1 logging 模块
logging有两种的配置的方式，configure、logger
1.1 config方式
import logging
'''
日志的配置：config模式
只能选择在屏幕或者在文件输出
'''
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s [%(lineno)s] %(message)s' ,
filename='log.txt',
filemode='a'
)
# logging.debug('debug message') 只有这些内容的时候是只显示在屏幕
# logging.info('info message')
# logging.warning('warning message')
# logging.error('error message')
# logging.critical('critical message')
logging.info('info message')
通过logging.basicConig可以配置输出的格式，level=DEBUG，还可以是INFO、WARNING、ERROR、DIGITAL,这个的优先级是从上往下的。设置好了哪一个就会显示他后面的。
1.2 logger
推荐用logger
默认的情况是输出到屏幕的
import logging
logger=logging.getLogger()logger.debug('debug message')
logger.info('info message')
logger.warning('warning message')
logger.error('error message')
logger.critical('critical message')
可通过
import logginglogger=logging.getLogger()
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')fh=logging.FileHandler('test.txt') # 文件流
sh=logging.StreamHandler() # 屏幕流fh.setFormatter(formatter) # 这是通过对象实现的设置格式
sh.setFormatter(formatter) #logger.addHandler(fh)
logger.addHandler(sh)logger.debug(' logger debug message')
logger.info('logger info message')
logger.warning('logger warning message')
logger.error('logger error message')
logger.critical('logger critical message')
函数的方法:
def logger():
logger = logging.getLogger() # 吸星大法 fh = logging.FileHandler('logger.txt') # 文件流
sh = logging.StreamHandler() # 屏幕流 logger.addHandler(fh) # 追加写 设置成文件写入
logger.addHandler(sh) # 默认是屏幕流 关闭后就屏幕不输出 logger.setLevel(logging.DEBUG) # 设置等级 操作的对象是logger fm = logging.Formatter('%(asctime)s [%(lineno)s] %(message)s') fh.setFormatter(fm) # 文件的对象
# sh.setFormatter(fm) # 屏幕的对象 添加格式
return loggerlogger1=logger() # 现在是把函数的运行结果给一个对象# 对象能够使用方法
logger1.debug('debug message')
logger1.info('info message')
logger1.warning('warning message')
logger1.error('error message')
logger1.critical('critical message')
2 序列化模块
2.1 JSON
json是不同语言之间的数据准换
序列化 反序列化
import json
'''
序列化
'''
d={'a':123,"b":456} # 数据格式是字典
s=json.dumps(d) # 转换成json字符串（实际是Unicode）
print(s) # 这是json中的数据 {"a": 123, "b": 456} 是双引号
print(type(s))# f=open('b.txt','w')
# f.write(s)
# f.close()'''
反序列化
'''
f=open('b.txt')
data=f.read()
print(data)data2=json.loads(data) # 现在就是字典的格式
print(data2)
json.dump(d,f) # d 是字典 f是文件句柄 有写入的操作
json 应用
import json
i=10
s='hello'
t=(1,4,6)
l=[3,5,7]
d={'name':"aa"}json_str1=json.dumps(i)
json_str2=json.dumps(s)
json_str3=json.dumps(t)
json_str4=json.dumps(l)
json_str5=json.dumps(d)print(json_str1) #'10'
print(json_str2) #'"hello"'
print(json_str3) #'[1, 4, 6]' # 元组转换成json格式
print(json_str4) #'[3, 5, 7]'
print(json_str5) #'{"name": "aa"}'
2.2 pickle模块
在python中能够序列化任何数据类型，是Python专用 的
序列化
import pickle # pickle 是Python文件中间转换的
import datetime# print(datetime.datetime.now())
t=datetime.datetime.now()
d={'data':t}s=pickle.dump(d,open('new','wb')) # json 不支持时间的格式print(s)
反序列化
f=open('new','rb')
data=pickle.loads(f.read())
print(data)
3 正则模块re
正则是对字符串的模糊匹配
re.findall(‘元字符’,”字符串”)
是字符串中的每一个去对应元字符中的规则
元字符
1.通配符"." # 不能配换行符\n,如果有换行符，返回一个空列表
2.模糊匹配"*" [0,+∞]
3. + [1,+∞]
4. ？ [0,1]
5. {} {0,}==* {1,}==+ {0,1}==？
6.字符集 [ab] a b 是或者的关系
\* + 是普通字符
\- ^ \ 有特殊用处
[0-9]+
[a-z]+
[^2] 取反
[^\d ] 单个
[^\d]+ 多个连续的
7.分组（） "（ab）+","add" # 分组中默认只有一个
取消优先级（？：）
8. | ：或
9. \
\d
\w
\.
\d 匹配任何十进制数；它相当于类 [0-9]。
\D 匹配任何非数字字符；它相当于类 [^0-9]。
\s 匹配任何空白字符；它相当于类 [ \t\n\r\f\v]。
\S 匹配任何非空白字符；它相当于类 [^ \t\n\r\f\v]。
\w 匹配任何字母数字字符；它相当于类 [a-zA-Z0-9_]。
\W 匹配任何非字母数字字符；它相当于类 [^a-zA-Z0-9_]
\b 匹配一个特殊字符边界，比如空格 ，&，＃等 r'\b','' \b在ASCII中有专门的意思
命名分组
res=re.search(r"(?P<A>\w+)\\article\\(?P<id>\d+)", r"abc\article\123", flags=0)
print(res)
print(res.group("A"))
print(res.group("id"))
结果：
abc
123
无命名分组
res=re.findall("(ad)+abc", "adabcnnf", flags=0)
res=re.findall("(?:ad)+abc", "adabcnnf", flags=0) # 取消优先级
结果：
[‘ad’]
[‘adabc’]
finditer 方法
res=re.finditer("\d+", "ad324daa", flags=0)
print(res)
结果：是一个生成器
callable_iterator object at 0x0000000002B29240>
用next方法
print(next(res).group())
print(next(res).group())
search 方法
search 值匹配第一个结果
res= re.search("\d+", "sjasdff454asef2352", flags=0)
print(res)
print(res.group())
match 方法
mach只在字符串开始的位置匹配
res = re.match("\d+", "123nljklkl2565+6", flags=0)
print(res)
print(res.group())
split 方法
maxsplit是最大的分割次数，默认是0
res=re.split("\d+", "asd123fk234as123df1231sdf132fff", maxsplit=4, flags=0)
print(res)
[‘asd’, ‘fk’, ‘as’, ‘df’, ‘sdf132fff’] 第5次没有继续分割
sub 方法
res = re.sub("\d+", "A","abc2342abc123aaa123", count=3,flags=0)
print(res)
结果：
abcAabcAaaaA
compile 方法
res = re.compile("\d+", flags=0)
res2 = res.findall("hello1232") # 把编译好的直接用
print(res2)
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