json与picklepython
pickle 写入多个对象,读取多个对象json
pickle支持屡次dump,但对于读取文件,咱们再不清楚内容(load多少次)时,使用try except EOFError class A: def __init__(self): self.li = [] class B: def __init__(self): self.li = [] a = A() a.li.append(1) b = B() b.li.append(2) import pickle class My_pickle(): def __init__(self,path): self.path = path def dump(self,*args): with open(self.path,mode='wb') as f: for i in args: pickle.dump(i,f) def load(self): with open(self.path,mode='rb') as f: while 1: try: yield pickle.load(f) except EOFError: break p1 = My_pickle('test.pikle') p1.dump(a,b) for i in p1.load(): print(i)
json写入多行网络
方式一: 将待写入的多种数据(列表,元组,字典)放到一个列表中写入,读取时,将列表反序列化到内存,在逐个返回。 缺点:一次性取出全部,内存占用大。 import json class My_json(): def __init__(self,file): self.file = file def dump(self,*args): with open(self.file,mode='w',encoding='utf-8') as f: li = [] for i in args: li.append(i) json.dump(li,f) def load(self): with open(self.file,mode='r',encoding='utf-8') as f: ret = json.load(f) for j in ret: yield j j = My_json('test.json') j.dump([1,2,3,4,],'ssss') for i in j.load(): print(i)
方式二: 推荐 将待写入的多种数据(列表,元组,字典)写入一种数据的同时写入一个\n,这样读取文件的时候,使用for遍历文件句柄,对于获得的字符串使用json.loads()方法进行反序列化。 import json class My_json(): def __init__(self,file): self.file = file def dump(self,*args): with open(self.file,mode='w',encoding='utf-8') as f: for i in args: json.dump(i,f) f.write('\n') def load(self): with open(self.file,encoding='utf-8') as f: for line in f: ret = json.loads(line) print(ret) j = My_json('test.json') j.dump([1,2,3,4,],'ssss') j.load()
方式三: 在方式二的基础上进行的小改,除了先dump(i)在write('\n'),咱们还能够先用 dumps(i)序列化数据,而后再write(序列化数据 + '\n') import json class My_json(): def __init__(self,file): self.file = file def dump(self,*args): with open(self.file,mode='w',encoding='utf-8') as f: for i in args: f.write(json.dumps(i) + '\n') def load(self): with open(self.file,encoding='utf-8') as f: for line in f: ret = json.loads(line) print(ret) j = My_json('test.json') j.dump([1,2,3,4,],'ssss') j.load()
pickle和json在对多行写入,写出的区别:app