallylimitingmul

Key features of Python include: 1. The syntax is concise and easy to understand, suitable for beginners; 2. Dynamic type system, improving development speed; 3. Rich standard library, supporting multiple tasks; 4. Strong community and ecosystem, providing extensive support; 5. Interpretation, suitable for scripting and rapid prototyping; 6. Multi-paradigm support, suitable for various programming styles.

Python is an interpreted language, but it also includes the compilation process. 1) Python code is first compiled into bytecode. 2) Bytecode is interpreted and executed by Python virtual machine. 3) This hybrid mechanism makes Python both flexible and efficient, but not as fast as a fully compiled language.

Useaforloopwheniteratingoverasequenceorforaspecificnumberoftimes;useawhileloopwhencontinuinguntilaconditionismet.Forloopsareidealforknownsequences,whilewhileloopssuitsituationswithundeterminediterations.

Pythonloopscanleadtoerrorslikeinfiniteloops,modifyinglistsduringiteration,off-by-oneerrors,zero-indexingissues,andnestedloopinefficiencies.Toavoidthese:1)Use'i


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

Dreamweaver CS6
Visual web development tools

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

WebStorm Mac version
Useful JavaScript development tools
