本文实例讲述了Python通过正则表达式选取callback的方法。分享给大家供大家参考。具体如下:
最近在瞎想怎么通过xpath去精确抓取文章的正文,跟parselets类似的想法,只不过更简单。
代码设计上采用正则表达式匹配URL,再选择callback handler的方式,主要参考web.py的分发器(Dispatcher)。
当然,这个实现比较老土一些,全部用function的方式回调,没有用类。
#!/bin/env python import re, sys # Define parser first. def baidu(username): # Business logic return "Using parser Baidu. and the user's name is: %s." % username def qzone(uin): # Business logic return "Using parser Qzone, and the user's QQ is: %s." % uin # From web.py def group(seq, size):#{{{ """ Returns an iterator over a series of lists of length size from iterable. >>> list(group([1,2,3,4], 2)) [[1, 2], [3, 4]] >>> list(group([1,2,3,4,5], 2)) [[1, 2], [3, 4], [5]] """ def take(seq, n): for i in xrange(n): yield seq.next() if not hasattr(seq, 'next'): seq = iter(seq) while True: x = list(take(seq, size)) if x: yield x else: break #}}} def parser_init(url,mapping): for pat, what in group(mapping,2): result = re.compile('^' + pat + '$').match(url) if result: return what, [x for x in result.groups()] return None, None if __name__ == '__main__': mapping = ( 'http://(?:hi|space).baidu.com/([^/]+)(?:/.*)?','baidu', 'http://(\d+).qzone.qq.com(?:/.*)?','qzone', ) (func, args) = parser_init(sys.argv[1],mapping) if func: callback = func if func in globals(): callback = globals()[func] if callable(callback): print callback(*args) else: print 'No parser found.';
希望本文所述对大家的Python程序设计有所帮助。

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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.


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