python常用内建模块
Posted 嘉禾世兴
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【datetime】
No1：
获取当前时间
No2：
时区转换
>>> from datetime import datetime, timedelta, timezone >>> tz_utc_8 = timezone(timedelta(hours=8)) # 创建时区UTC+8:00 >>> now = datetime.now() >>> now datetime.datetime(2015, 5, 18, 17, 2, 10, 871012) >>> dt = now.replace(tzinfo=tz_utc_8) # 强制设置为UTC+8:00 >>> dt datetime.datetime(2015, 5, 18, 17, 2, 10, 871012, tzinfo=datetime.timezone(datetime.timedelta(0, 28800)))
# 拿到UTC时间，并强制设置时区为UTC+0:00: >>> utc_dt = datetime.utcnow().replace(tzinfo=timezone.utc) >>> print(utc_dt) 2015-05-18 09:05:12.377316+00:00 # astimezone()将转换时区为北京时间: >>> bj_dt = utc_dt.astimezone(timezone(timedelta(hours=8))) >>> print(bj_dt) 2015-05-18 17:05:12.377316+08:00 # astimezone()将转换时区为东京时间: >>> tokyo_dt = utc_dt.astimezone(timezone(timedelta(hours=9))) >>> print(tokyo_dt) 2015-05-18 18:05:12.377316+09:00 # astimezone()将bj_dt转换时区为东京时间: >>> tokyo_dt2 = bj_dt.astimezone(timezone(timedelta(hours=9))) >>> print(tokyo_dt2) 2015-05-18 18:05:12.377316+09:00
【collections】
No3：
No4：
deque方便插入和删除
OrderedDict有序
>>> from collections import OrderedDict >>> d = dict([(\'a\', 1), (\'b\', 2), (\'c\', 3)]) >>> d # dict的Key是无序的 {\'a\': 1, \'c\': 3, \'b\': 2} >>> od = OrderedDict([(\'a\', 1), (\'b\', 2), (\'c\', 3)]) >>> od # OrderedDict的Key是有序的 OrderedDict([(\'a\', 1), (\'b\', 2), (\'c\', 3)])
>>> od = OrderedDict() >>> od[\'z\'] = 1 >>> od[\'y\'] = 2 >>> od[\'x\'] = 3 >>> list(od.keys()) # 按照插入的Key的顺序返回 [\'z\', \'y\', \'x\']
FIFO（先进先出）的dict
from collections import OrderedDict class LastUpdatedOrderedDict(OrderedDict): def __init__(self, capacity): super(LastUpdatedOrderedDict, self).__init__() self._capacity = capacity def __setitem__(self, key, value): containsKey = 1 if key in self else 0 if len(self) - containsKey >= self._capacity: last = self.popitem(last=False) print(\'remove:\', last) if containsKey: del self[key] print(\'set:\', (key, value)) else: print(\'add:\', (key, value)) OrderedDict.__setitem__(self, key, value)
Counter计数器
>>> from collections import Counter >>> c = Counter() >>> for ch in \'programming\': ... c[ch] = c[ch] + 1 ... >>> c Counter({\'g\': 2, \'m\': 2, \'r\': 2, \'a\': 1, \'i\': 1, \'o\': 1, \'n\': 1, \'p\': 1})
【base64】
No5：
Base64是一种用64个字符来表示任意二进制数据的方法。
>>> import base64 >>> base64.b64encode(b\'binary\\x00string\') b\'YmluYXJ5AHN0cmluZw==\' >>> base64.b64decode(b\'YmluYXJ5AHN0cmluZw==\') b\'binary\\x00string\'
>>> base64.b64encode(b\'i\\xb7\\x1d\\xfb\\xef\\xff\') b\'abcd++//\' >>> base64.urlsafe_b64encode(b\'i\\xb7\\x1d\\xfb\\xef\\xff\') b\'abcd--__\' >>> base64.urlsafe_b64decode(\'abcd--__\') b\'i\\xb7\\x1d\\xfb\\xef\\xff\'
No6：
【struct】
pack的第一个参数是处理指令，\'>I\'的意思是：
>表示字节顺序是big-endian，也就是网络序，I表示4字节无符号整数。
【摘要算法】
No7：
摘要算法又称哈希算法、散列算法。它通过一个函数，把任意长度的数据转换为一个长度固定的数据串（通常用16进制的字符串表示）
No8：
【hmac】
No9：
【itertools】迭代
count()
>>> import itertools >>> natuals = itertools.count(1) >>> for n in natuals: ... print(n) ...
数字无限增长，差点没爆掉
cycle()
>>> import itertools >>> cs = itertools.cycle(\'ABC\') # 注意字符串也是序列的一种 >>> for c in cs: ... print(c) ...
