


Preface
Everyone’s format when writing a script will be different. Some will indicate some information about the script itself, while others will get straight to the point. In fact, there is nothing in the team. You basically know what others do, but if you put it into a large team, it will be more troublesome, because as the number of people increases, the script grows exponentially. If everyone’s style is not unified, it will cause problems in the end. It is a very big disadvantage, so when the number of people in the team increases, there must be a set of standards to form unified coding rules for everyone, so that even if you don't see the specific implementation of the script, you know what the function of the script is.
The script we share today is a script that automatically adds comment information. The added information includes script name, author, time, description, script usage, language version, remarks, etc. Let’s look at the sample code
#!/usr/bin/env python from os.path import exists from time import strftime import os title = raw_input("Enter a title for your script: ") title = title + '.py' title = title.lower() title = title.replace(' ', '_') if exists(title): print "\nA script with this name already exists." exit(1) descrpt = raw_input("Enter a description: ") name = raw_input("Enter your name: ") ver = raw_input("Enter the version number: ") p = '=======================================' filename = open(title, 'w') date = strftime("%Y%m%d") filename.write('#!/usr/bin/python') filename.write('\n#title\t\t\t:' + title) filename.write('\n#description\t\t:' + descrpt) filename.write('\n#author\t\t\t:' + name) filename.write('\n#date\t\t\t:' + date) filename.write('\n#version\t\t:' + ver) filename.write('\n#usage\t\t\t:' + 'python ' + title) filename.write('\n#notes\t\t\t:') filename.write('\n#python_version\t\t:2.6.6') filename.write('\n#' + p * 2 + '\n') filename.write('\n') filename.write('\n') filename.close() os.system("clear") os.system("vim +12 " + title) exit()
I won’t explain too much about the script. It basically gets the information and writes it into a file. No more nonsense. This script is simple enough. Let’s do it last. Take a look at the generated results:
#!/usr/bin/python #title :test4.py #description :I am test script #author :python技术 #date :20160902 #version :0.1 #usage :python test4.py #notes : #python_version :2.6.6 #==============================================================================
Summary
Everyone think about it, if every There is this basic information in front of each script. It will look much clearer. Finally, I hope this script can bring some help to everyone. Of course, if you have any questions, you can leave a message to communicate. Thank you for your support to the PHP Chinese website.
For more articles related to Python's automatic addition of script header information, please pay attention to the PHP Chinese website!

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.


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