序列化： dumps把内存的数据结构保存下来import jsondic={'a':1}res1=json.dumps(dic)re2=str(dic)print(res1,type(res1)) #json格式都是用的双引号print(res2,type(res2)) x=Noneres=json.dumps(x)print(res,type(res))import json #把python格式转化为json格式user={'name':'xiaoxiao','age':18,'ng':True} with open('user.json','w',encoding='utf-8') as f: f.write(json.dumps(user))import json #同上user={'name':'xiaoxiao','age':18,'ng':True} json.dump(user,open('user_new.json','w',enccoding='utf-8')) #dump合并成一行反序列化：loadsimport json with open('user.json','r',encoding='utf-8') as f: user=json.loads(f.read()) #以json格式读取文件内容 print(user.['name'])import json u=json.load(open('user.json','r',encoding='utf-8')) #同上，load合并成一行print(u['age'])json_res={"name":'xi'} #json只能用双引号print(json.load(json_res))pickle：序列化，能支持所有的Python类型，并以byte类型打开improt pickle,jsons={1,2,3,4}#print(json.dumps(s))print(pickle.dumps(s))with open('s.pkl','wb') as f: f.write(pickle.dumps(s))pickle.dump(s,open('s.pkl','wb')) #同上#pickle反序列化import picklewith open('s.pkl','rb') as f: s=pickle.loads(f.read()) print(s,type(s))s=pickle.load(open('s.pkl','rb')) #同上print(s,type(s))