#!/usr/bin/py2
# -*- coding: utf-8 -*-
#encoding=utf-8
'''''
ftp自动下载、自动上传脚本,可以递归目录操作
'''
from ftplib import FTP
import os, sys, string, datetime, time
import socket
class FtpClient:
def __init__(self, host, user, passwd, remotedir, port=21):
self.hostaddr = host
self.username = user
self.password = passwd
self.remotedir = remotedir
self.port = port
self.ftp = FTP()
self.file_list = []
def __del__(self):
self.ftp.close()
def login(self):
ftp = self.ftp
try:
timeout = 60
socket.setdefaulttimeout(timeout)
ftp.set_pasv(True)
ftp.connect(self.hostaddr, self.port)
print 'Connect Success %s' %(self.hostaddr)
ftp.login(self.username, self.password)
print 'Login Success %s' %(self.hostaddr)
debug_print(ftp.getwelcome())
except Exception:
deal_error("Connect Error or Login Error")
try:
ftp.cwd(self.remotedir)
except(Exception):
deal_error('Change Directory Error')
def is_same_size(self, localfile, remotefile):
try:
remotefile_size = self.ftp.size(remotefile)
except:
remotefile_size = -1
try:
localfile_size = os.path.getsize(localfile)
except:
localfile_size = -1
debug_print('lo:%d re:%d' %(localfile_size, remotefile_size),)
if remotefile_size == localfile_size:
return 1
else:
return 0
def download_file(self, localfile, remotefile):
if self.is_same_size(localfile, remotefile):
return
else:
pass
file_handler = open(localfile, 'wb')
self.ftp.retrbinary('RETR %s'%(remotefile), file_handler.write)
file_handler.close()
def download_files(self, localdir='./', remotedir='./'):
try:
self.ftp.cwd(remotedir)
except:
return
if not os.path.isdir(localdir):
os.makedirs(localdir)
self.file_list = []
self.ftp.dir(self.get_file_list)
remotenames = self.file_list
for item in remotenames:
filetype = item[0]
filename = item[1]
local = os.path.join(localdir, filename)
if filetype == 'd':
self.download_files(local, filename)
elif filetype == '-':
self.download_file(local, filename)
self.ftp.cwd('..')
def upload_file(self, localfile, remotefile):
if not os.path.isfile(localfile):
return
if self.is_same_size(localfile, remotefile):
return
file_handler = open(localfile, 'rb')
self.ftp.storbinary('STOR %s' %remotefile, file_handler)
file_handler.close()
def upload_files(self, localdir='./', remotedir = './'):
if not os.path.isdir(localdir):
return
localnames = os.listdir(localdir)
self.ftp.cwd(remotedir)
for item in localnames:
src = os.path.join(localdir, item)
if os.path.isdir(src):
try:
self.ftp.mkd(item)
except:
debug_print('Directory Exists %s' %item)
self.upload_files(src, item)
else:
self.upload_file(src, item)
self.ftp.cwd('..')
def mkdir(self, remotedir='./'):
try:
self.ftp.mkd(remotedir)
except:
debug_print('Directory Exists %s' %remotedir)
def get_file_list(self, line):
ret_arr = []
file_arr = self.get_filename(line)
if file_arr[1] not in ['.', '..']:
self.file_list.append(file_arr)
def get_filename(self, line):
pos = line.rfind(':')
while(line[pos] != ' '):
pos += 1
while(line[pos] == ' '):
pos += 1
file_arr = [line[0], line[pos:]]
return file_arr
def debug_print(str):
print (str)
def deal_error(e):
timenow = time.localtime()
datenow = time.strftime('%Y-%m-%d', timenow)
logstr = '%s Error: %s' %(datenow, e)
debug_print(logstr)
file.write(logstr)
sys.exit()

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version
Visual web development tools

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

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

WebStorm Mac version
Useful JavaScript development tools