ipython的使用
地址:https://ipython.org/install.html
简单的安装方法:pip install ipython
一些方便的使用方法:
- 输入要查看的对象,然后输入一个问号可以查看API,输入两个问号可以查看代码
- 可以直接调用shell命令,在前面带上!即可
- 按Tab可以自动语法补全
- 最近的命令输出结果,可以从_、__、___三个变量获得
- %hist或者%history查看历史命令
- %timeit可以进行命令的执行时间测试
数据结构与算法
列表生成器
In [5]: a=[1,2,3] In [6]: [x*x for x in a if x>1] Out[6]: [4, 9]
集合生成器(和列表生成器相同)
In [7]: a=[1,2,3] In [8]: s = {x*x for x in a if x>1} In [9]: s Out[9]: {4, 9} In [10]: type(s) Out[10]: set
字典生成器
In [11]: a=[1,2,3] In [12]: {str(x):x+1 for x in a if x>1} Out[12]: {'2': 3, '3': 4}
range和xrange的使用
In [13]: range? Docstring: range(stop) -> list of integers range(start, stop[, step]) -> list of integers In [14]: range(10) Out[14]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] In [15]: range(3,10) Out[15]: [3, 4, 5, 6, 7, 8, 9] In [16]: xrange? Docstring: xrange(stop) -> xrange object xrange(start, stop[, step]) -> xrange object In [19]: list(xrange(3,10)) Out[19]: [3, 4, 5, 6, 7, 8, 9] In [21]: list(xrange(10)) Out[21]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
range和xrange的用法相同,只是range会直接生成一个内存列表,xrange会生成一个生产器,xrange的效率更高,更节省内存
filter用于过滤数据
In [22]: filter? Docstring: filter(function or None, sequence) -> list, tuple, or string Return those items of sequence for which function(item) is true. If function is None, return the items that are true. If sequence is a tuple or string, return the same type, else return a list. Type: builtin_function_or_method In [23]: filter(lambda x:x%3==0, xrange(10)) Out[23]: [0, 3, 6, 9]
使用collections.namedtuple给列表或者元组命名
In [24]: from collections import namedtuple In [30]: Point = namedtuple('Point', ['x', 'y']) In [31]: p = Point(11, 22) In [32]: p.__dict__ Out[32]: OrderedDict([('x', 11), ('y', 22)]) In [33]: p.x Out[33]: 11 In [34]: p.y Out[34]: 22
random的使用
In [35]: from random import randint In [36]: randint? Signature: randint(a, b) Docstring: Return random integer in range [a, b], including both end points. File: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/random.py Type: instancemethod In [37]: randint(1,10) Out[37]: 2
统计序列元素的频度和TOP N
In [42]: from collections import Counter In [43]: Counter? In [44]: c = Counter('aaabbbbccccccddddddeeeeee') In [45]: c Out[45]: Counter({'a': 3, 'b': 4, 'c': 6, 'd': 6, 'e': 6}) In [46]: c.most_common(3) Out[46]: [('c', 6), ('e', 6), ('d', 6)]
将字典按value排序
In [47]: from random import randint In [48]: keys = 'abcdefg' In [50]: d = {x:randint(90,100) for x in keys} In [51]: d Out[51]: {'a': 90, 'b': 100, 'c': 94, 'd': 97, 'e': 94, 'f': 95, 'g': 91} In [53]: d.items() Out[53]: [('a', 90), ('c', 94), ('b', 100), ('e', 94), ('d', 97), ('g', 91), ('f', 95)] In [54]: sorted? Docstring: sorted(iterable, cmp=None, key=None, reverse=False) --> new sorted list Type: builtin_function_or_method In [55]: sorted(d.items(), key=lambda x : x[1]) Out[55]: [('a', 90), ('g', 91), ('c', 94), ('e', 94), ('f', 95), ('d', 97), ('b', 100)]
获得多个词典的key的交集
