Serialization is the process of transforming the state of an object into a format that can be maintained or transmitted . The opposite of serialization is deserialization , It turns the stream into an object . The two processes combine , Data can be stored and transferred easily .
pickle What is the module used for
Used to access structured data . be used for python Unique types and python The data types are converted .
pickle Types of data that can be stored
pickle Common methods in modules
pickle There are four functions ：dumps,dump,loads,load
1.pickle.dumps(obj[, protocol])
Function functions ： take obj Object serialization to string form , Not in a file （ Returns the encapsulated object as a byte object , No need to write to file ）.
Parameters on ：
obj： Want to serialize obj object .
protocal： If this item omits , The default is 0. If it's negative or HIGHEST_PROTOCOL, Use the highest protocol version .
# dumps function
# dumps Convert data into only... In a special form python The string of language recognition
import pickle
info = {
'name': 'Vivian',
'age': 20,
'height': 157
}
data = pickle.dumps(info) # dumps It turns the data into bytes form
print(data)
# Output
# b'\x80\x03}q\x00(X\x04\x00\x00\x00nameq\x01X\x06\x00\x00\x00Vivianq\x02X\x03\x00\x00\x00ageq\x03K\x14X\x06\x00\x00\x00heightq\x04K\x9du.'
2.pickle.dump(obj, file, protocol=None,)
Function functions ： take obj Object serialization is stored in the opened file in .
Parameters on ：
Required parameters obj Represents the object to be encapsulated
Required parameters file Express obj File object to write ,file Must be opened in binary writable mode , namely “wb”
notes ： A dictionary a = {‘name’:‘Tom’,‘age’:22}, use pickle.dump Save to local file , The structure of the stored data is a dictionary , And ordinary. file.write Writing to the file is a string .
# dump function
# dump Convert data into only... In a special form python The string of language recognition , And write the file
import pickle
info = {
'name': 'Vivian',
'age': 20,
'height': 157
}
with open('information.pkl', 'wb') as f:
pickle.dump(info, f)
3.pickle.loads(string)
Function functions ： Deserialization . from string Read before serialization obj object （ Read the encapsulated object from the byte object , And back to ）.
Parameters on ：
string： File name .
# loads function
# loads take pickle Data to python Data structure of
import pickle
info = {
'name': 'Vivian',
'age': 20,
'height': 157
}
data1 = pickle.dumps(info)
print(data1)
data2 = pickle.loads(data1)
print(data2)
# Output
# b'\x80\x03}q\x00(X\x04\x00\x00\x00nameq\x01X\x06\x00\x00\x00Vivianq\x02X\x03\x00\x00\x00ageq\x03K\x14X\x06\x00\x00\x00heightq\x04K\x9du.'
# {'name': 'Vivian', 'age': 20, 'height': 157}
4.pickle.load(file)
Function functions ：load Object deserialization , Read data from file , take file Object serialization read in .
Parameters on ：
file： File name . Required parameters file Must be opened in binary readable mode , namely “rb”, Others are optional parameters .
# load function
# load Read data from a data file , And converted to python Data structure of
import pickle
with open('information.pkl', 'rb') as f:
print(pickle.load(f))
# Output
# {'name': 'Vivian', 'age': 20, 'height': 157}
json What is the module used for
Used to access structured data . For strings and Python Conversion between data types .
json Types of data that can be stored
Can only support int\str\list\tuple\dict
json Common methods in modules
json There are four functions ：dumps,dump,loads,load
1. Turn the dictionary into json strand
Only strings can be written in the file , But you can turn the dictionary into json strand ,json String is a string , Can be saved in a file .
# json.dumps Convert data into a string that is recognized by all programming languages in a special form
import json
info = {
'name': 'Vivian',
'age': 20,
'height': 157
}
j_str = json.dumps(info) # Be careful json dumps The result is a string , No bytes
print(j_str)
print(type(j_str))
# Output
# {"name": "Vivian", "age": 20, "height": 157}
# <class 'str'>
# Use .dump() Before the method , To open the file first , Write again
with open('massage.json', 'w') as f:
json.dump(info, f)
2.json String into dictionary
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# json.loads Used to decode JSON data . This function returns Python The data type of the field
print(json.loads(j_str))
print(type(json.loads(j_str)))
# Output
# {'name': 'Vivian', 'age': 20, 'height': 157}
# <class 'dict'>
with open('massage.json') as f:
data = json.load(f)
print(data)
print(type(data))
# {"name": "Vivian", "age": 20, "height": 157}
# <class 'dict'>
advantage ： Cross language ( Data transfer between different languages is available json Handover )、 Small volume
shortcoming ： Can only support int\str\list\tuple\dict
advantage ： Specially designed for python Design , Support python All data types
shortcoming ： Only in python Use in , Big storage space
load and loads It's all about realizing “ Deserialization ”, The difference lies in ：
loads For memory objects
the Python The built-in data is serialized into strings . If you use json.dumps Serialized objects d_json=json.dumps({‘a’:1, ‘b’:2}), ad locum d_json Is a string ’{“b”: 2, “a”: 1}’
d=json.loads(d_json) #{ b": 2, "a": 1}, Use load Re deserialize to dict
load For file handle
If there is a local json file a.json Then you can d=json.load(open(‘a.json’))
Corresponding ,dump Is to serialize the built-in type into json Write to file after object
