序列化
序列化是指把内存里的数据类型转变成字符串,以使其能存储到硬盘或通过网络传输到远程,因为硬盘或网络传输时只能接受bytes.
json 模块
json.dump(d,f) json.load(f) #与文件得交互 dump(可多次,但不那样做) load(只可一次)
把数据类型转成字符串存到内存里得意义?
json.dumps(data) json.loads(q) #与内存得交互
1.把内存数据 通过网络 共享给远程其他人 必须:bytes
2.定义了不同语言之间得交互规则
2.1 纯文本:坏处不能共享复杂得数据类型
18:32 424224 iphone 5000
2.2 xml 占得空间大 效率低
<data>
<country>
<year>2018</year> # year:2018
</country>
</data>
2.3 json 简单 可读性好
data = {
'roles':[
{'role':'monster','type':'pig','life':50},
{'role':'hero','type':'关羽','life':80}
]
}
import json
data = {
'roles':[
{'role':'monster','type':'pig','life':50},
{'role':'hero','type':'关羽','life':80}
]
}
s = json.dumps(data)
print(s,type(s))
data = json.loads(s)
print(data,type(data),data['roles'])
json.dump(data,open('test.json','w',encoding='utf-8'))
data = json.load(open('test.json','r',encoding='utf-8'))
print(data['roles'],type(data))
pickle 模块
rb wb 和json得四个方法一样 写读 都是bytes形式的 可以将函数dump load都行
pickle.dumps(d) json.loads(d)
pickle.dump(d,pk) pickle.load(pk)
import pickle
data = {
'roles':[
{'role':'monster','type':'pig','life':50},
{'role':'hero','type':'关羽','life':80}
]
}
def sayhi():
print('sayhi')
s = pickle.dumps(data)
print(s,type(s))
data = pickle.loads(s)
print(data,type(data),data['roles'])
pickle.dump(data,open('test.json','wb'))
data = pickle.load(open('test.json','rb'))
print(data,type(data))
s = pickle.dumps(sayhi)
print(s)
data = pickle.loads(s)
data()
pickle.dump(sayhi,open('test1.json','wb'))
pickle.load(open('test1.json','rb'))()
json 和 pickle 得区别
json 转化得数据类型:str int list tuple dict 不支持set
pickle 支持python里得所有数据类型 确定是 只能在python里使用 函数都可以序列化
shelve 模块
pickle封装了shelve 只能在python中用
序列化:
import shelve
f = shelve.open('shelve_test') # 打开一个文件
names = ["alex", "rain", "test"]
info = {'name':'alex','age':22}
f["names"] = names # 持久化列表
f['info_dic'] = info
f.close()
反序列化:
import shelve
d = shelve.open('shelve_test') # 打开一个文件
print(d['names'])
print(d['info_dic'])
#del d['test'] #还可增加 删除 可整体重新赋值
xml 模块
作用:
不同语言之间内存数据得交换
内存得数据可转换成xml存到硬盘上
1.xml的格式如下,就是通过<>节点来区别数据结构的:
<?xml version="1.0"?>
<data>
<country name="Liechtenstein">
<rank updated="yes">2</rank>
<year>2008</year>
<gdppc>141100</gdppc>
<neighbor name="Austria" direction="E"/>
<neighbor name="Switzerland" direction="W"/>
</country>
<country name="Singapore">
<rank updated="yes">5</rank>
<year>2011</year>
<gdppc>59900</gdppc>
<neighbor name="Malaysia" direction="N"/>
</country>
<country name="Panama">
<rank updated="yes">69</rank>
<year>2011</year>
<gdppc>13600</gdppc>
<neighbor name="Costa Rica" direction="W"/>
<neighbor name="Colombia" direction="E"/>
</country>
</data>
2.xml协议在各个语言里的都 是支持的,在python中可以用以下模块操作xml
import xml.etree.ElementTree as ET
tree = ET.parse("xmltest.xml")
root = tree.getroot()
print(root.tag)
#遍历xml文档
for child in root:
print(child.tag, child.attrib)
for i in child:
print(i.tag,i.text)
#只遍历year 节点
for node in root.iter('year'):
print(node.tag,node.text)
3.修改和删除xml文档内容
import xml.etree.ElementTree as ET
tree = ET.parse("xmltest.xml")
root = tree.getroot()
#修改
for node in root.iter('year'):
new_year = int(node.text) + 1
node.text = str(new_year)
node.set("updated","yes")
tree.write("xmltest.xml")
#删除node
for country in root.findall('country'):
rank = int(country.find('rank').text)
if rank > 50:
root.remove(country)
tree.write('output.xml')
4.自己创建xml文档
import xml.etree.ElementTree as ET
new_xml = ET.Element("namelist")
name = ET.SubElement(new_xml,"name",attrib={"enrolled":"yes"})
age = ET.SubElement(name,"age",attrib={"checked":"no"})
sex = ET.SubElement(name,"sex")
sex.text = '33'
name2 = ET.SubElement(new_xml,"name",attrib={"enrolled":"no"})
age = ET.SubElement(name2,"age")
age.text = '19'
et = ET.ElementTree(new_xml) #生成文档对象
et.write("test.xml", encoding="utf-8",xml_declaration=True)
ET.dump(new_xml) #打印生成的格式