python合并文本文件示例代码。
python实现两个文本合并
employee文件中记录了工号和姓名
cat employee.txt:
100 Jason Smith 200 John Doe 300 Sanjay Gupta 400 Ashok Sharma
bonus文件中记录工号和工资
cat bonus.txt:
100 $5,000 200 $500 300 $3,000 400 $1,250
要求把两个文件合并并输出如下, 处理结果:
400 ashok sharma $1,250 100 jason smith $5,000 200 john doe $500 300 sanjay gupta $3,000
这个应该是要求用shell来写的,但我的shell功底不怎么样,就用python来实现了
注意,按题目的意思,在输出文件中还需要按照姓名首字母来排序的
#! /usr/bin/env python #coding=utf-8 fp01=open("bonus.txt","r") a=[] for line01 in fp01: a.append(line01) fp02=open("employee.txt","r") fc02=sorted(fp02,key=lambda x:x.split()[1]) for line02 in fc02: i=0 while line02.split()[0]!=a[i].split()[0]: i+=1 print "%s %s %s %s" % (line02.split()[0],line02.split()[1],line02.split()[2],a[i].split()[1]) fp01.close() fp02.close()
我们再来看一段同样功能的 代码
# coding gbk # # author: GreatGhoul # email : greatghoul@gmail.com # blog : http://greatghoul.javaeye.com import sys,os,msvcrt def join(in_filenames, out_filename): out_file = open(out_filename, 'w+') err_files = [] for file in in_filenames: try: in_file = open(file, 'r') out_file.write(in_file.read()) out_file.write('\n\n') in_file.close() except IOError: print 'error joining', file err_files.append(file) out_file.close() print 'joining completed. %d file(s) missed.' % len(err_files) print 'output file:', out_filename if len(err_files) > 0: print 'missed files:' print '--------------------------------' for file in err_files: print file print '--------------------------------' if __name__ == '__main__': print 'scanning...' in_filenames = [] file_count = 0 for file in os.listdir(sys.path[0]): if file.lower().endswith('[all].txt'): os.remove(file) elif file.lower().endswith('.txt'): in_filenames.append(file) file_count = file_count + 1 if len(in_filenames) > 0: print '--------------------------------' print '\n'.join(in_filenames) print '--------------------------------' print '%d part(s) in total.' % file_count book_name = raw_input('enter the book name: ') print 'joining...' join(in_filenames, book_name + '[ALL].TXT') else: print 'nothing found.' msvcrt.getch()
最后我们再来看一个小编遇到的情况:
今天汇编的时候在阿甘的博客里面看到了一部小说《疯狂的程序员》,于是网上搜了下准备放到手机里闲时看看,无奈下载后发现是分章节的txt文本,一共有87个文件,考虑到阅读起来不是很方便,于是想找个现成的工具合并txt文本。
结果尝试了几个工具后觉得合并效果都不给力啊,于是打算自己动手。其实cmd的命令"type *.txt >> crazy-programmer.txt"还是很有效果的,然而合并后的txt文件却十分庞大,所以我还是自己写了一个脚本完成了合并。
说明:由于我下载的87个txt文件的字符编码格式都不统一,所以我用chardet模块判断字符编码类型后再用codecs模块的codecs.open功能解决了编码问题。如果直接用file的open打开txt文件的话,在UCS-2 Little Endian的编码情况下,file.read()遇到中文的冒号(即“:”)后会无法读取冒号以后的内容,所以需要用codecs.open(path,'r',encoding)来解决。
如果还有问题可以留言,代码如下:
#!coding: cp936 import codecs, chardet def fileopen(filename): f = open(filename, 'r') s = f.read() if(chardet.detect(s)['encoding'] == 'UTF-16LE'): f.close() f = codecs.open(filename, 'r', 'utf-16-le') data = f.read().encode('gb2312', 'ignore') f.close() elif(chardet.detect(s)['encoding'] == 'GB2312'): data = s f.close() return data i = 1 while i <=87: if(i < 10): filename = '0'+str(i)+'.txt' else: filename = str(i)+'.txt' text = fileopen(filename) file('crazy-p.txt', 'a+').write(text) i = i+1
其中,chardet模块需要下载安装,脚本还可以改进以适应更多种情况,我就懒了。

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

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

SublimeText3 Linux new version
SublimeText3 Linux latest version

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

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

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