In [99]: from random import randint, sample In [100]: dd1 = {x:randint(90,100) for x in sample('abcdefghij', 5)} In [101]: dd2 = {x:randint(90,100) for x in sample('abcdefghij', 5)} In [102]: dd3 = {x:randint(90,100) for x in sample('abcdefghij', 5)} In [103]: dd1 Out[103]: {'b': 100, 'c': 97, 'd': 100, 'e': 97, 'f': 92} In [104]: dd2 Out[104]: {'a': 100, 'c': 90, 'g': 93, 'h': 93, 'j': 90} In [105]: dd3 Out[105]: {'c': 96, 'e': 93, 'f': 91, 'h': 97, 'j': 90} In [106]: mp = map(dict.viewkeys, (dd1, dd2, dd3)) In [107]: mp Out[107]: [dict_keys(['c', 'b', 'e', 'd', 'f']), dict_keys(['a', 'h', 'c', 'j', 'g']), dict_keys(['h', 'c', 'j', 'e', 'f'])] In [108]: reduce(lambda x,y: x&y, mp) Out[108]: {'c'}
怎样让字典按照插入有序
In [122]: from collections import OrderedDict In [123]: d = OrderedDict() In [124]: d['x'] = 1 In [125]: d['y'] = 2 In [126]: d['a'] = 2 In [127]: d['b'] = 2 In [128]: d Out[128]: OrderedDict([('x', 1), ('y', 2), ('a', 2), ('b', 2)])
怎样实现长度为N的队列功能
In [138]: from collections import deque In [139]: deque? Docstring: deque([iterable[, maxlen]]) --> deque object Build an ordered collection with optimized access from its endpoints. File: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/collections.py Type: type In [141]: d = deque([], 3) In [142]: d.append(1) In [143]: d.append(2) In [144]: d.append(3) In [145]: d.append(4) In [146]: d Out[146]: deque([2, 3, 4])
迭代器
怎样齐头并进并行的遍历多个集合
In [147]: names = [x for x in 'abcdefg'] In [148]: ages = [x for x in range(21, 28)] In [149]: scores = [randint(90,100) for x in range(7)] In [150]: names Out[150]: ['a', 'b', 'c', 'd', 'e', 'f', 'g'] In [151]: ages Out[151]: [21, 22, 23, 24, 25, 26, 27] In [152]: scores Out[152]: [93, 90, 95, 97, 91, 93, 92] In [153]: In [153]: zip? Docstring: zip(seq1 [, seq2 [...]]) -> [(seq1[0], seq2[0] ...), (...)] Return a list of tuples, where each tuple contains the i-th element from each of the argument sequences. The returned list is truncated in length to the length of the shortest argument sequence. Type: builtin_function_or_method In [154]: for name,age,score in zip(names, ages, scores): ...: print name,age,score ...: a 21 93 b 22 90 c 23 95 d 24 97 e 25 91 f 26 93 g 27 92
怎样串行的遍历多个集合
In [158]: lista = (randint(60,70) for x in range(10)) In [159]: list(lista) Out[159]: [65, 60, 62, 64, 63, 60, 68, 67, 61, 62] In [160]: listb = [randint(90,100) for x in range(20)] In [161]: listb Out[161]: [98, 96, 97, 98, 95, 95, 90, 99, 92, 92, 99, 92, 100, 95, 100, 100, 93, 91, 92, 98] In [163]: from itertools import chain In [164]: chain? Docstring: chain(*iterables) --> chain object Return a chain object whose .next() method returns elements from the first iterable until it is exhausted, then elements from the next iterable, until all of the iterables are exhausted. File: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/lib-dynload/itertools.so Type: type In [165]: for x in chain(lista, listb): ...: print x, ...: 98 96 97 98 95 95 90 99 92 92 99 92 100 95 100 100 93 91 92 98
字符串
使用多种分隔符拆分字符串
In [166]: s = 'a,b;c/d' In [167]: import re In [169]: re.sub? Signature: re.sub(pattern, repl, string, count=0, flags=0) Docstring: Return the string obtained by replacing the leftmost non-overlapping occurrences of the pattern in string by the replacement repl. repl can be either a string or a callable; if a string, backslash escapes in it are processed. If it is a callable, it's passed the match object and must return a replacement string to be used. File: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/re.py Type: function In [171]: re.sub(r'[,;/]', '-', s) Out[171]: 'a-b-c-d'
如果进行字符串的模糊搜索与部分替换
