所有文件都包含在各个不同的目录下,不过Python也能轻松处理。os模块有许多方法能帮你创建,删除和更改目录。
mkdir()方法
可以使用os模块的mkdir()方法在当前目录下创建新的目录们。你需要提供一个包含了要创建的目录名称的参数。
语法:
os.mkdir("newdir")
例子:
下例将在当前目录下创建一个新目录test。
#!/usr/bin/python # -*- coding: UTF-8 -*- import os # 创建目录test os.mkdir("test")
chdir()方法
可以用chdir()方法来改变当前的目录。chdir()方法需要的一个参数是你想设成当前目录的目录名称。
语法:
os.chdir("newdir")
例子:
下例将进入"/home/newdir"目录。
#!/usr/bin/python # -*- coding: UTF-8 -*- import os # 将当前目录改为"/home/newdir" os.chdir("/home/newdir")
getcwd()方法:
getcwd()方法显示当前的工作目录。
语法:
os.getcwd()
例子:
下例给出当前目录:
#!/usr/bin/python # -*- coding: UTF-8 -*- import os # 给出当前的目录 os.getcwd()
rmdir()方法
rmdir()方法删除目录,目录名称以参数传递。
在删除这个目录之前,它的所有内容应该先被清除。
语法:
os.rmdir('dirname')
例子:
以下是删除" /tmp/test"目录的例子。目录的完全合规的名称必须被给出,否则会在当前目录下搜索该目录。
#!/usr/bin/python # -*- coding: UTF-8 -*- import os # 删除”/tmp/test”目录 os.rmdir( "/tmp/test" )

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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

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.


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