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[Solved] Using pickle.dump – TypeError: must be str, not bytes

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error Using pickle.dump – TypeError: must be str, not bytes in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How Using pickle.dump – TypeError: must be str, not bytes Error Occurs?

Today I get the following error Using pickle.dump – TypeError: must be str, not bytes in python.

How To Solve Using pickle.dump – TypeError: must be str, not bytes Error ?

  1. How To Solve Using pickle.dump – TypeError: must be str, not bytes Error ?

    To Solve Using pickle.dump – TypeError: must be str, not bytes Error The output file needs to be opened in binary mode:
    f = open('varstor.txt','w')

  2. Using pickle.dump – TypeError: must be str, not bytes

    To Solve Using pickle.dump – TypeError: must be str, not bytes Error The output file needs to be opened in binary mode:
    f = open('varstor.txt','w')

Solution 1


Just had same issue. In Python 3, Binary modes ‘wb’, ‘rb’ must be specified whereas in Python 2x, they are not needed. When you follow tutorials that are based on Python 2x, that’s why you are here.

import pickle

class MyUser(object):
    def __init__(self,name):
        self.name = name

user = MyUser('Peter')

print("Before serialization: ")
print(user.name)
print("------------")
serialized = pickle.dumps(user)
filename = 'serialized.native'

with open(filename,'wb') as file_object:
    file_object.write(serialized)

with open(filename,'rb') as file_object:
    raw_data = file_object.read()

deserialized = pickle.loads(raw_data)


print("Loading from serialized file: ")
user2 = deserialized
print(user2.name)
print("------------")

Solution 2

The output file needs to be opened in binary mode:

f = open('varstor.txt','w')

needs to be:

f = open('varstor.txt','wb')

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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