序列化是指把内存里的数据类型转酿成字符串，以使其能存储到硬盘或通过网络传输到长途，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 共享给长途其他人 必需：bytes 2.界说了差别语言之间得交互法则 2.1 纯文本：坏处不能共享庞大得数据类型 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得四个要领一样 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 不撑持set pickle 撑持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顶用

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 # 长期化列表 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 可整体从头赋值 xml 模块

感化：
差别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的格局如下，就是通过<>节点来区别数据布局的: <?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 是撑持的，在python中可以用以下模块操纵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.改削和删除xml文档内容 import xml.etree.ElementTree as ET tree = ET.parse("xmltest.xml") root = tree.getroot() #改削 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.本身创建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) #生成文档东西 et.write("test.xml", encoding="utf-8",xml_declaration=True) ET.dump(new_xml) #打印生成的格局

模块 序列化 json pickle shelv xml

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