


In fact, Django comes with a built-in lightweight web server that can be used during site development. We provide this server to allow you to quickly develop your site, which means there is no need to configure a production-level web server (such as Apache) before you are ready to release the product.
But in actual development, instead of one person developing, multiple people need to be able to access this machine. So how do we configure it? Let’s take a look:
1. Create a web project
Run the
django-admin.py startproject pytab
command to create a pytab directory in the current directory.
Note:
If you have a PHP programming background, you may be accustomed to placing your code in the document root directory of the Web server (such as /var/www). In Django, you can't do this. It's not a good idea to put any Python code in the document root of your web server because you run the risk of someone seeing the code directly through the page. This is not a good thing for security. So, place the code in some directory outside of the document root.
2. Run the built-in server
and let it run so that we can access
If you are not already in the mysite directory, go into it now and run the python manage.py runserver command. You will see the following output:
Validating models...
0 errors found
Django version 1.4.3, using settings 'mysite.settings'
Development server is running at http://127.0.0.1:8000 /
Quit the server with CONTROL-C.
After the above prompt appears, it will be in a waiting state. When an access comes in, some user access information will appear. For example:
[11/Jan/2013 00:47:58] "GET / HTTP/1.1" 200 1957
200 Description The request is successful, 1957 represents the size of the sent data, the unit is B.
Although this development server is great for development, be sure to avoid the idea of using this server in a production-level environment. The server could only reliably handle a single request once at a time and was not subject to any kind of security auditing.
But in actual development, instead of one person developing, multiple people need to be able to access this machine. Django thinks of this problem for us. You can use the runserver command to solve this problem:
1. Change the listening port.
If you want to change the server port, you can pass the port as a command line parameter:
python manage.py runserver 8070
2. You can also change the IP address that the server monitors. This feature is especially useful if you want to share the same development site with other developers. The following command:
python manage.py runserver 0.0.0.0:8000
will cause Django to listen on all network interfaces and IP addresses, thus allowing other computers to connect to the development server.
Now that the server is running, you can now access http://192.168.1.111:8000/ using a web browser on other computers.

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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