ABC无限重复，又差点没爆掉
repeat()--限定重复次数
chain()--可以把一组迭代对象串联起来，形成一个更大的迭代器：
groupby()--把迭代器中相邻的重复元素挑出来放在一起：
No10:
try: f = open(\'/path/to/file\', \'r\') f.read() finally: if f: f.close()
可简化为
with open(\'/path/to/file\', \'r\') as f: f.read()
No11：
class Query(object): def __init__(self, name): self.name = name def __enter__(self): print(\'Begin\') return self def __exit__(self, exc_type, exc_value, traceback): if exc_type: print(\'Error\') else: print(\'End\') def query(self): print(\'Query info about %s...\' % self.name)
使用
with Query(\'Bob\') as q: q.query()
》》》》类可简化为
from contextlib import contextmanager class Query(object): def __init__(self, name): self.name = name def query(self): print(\'Query info about %s...\' % self.name) @contextmanager def create_query(name): print(\'Begin\') q = Query(name) yield q print(\'End\')
使用
with create_query(\'Bob\') as q: q.query()
No12：
No13：
from contextlib import closing from urllib.request import urlopen with closing(urlopen(\'https://www.python.org\')) as page: for line in page: print(line)
结果居然打印出整个html界面的代码
【GET】
No14：
from urllib import request req = request.Request(\'http://www.douban.com/\') req.add_header(\'User-Agent\', \'Mozilla/6.0 (iPhone; CPU iPhone OS 8_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/8.0 Mobile/10A5376e Safari/8536.25\') with request.urlopen(req) as f: print(\'Status:\', f.status, f.reason) for k, v in f.getheaders(): print(\'%s: %s\' % (k, v)) print(\'Data:\', f.read().decode(\'utf-8\'))
结果会返回豆瓣网的移动端页面
No15：
【POST】
模拟微博登陆
from urllib import request, parse print(\'Login to weibo.cn...\') email = input(\'Email: \') passwd = input(\'Password: \') login_data = parse.urlencode([ (\'username\', email), (\'password\', passwd), (\'entry\', \'mweibo\'), (\'client_id\', \'\'), (\'savestate\', \'1\'), (\'ec\', \'\'), (\'pagerefer\', \'https://passport.weibo.cn/signin/welcome?entry=mweibo&r=http%3A%2F%2Fm.weibo.cn%2F\') ]) req = request.Request(\'https://passport.weibo.cn/sso/login\') req.add_header(\'Origin\', \'https://passport.weibo.cn\') req.add_header(\'User-Agent\', \'Mozilla/6.0 (iPhone; CPU iPhone OS 8_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/8.0 Mobile/10A5376e Safari/8536.25\') req.add_header(\'Referer\', \'https://passport.weibo.cn/signin/login?entry=mweibo&res=wel&wm=3349&r=http%3A%2F%2Fm.weibo.cn%2F\') with request.urlopen(req, data=login_data.encode(\'utf-8\')) as f: print(\'Status:\', f.status, f.reason) for k, v in f.getheaders(): print(\'%s: %s\' % (k, v)) print(\'Data:\', f.read().decode(\'utf-8\'))
No16：
【Handler】
proxy_handler = urllib.request.ProxyHandler({\'http\': \'http://www.example.com:3128/\'})
proxy_auth_handler = urllib.request.ProxyBasicAuthHandler()
proxy_auth_handler.add_password(\'realm\', \'host\', \'username\', \'password\')
opener = urllib.request.build_opener(proxy_handler, proxy_auth_handler)
with opener.open(\'http://www.example.com/login.html\') as f:
pass
No17:
【XML】
操作XML有两种方法：DOM和SAX。DOM会把整个XML读入内存，解析为树，因此占用内存大，解析慢，优点是可以任意遍历树的节点。SAX是流模式，边读边解析，占用内存小，解析快，缺点是我们需要自己处理事件。
正常情况下，优先考虑SAX，因为DOM实在太占内存。
from xml.parsers.expat import ParserCreate class DefaultSaxHandler(object): def start_element(self, name, attrs): print(\'sax:start_element: %s, attrs: %s\' % (name, str(attrs))) def end_element(self, name): print(\'sax:end_element: %s\' % name) def char_data(self, text): print(\'sax:char_data: %s\' % text) xml = r\'\'\'<?xml version="1.0"?> <ol> <li><a href="/python">Python</a></li> <li><a href="/ruby">Ruby</a></li> </ol> \'\'\' handler = DefaultSaxHandler() parser = ParserCreate() parser.StartElementHandler = handler.start_element parser.EndElementHandler = handler.end_element parser.CharacterDataHandler = handler.char_data parser.Parse(xml)
L = [] L.append(r\'<?xml version="1.0"?>\') L.append(r\'<root>\') L.append(encode(\'some & data\')) L.append(r\'</root>\') return \'\'.join(L)
No18：
【HTMLParser】
from html.parser import HTMLParser from html.entities import name2codepoint class MyHTMLParser(HTMLParser): def handle_starttag(self, tag, attrs): print(\'<%s>\' % tag) def handle_endtag(self, tag): print(\'</%s>\' % tag) def handle_startendtag(self, tag, attrs): print(\'<%s/>\' % tag) def handle_data(self, data): print(data) def handle_comment(self, data): print(\'<!--\', data, \'-->\') def handle_entityref(self, name): print(\'&%s;\' % name) def handle_charref(self, name): print(\'&#%s;\' % name) parser = MyHTMLParser() parser.feed(\'\'\'<html> <head></head> <body> <!-- test html parser --> <p>Some <a href=\\"#\\">html</a> HTML tutorial...<br>END</p> </body></html>\'\'\')
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