In [172]: s = 'things happend in 2017-08-09, it is a sunddy' In [175]: re.sub(r'(\d{4})-(\d{2})-(\d{2})', r'\2-\1-\3', s) Out[175]: 'things happend in 08-2017-09, it is a sunddy'
列表JOIN时如果有数字元素怎么办
In [176]: print '\t'.join([str(x) for x in ['a','b',33,4.0,'e']]) a b 33 4.0 e
文件
如何使用临时文件
In [186]: from tempfile import TemporaryFile,NamedTemporaryFile In [187]: t = TemporaryFile() In [188]: t.write('aa') In [189]: t.close() In [191]: NamedTemporaryFile? Signature: NamedTemporaryFile(mode='w+b', bufsize=-1, suffix='', prefix='tmp', dir=None, delete=True) Docstring: Create and return a temporary file. Arguments: 'prefix', 'suffix', 'dir' -- as for mkstemp. 'mode' -- the mode argument to os.fdopen (default "w+b"). 'bufsize' -- the buffer size argument to os.fdopen (default -1). 'delete' -- whether the file is deleted on close (default True). The file is created as mkstemp() would do it. Returns an object with a file-like interface; the name of the file is accessible as its 'name' attribute. The file will be automatically deleted when it is closed unless the 'delete' argument is set to False. File: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/tempfile.py Type: function In [192]: t = NamedTemporaryFile() In [193]: t.write("a") In [194]: t.name Out[194]: '/var/folders/sc/rpg0yq054hb7vdr83ms1rp2w0000gn/T/tmpQIONuU'
并发编程
如何使用多线程
In [8]: cat multi_threading.py from threading import Thread def func(x): print x, x*x*x ts = [] for x in range(10): t = Thread(target=func, args=(x,)) t.start() ts.append(t) for t in ts: t.join() print 'main thread over' In [9]: %run multi_threading.py 0 0 1 1 2 8 3 27 4 64 5 125 6 216 7 343 8 512 9 729 main thread over
上一中是直接用函数执行,第二种是先创建一个类继承自Thread类
In [18]: cat multi_threading_class.py from threading import Thread class MyThread(Thread): def __init__(self, x): Thread.__init__(self) self.x = x def run(self): print self.x, self.x*self.x*self.x ts = [] for x in range(10): t = MyThread(x) t.start() ts.append(t) for t in ts: t.join() print 'main thread over' In [19]: %run multi_threading_class.py 0 0 1 1 2 8 3 27 4 64 5 125 6 216 7 343 8 512 9 729 main thread over
线程间通信-生产者消费者模式
In [8]: cat producer_consumer.py #coding:utf8 from threading import Thread,currentThread from Queue import Queue from time import sleep from random import randint,sample from itertools import chain class Producer(Thread): def __init__(self, queue): Thread.__init__(self) self.queue = queue def run(self): for x in range(5): sleep(randint(1,3)) ele = sample('abcdefg',1)[0] print 'producer %s: %s'%(currentThread().name, ele) self.queue.put(ele) class Consumer(Thread): def __init__(self, queue): Thread.__init__(self) self.setDaemon(True) self.queue = queue def run(self): while(True): e = self.queue.get() sleep(1) print 'consumer %s: %s' % (currentThread().name, e) queue = Queue() tps = [] for x in range(3): tp = Producer(queue) tp.start() tps.append(tp) for x in range(2): tc = Consumer(queue) tc.start() for t in tps: t.join() print 'main thread over' In [9]: %run producer_consumer.py producer Thread-301: a ^Cconsumer Thread-304: a producer Thread-302: c producer Thread-303: g producer Thread-301: c consumer Thread-304: g consumer Thread-305: c producer Thread-303: b
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