UnicodeDecodeError: 'utf-8' codec can't decode byte in position: invalid continuation byte

The Python “UnicodeDecodeError: ‘utf-8’ codec can’t decode byte in position: invalid continuation byte” occurs when we try to decode a bytes object using an incorrect encoding. To solve this error, we need to specify the correct encoding when decoding the bytes object.

For example, the following code will raise the UnicodeDecodeError:

my_bytes = 'one é two'.encode('latin-1')my_str = my_bytes.decode('utf-8') # UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe9 in position 4: invalid continuation byte

How to Fix UnicodeDecodeError: ‘utf-8’ codec can’t decode byte in position: invalid continuation byte

This error occurs because the string “one é two” was encoded using the ‘latin-1’ encoding, but we are trying to decode it using ‘utf-8’ encoding. To fix this, we need to use the ‘latin-1’ encoding when decoding the bytes object:

my_bytes = 'one é two'.encode('latin-1')my_str = my_bytes.decode('latin-1') # "one é two"

If you encounter this error when reading a file using pandas, you can try specifying the encoding as ‘latin-1’:

import pandas as pddf = pd.read_csv('employees.csv', sep='|', encoding='latin-1')

You can also use the native open() function and specify the encoding as ‘latin-1’:

import csvwith open('employees.csv', newline='', encoding='latin-1') as csvfile:    csv_reader = list(csv.reader(csvfile, delimiter='|'))    print(csv_reader)

Solve the error using ‘ignore’:

Another option is to set the errors keyword argument to ‘ignore’ to ignore the characters that cannot be decoded. However, this approach can lead to data loss, so it should be used with caution.

import csvwith open('employees.csv', newline='', encoding='utf-8', errors='ignore') as csvfile:    csv_reader = list(csv.reader(csvfile, delimiter='|'))    print(csv_reader)

It’s also important to note that if you are trying to read from or write to a PDF file, you should use the ‘rb’ or ‘wb’ modes as PDF files are stored as bytes.

with open('example.pdf', 'rb') as file1:    my_bytes = file1.read()    print(my_bytes.decode('latin-1'))

In general, it’s crucial to use the correct encoding when working with bytes objects in Python. If you’re unsure about the encoding of a file or bytes object, you can try using the chardet library to automatically detect the encoding.

Detect encoding using chardet library:

Here is an example of how using a different encoding to encode a string to bytes than the one used to decode the bytes object causes an error:

# Encode the string "hello world" to bytes using UTF-8encoded_string = "hello world".encode('UTF-8')# Attempt to decode the bytes object using the latin-1 encodingdecoded_string = encoded_string.decode('latin-1')# This will raise a UnicodeDecodeError, because the latin-1 encoding is not able to properly decode the bytes encoded with UTF-8

As you can see, the encode() method is used to convert the string “hello world” to bytes using the UTF-8 encoding. Then, the decode() method is used to convert the bytes object back to a string using the latin-1 encoding. However, since the bytes object was encoded using UTF-8, the latin-1 encoding is not able to properly decode it and a UnicodeDecodeError is raised.

It is important to use the same encoding when encoding and decoding a string, otherwise, errors like the one shown above will occur.

In this example, we can see how using a different encoding to encode a string to bytes than the one used to decode the bytes object causes the error. It’s important to be consistent with the encoding used when working with bytes and strings in Python, otherwise, you may encounter unexpected results or errors. To avoid this issue, make sure to use the same encoding for both the encoding and decoding process.

Additionally, it’s worth noting that when working with text data, it’s a good practice to explicitly specify the encoding when reading or writing files, as different systems and environments may have different default encodings. This can help to ensure that the data is interpreted correctly and avoid any potential issues that may arise from using the wrong encoding.

Conclusion on UnicodeDecodeError: ‘utf-8’ codec can’t decode byte in position: invalid continuation byte

In conclusion, understanding the different types of encodings and how they work is essential when working with text data in Python. It’s important to be consistent with the encoding used when working with bytes and strings, and to explicitly specify the encoding when reading or writing files to ensure that the data is interpreted correctly.