python开发之基于thread线程搜索本地文件的方法
本文实例讲述了python开发之基于thread线程搜索本地文件的方法。分享给大家供大家参考,具体如下:
先来看看运行效果图:
利用多个线程处理搜索的问题,我们可以发现他很快....
下面是代码部分:
# A parallelized "find(1)" using the thread module. # This demonstrates the use of a work queue and worker threads. # It really does do more stats/sec when using multiple threads, # although the improvement is only about 20-30 percent. # (That was 8 years ago. In 2002, on Linux, I can't measure # a speedup. :-( ) # I'm too lazy to write a command line parser for the full find(1) # command line syntax, so the predicate it searches for is wired-in, # see function selector() below. (It currently searches for files with # world write permission.) # Usage: parfind.py [-w nworkers] [directory] ... # Default nworkers is 4 import sys import getopt import time import os from stat import * import _thread as thread # Work queue class. Usage: # wq = WorkQ() # wq.addwork(func, (arg1, arg2, ...)) # one or more calls # wq.run(nworkers) # The work is done when wq.run() completes. # The function calls executed by the workers may add more work. # Don't use keyboard interrupts! class WorkQ: # Invariants: # - busy and work are only modified when mutex is locked # - len(work) is the number of jobs ready to be taken # - busy is the number of jobs being done # - todo is locked iff there is no work and somebody is busy def __init__(self): self.mutex = thread.allocate() self.todo = thread.allocate() self.todo.acquire() self.work = [] self.busy = 0 def addwork(self, func, args): job = (func, args) self.mutex.acquire() self.work.append(job) self.mutex.release() if len(self.work) == 1: self.todo.release() def _getwork(self): self.todo.acquire() self.mutex.acquire() if self.busy == 0 and len(self.work) == 0: self.mutex.release() self.todo.release() return None job = self.work[0] del self.work[0] self.busy = self.busy + 1 self.mutex.release() if len(self.work) > 0: self.todo.release() return job def _donework(self): self.mutex.acquire() self.busy = self.busy - 1 if self.busy == 0 and len(self.work) == 0: self.todo.release() self.mutex.release() def _worker(self): time.sleep(0.00001) # Let other threads run while 1: job = self._getwork() if not job: break func, args = job func(*args) self._donework() def run(self, nworkers): if not self.work: return # Nothing to do for i in range(nworkers-1): thread.start_new(self._worker, ()) self._worker() self.todo.acquire() # Main program def main(): nworkers = 4 #print(getopt.getopt(sys.argv[1:], '-w:')) opts, args = getopt.getopt(sys.argv[1:], '-w:') for opt, arg in opts: if opt == '-w': nworkers = int(arg) if not args: #print(os.curdir) args = [os.curdir] wq = WorkQ() for dir in args: wq.addwork(find, (dir, selector, wq)) t1 = time.time() wq.run(nworkers) t2 = time.time() sys.stderr.write('Total time %r sec.\n' % (t2-t1)) # The predicate -- defines what files we look for. # Feel free to change this to suit your purpose def selector(dir, name, fullname, stat): # Look for world writable files that are not symlinks return (stat[ST_MODE] & 0o002) != 0 and not S_ISLNK(stat[ST_MODE]) # The find procedure -- calls wq.addwork() for subdirectories def find(dir, pred, wq): try: names = os.listdir(dir) except os.error as msg: print(repr(dir), ':', msg) return for name in names: if name not in (os.curdir, os.pardir): fullname = os.path.join(dir, name) try: stat = os.lstat(fullname) except os.error as msg: print(repr(fullname), ':', msg) continue if pred(dir, name, fullname, stat): print(fullname) if S_ISDIR(stat[ST_MODE]): if not os.path.ismount(fullname): wq.addwork(find, (fullname, pred, wq)) # Call the main program main()
希望本文所述对大家Python程序设计有所帮助。

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

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

To run Python code in Sublime Text, you need to install the Python plug-in first, then create a .py file and write the code, and finally press Ctrl B to run the code, and the output will be displayed in the console.

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.

Writing code in Visual Studio Code (VSCode) is simple and easy to use. Just install VSCode, create a project, select a language, create a file, write code, save and run it. The advantages of VSCode include cross-platform, free and open source, powerful features, rich extensions, and lightweight and fast.

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".
