Analysis of powerful Python applications

The people who initially designed the Python application did not expect that today Python will be so widely used in industry and scientific research, which greatly improves the efficiency of developers and program designers, it is also convenient for users.

Zope created with Python is the most widely used and understandable content management framework in the open source code field. This tool allows Python programmers to create and deploy highly interactive websites with less time than JSP/ASP. In this framework, website owners can easily modify website content without the intervention of programmers.

Zope has been put into practice for several years. At present, it has been widely used in Europe. Zope has also won wide popularity in the United States. The current development of Zope mainly focuses on simplifying the development process and further separating functions from the representation of content, thus increasing the Zope penetration rate, like Python, Zope is also open source software.

Zope does introduce a considerable amount of system load, which reduces the system performance during development, but some technologies can effectively minimize the problems encountered when deploying websites. When considering Enterprise Python applications, it is often ignored. This is the Python application variant Jython. Jython is fully written in Java.

Quick Development and application testing are implemented, which is much lower than the development time of Java edit-compile-test to improve the application of Java class libraries. Jython also tightly integrates Python and Java code. So that both can make full use of the advantages of the other party. This is exactly one of the goals of Microsoft. NET's CLR technology, but today it has become a reality for Python.

Disadvantages obviously, enterprise applications of Python should also take their views seriously. The main points against Python as an enterprise-level programming language are as follows:

◆ Fewer developers than other programming languages, such as Java and Python applications.

◆ Lack of real multi-processor support.

◆ Lack of commercial support.

◆ Software performance, but various evaluations repeatedly show that Python is comparable to Java in most applications ).

Of course, the lack of commercial support is a problem faced by most open source technologies. For Python, I cannot find a proper method at the moment. However. Recently, some European companies that are concerned with Python have formed a new business group, which may mark a new stage of Python development. Please refer to the Python Business Forum website ).

Most development managers seldom know Python. In a highly stressful environment in the modern IT field, the lack of understanding of Python and its tools and the lack of knowledge in software development naturally become a dead point for Python.

After all, CIOs or development directors are under heavy pressure to complete the development task. Most development managers prefer to choose what they know in the absence of specific and attractive evidence of possible benefits. So it is not surprising that few people know Python. The limitations of the database access layer are far more primitive than the existing mature technologies, such as ODBC and JDBC. This aspect is also changing.

However, the Development Department needs to smoothly join existing complex legacy data and quickly access the SQL database, which makes it difficult to show much interest in Python in a short period of time. Creating graphical user interfaces for Python applications is not complex. The Tk that comes with the Python distribution version is the most commonly used tool by Python developers. However, Tk lacks accessible and easy-to-use GUI tools.

The just-launched PythonCard project is still in the prototype phase, but may fill this gap in the future. Boa-constructor has attracted some Python programmers, but it is really complicated to use it to create a fully functional IDE.

What's worse than the lack of GUI tools is that Python almost does not support team-developed protocol tools. Java is quite rich in these tools, at least comparable to C ++. In the enterprise software development market, this defect can be seen as critical. Without such tools, it is almost impossible for many programmers to develop the same project together.

Python uses its modular and namespace analysis features to alleviate this demand. These features enable multiple programmers to develop projects without the possibility of code conflicts. However, this does not change the severity of the lack of collaborative performance.

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