在使用Python多年之后,我偶然发现了一些咱们过去不知道的功能和特性。一些能够说是很是有用,但却没有充分利用。考虑到这一点,我编辑了一些的你应该了解的Pyghon功能特点。html
带任意数量参数的函数
你可能已经知道了Python容许你定义可选参数。但还有一个方法,能够定义函数任意数量的参数。python
首先,看下面是一个只定义可选参数的例子数据库
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def function(arg1 = " ",arg2=" "): |
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print "arg1: {0}" . format (arg1) |
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print "arg2: {0}" . format (arg2) |
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function( "Hello" , "World" ) |
如今,让咱们看看怎么定义一个能够接受任意参数的函数。咱们利用元组来实现。json
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def foo( * args): # just use "*" to collect all remaining arguments into a tuple |
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print "Number of arguments: {0}" . format (numargs) |
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for i, x in enumerate (args): |
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print "Argument {0} is: {1}" . format (i,x) |
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# Number of arguments: 0 |
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# Number of arguments: 1 |
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# Argument 0 is: hello |
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foo( "hello" , "World" , "Again" ) |
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# Number of arguments: 3 |
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# Argument 0 is: hello |
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# Argument 1 is: World |
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# Argument 2 is: Again |
使用Glob()查找文件
大多Python函数有着长且具备描述性的名字。可是命名为glob()的函数你可能不知道它是干什么的除非你从别处已经熟悉它了。
它像是一个更强大版本的listdir()函数。它可让你经过使用模式匹配来搜索文件。api
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files = glob.glob( '*.py' ) |
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# ['arg.py', 'g.py', 'shut.py', 'test.py'] |
你能够像下面这样查找多个文件类型:数组
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import itertools as it, glob |
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def multiple_file_types( * patterns): |
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return it.chain.from_iterable(glob.glob(pattern) for pattern in patterns) |
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for filename in multiple_file_types( "*.txt" , "*.py" ): # add as many filetype arguements |
若是你想获得每一个文件的绝对路径,你能够在返回值上调用realpath()函数:app
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import itertools as it, glob, os |
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def multiple_file_types( * patterns): |
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return it.chain.from_iterable(glob.glob(pattern) for pattern in patterns) |
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for filename in multiple_file_types( "*.txt" , "*.py" ): # add as many filetype arguements |
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realpath = os.path.realpath(filename) |
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# C:\xxx\pyfunc\test.txt |
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# C:\xxx\pyfunc\arg.py |
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# C:\xxx\pyfunc\shut.py |
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# C:\xxx\pyfunc\test.py |
调试
下面的例子使用inspect模块。该模块用于调试目的时是很是有用的,它的功能远比这里描述的要多。函数
这篇文章不会覆盖这个模块的每一个细节,但会展现给你一些用例。ui
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import logging, inspect |
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logging.basicConfig(level = logging.INFO, |
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format = '%(asctime)s %(levelname)-8s %(filename)s:%(lineno)-4d: %(message)s' , |
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datefmt = '%m-%d %H:%M' , |
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logging.debug( 'A debug message' ) |
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logging.info( 'Some information' ) |
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logging.warning( 'A shot across the bow' ) |
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frame,filename,line_number,function_name,lines,index = \ |
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inspect.getouterframes(inspect.currentframe())[ 1 ] |
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print (frame,filename,line_number,function_name,lines,index) |
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# Should print the following (with current date/time of course) |
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#10-19 19:57 INFO test.py:9 : Some information |
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#10-19 19:57 WARNING test.py:10 : A shot across the bow |
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#(, 'C:/xxx/pyfunc/magic.py', 16, '', ['test()\n'], 0) |
生成惟一ID
在有些状况下你须要生成一个惟一的字符串。我看到不少人使用md5()函数来达到此目的,但它确实不是以此为目的。
其实有一个名为uuid()的Python函数是用于这个目的的。spa
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# output => various attempts |
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# 9e177ec0-65b6-11e3-b2d0-e4d53dfcf61b |
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# be57b880-65b6-11e3-a04d-e4d53dfcf61b |
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# c3b2b90f-65b6-11e3-8c86-e4d53dfcf61b |
你可能会注意到,即便字符串是惟一的,但它们后边的几个字符看起来很类似。这是由于生成的字符串与电脑的MAC地址是相联系的。
为了减小重复的状况,你可使用这两个函数。
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print hmac.new(key, data, hashlib.sha256).hexdigest() |
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m.update( "The quick brown fox jumps over the lazy dog" ) |
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# c6e693d0b35805080632bc2469e1154a8d1072a86557778c27a01329630f8917 |
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# 2fd4e1c67a2d28fced849ee1bb76e7391b93eb12 |
序列化
你曾经须要将一个复杂的变量存储在数据库或文本文件中吧?你不须要想一个奇特的方法将数组或对象格转化为式化字符串,由于Python已经提供了此功能。
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variable = [ 'hello' , 42 , [ 1 , 'two' ], 'apple' ] |
