


Preface
To implement this function, all you need is to pause the program, wait and capture a keyboard input from the user, and then continue execution. Python has built-in libraries that can help us implement this function, but Windows and Linux must be treated differently. The
getch() method in msvcrt
can help to implement it under Windows. Its function is to obtain a key response and return the corresponding character. It is not echoed on the command line. There is the following program segment:
import msvcrt print ord(msvcrt.getch())
Here, ord
is used to convert the obtained characters into ASCII
values, such as capture Pressing the "d" key (note the lower case) will give you the value 100.
What about Linux? Well, it’s a little bit complicated, but it’ll be easier if you clarify your thoughts first.
First of all, you need to know the three modes of Linux terminal, which are standard mode, non-standard mode and raw mode:
Normal mode
Normal mode, also known as cooked
mode, is a common mode for users. Characters entered by the driver are saved in a buffer, and these buffered characters are only sent to the program when the Enter key is received. Buffered data allows the driver to implement the most basic editing functions. The specific keys assigned to these functions are set in the driver and can be modified through the command stty
or the system call tcsetattr
.
Non-canonical mode
When the buffering and editing functions are turned off, the connection is placed in non-canonical mode. The terminal processor still performs specific character processing, such as handling conversions between Ctrl-C and newline characters, but the edit keys will have no meaning, so the corresponding input is treated as regular data input, and the program needs to implement the editing function itself.
raw mode
When all processing is turned off and the driver passes input directly to the program, the connection is called raw
mode.
Here we need to resort to non-canonical mode, so to achieve similar behavior on Windows just now, we need the following code:
import os import termios # 获取标准输入的描述符 fd = sys.stdin.fileno() # 获取标准输入(终端)的设置 old_ttyinfo = termios.tcgetattr(fd) # 配置终端 new_ttyinfo = old_ttyinfo[:] # 使用非规范模式(索引3是c_lflag 也就是本地模式) new_ttyinfo[3] &= ~termios.ICANON # 关闭回显(输入不会被显示) new_ttyinfo[3] &= ~termios.ECHO # 使设置生效 termios.tcsetattr(fd, termios.TCSANOW, new_ttyinfo) # 从终端读取 print ord(os.read(fd, 7))
Therefore It seems that we only need to use the above method to capture a key response, and then continue the program to achieve the function of pressing any key to continue or exit. Of course, the function of pressing a specified key to continue or exit can also be implemented in a similar way, for example:
import msvcrt print("Press 'D' to exit...") while True: if ord(msvcrt.getch()) in [68, 100]: break
In this way, when the user presses "D" or "d", the program exits.
For more Python related articles about the function of pressing any key to continue/exit, please pay attention to the PHP Chinese website!

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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