When you encounter the `UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte` error, it typically indicates that you are attempting to read or decode a binary file (such as a file generated by the `pickle` module in Python) as if it were a text file encoded in UTF-8. The `pickle` module is used for serializing and de-serializing a Python object structure. When you serialize an object with `pickle`, it is converted into a byte stream, which is not readable as standard UTF-8 encoded text. When you try to read this byte stream with the assumption that it is a UTF-8 text file, you will encounter the above error because the binary data does not conform to UTF-8 encoding standards. Here is the correct way to use `pickle` to serialize and de-serialize objects: To serialize (or "pickle") an object: ```python import pickle # Your object my_object = {'key': 'value'} # Serialize the object to a binary file with open('my_object.pkl', 'wb') as output_file: pickle.dump(my_object, output_file) ``` To de-serialize (or "unpickle") the object: ```python import pickle # Load the object back from the binary file with open('my_object.pkl', 'rb') as input_file: my_object = pickle.load(input_file) print(my_object) # Output: {'key': 'value'} ``` Note that when opening the file for reading or writing, the mode is `'rb'` or `'wb'` for read binary or write binary, respectively. Please ensure the following to avoid such errors: 1. **Correct usage of file modes**: Use binary mode 'rb' or 'wb' when dealing with binary files such as those created by `pickle`. 2. **Matching `pickle` version**: Ensure you are not trying to unpickle an object with a different Python version than it was pickled with. While `pickle` tries to maintain backward compatibility, objects pickled with a newer Python version may not be unpickle-able with older versions. 3. **File corruption**: Make sure that the file has not been corrupted or altered, as this can also cause the error. 4. **Right file**: Make sure you are trying to unpickle the correct file and not accidentally a different file which is not a pickled object. If you're sharing pickled data between computers or storing it for long-term use, it's worth noting that `pickle` is not secure against erroneous or maliciously constructed data. Consider using a more robust format such as `json` (for data interchange) or `numpy`'s `.npz` for numerical data if this is a concern, although these alternatives cannot serialize arbitrary Python objects as comprehensively as `pickle`.