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file = open ( 'serial.txt' , 'w' ) |
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serialized_obj = pickle.dumps(variable) |
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file .write(serialized_obj) |
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# unserialize to produce original content |
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target = open ( 'serial.txt' , 'r' ) |
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myObj = pickle.load(target) |
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# ['hello', 42, [1, 'two'], 'apple'] |
这是一个原生的Python序列化方法。然而近几年来JSON变得流行起来,Python添加了对它的支持。如今你可使用JSON来编解码。
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variable = [ 'hello' , 42 , [ 1 , 'two' ], 'apple' ] |
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print "Original {0} - {1}" . format (variable, type (variable)) |
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encode = json.dumps(variable) |
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print "Encoded {0} - {1}" . format (encode, type (encode)) |
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decoded = json.loads(encode) |
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print "Decoded {0} - {1}" . format (decoded, type (decoded)) |
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# Original ['hello', 42, [1, 'two'], 'apple'] - <type 'list'="" style="word-wrap: break-word;"> |
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# Encoded ["hello", 42, [1, "two"], "apple"] - <type 'str'="" style="word-wrap: break-word;"> |
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# Decoded [u'hello', 42, [1, u'two'], u'apple'] - <type 'list'="" style="word-wrap: break-word;"> |
这样更紧凑,并且最重要的是这样与JavaScript和许多其余语言兼容。然而对于复杂的对象,其中的一些信息可能丢失。
压缩字符
当谈起压缩时咱们一般想到文件,好比ZIP结构。在Python中能够压缩长字符,不涉及任何档案文件。
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string = """ Lorem ipsum dolor sit amet, consectetur |
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adipiscing elit. Nunc ut elit id mi ultricies |
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adipiscing. Nulla facilisi. Praesent pulvinar, |
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sapien vel feugiat vestibulum, nulla dui pretium orci, |
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non ultricies elit lacus quis ante. Lorem ipsum dolor |
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sit amet, consectetur adipiscing elit. Aliquam |
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pretium ullamcorper urna quis iaculis. Etiam ac massa |
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sed turpis tempor luctus. Curabitur sed nibh eu elit |
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mollis congue. Praesent ipsum diam, consectetur vitae |
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ornare a, aliquam a nunc. In id magna pellentesque |
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tellus posuere adipiscing. Sed non mi metus, at lacinia |
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augue. Sed magna nisi, ornare in mollis in, mollis |
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sed nunc. Etiam at justo in leo congue mollis. |
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Nullam in neque eget metus hendrerit scelerisque |
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eu non enim. Ut malesuada lacus eu nulla bibendum |
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id euismod urna sodales. """ |
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print "Original Size: {0}" . format ( len (string)) |
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compressed = zlib.compress(string) |
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print "Compressed Size: {0}" . format ( len (compressed)) |
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decompressed = zlib.decompress(compressed) |
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print "Decompressed Size: {0}" . format ( len (decompressed)) |
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# Compressed Size: 423 |
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# Decompressed Size: 1022 |
注册Shutdown函数
有可模块叫atexit,它可让你在脚本运行完后立马执行一些代码。
假如你想在脚本执行结束时测量一些基准数据,好比运行了多长时间:
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def microtime(get_as_float = False ) : |
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return '%f %d' % math.modf(time.time()) |
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start_time = microtime( False ) |
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atexit.register(start_time) |
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print "Execution took: {0} seconds" . format (start_time) |
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atexit.register(shutdown) |
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# Execution took: 0.297000 1387135607 seconds |
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# Error in atexit._run_exitfuncs: |
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# Traceback (most recent call last): |
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# File "C:\Python27\lib\atexit.py", line 24, in _run_exitfuncs |
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# func(*targs, **kargs) |
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# TypeError: 'str' object is not callable |
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# Error in sys.exitfunc: |
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# Traceback (most recent call last): |
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# File "C:\Python27\lib\atexit.py", line 24, in _run_exitfuncs |
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# func(*targs, **kargs) |
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# TypeError: 'str' object is not callable |
打眼看来很简单。只须要将代码添加到脚本的最底层,它将在脚本结束前运行。但若是脚本中有一个致命错误或者脚本被用户终止,它可能就不运行了。
当你使用atexit.register()时,你的代码都将执行,不论脚本由于什么缘由中止运行