代码实例:
try:
import termios, TERMIOS 1
except ImportError:
try:
import msvcrt 2
except ImportError:
try:
from EasyDialogs import AskPassword 3
except ImportError:
getpass = "default_getpass" 4
else:
getpass = "AskPassword" 5
else:
getpass = "win_getpass"
else:
getpass = "unix_getpass"
1:termios 是 UNIX 独有的一个模块,它提供了对于输入终端的底层控制。如果这个模块无效 (因为它不在你的系统上,或你的系统不支持它),则导入失败,Python 引发我们捕捉的 ImportError 异常。
2:OK,我们没有 termios,所以让我们试试 msvcrt,它是 Windows 独有的一个模块,可以提供在 Microsoft Visual C++ 运行服务中的许多有用的函数的一个API。如果导入失败,Python 会引发我们捕捉的 ImportError 异常。
3:如果前两个不能工作,我们试着从 EasyDialogs 导入一个函数,它是 Mac OS 独有的一个模块,提供了各种各样类型的弹出对话框。再一次,如果导入失败,Python 会引发一个我们捕捉的 ImportError 异常。
4:这些平台特定的模块没有一个有效 (有可能,因为 Python 已经移植到了许多不同的平台上了),所以我们需要回头使用一个缺省口令输入函数 (这个函数定义在 getpass 模块中的别的地方)。注意我们在这里所做的:我们将函数 default_getpass 赋给变量 getpass。如果你读了官方 getpass 文档,它会告诉你 getpass 模块定义了一个 getpass 函数。它是这样做的:通过绑定 getpass 到正确的函数来适应你的平台。然后当你调用 getpass 函数时,你实际上调用了平台特定的函数,是这段代码已经为你设置好的。你不需要知道或关心你的代码正运行在何种平台上;只要调用 getpass,则它总能正确处理。
5:一个 try...except 块可以有一条 else 子句,就像 if 语句。如果在 try 块中没有异常引发,然后 else 子句被执行。在本例中,那就意味着如果 from EasyDialogs import AskPassword 导入可工作,所以我们应该绑定 getpass 到 AskPassword 函数。其它每个 try...except 块有着相似的 else 子句,当我们发现一个 import 可用时,就绑定 getpass 到适合的函数。

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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