Resolving Python 3.7 Error: Unsupported Pickle Protocol 5

The “unsupported pickle protocol 5” error in Python 3.7 occurs when you try to deserialize (unpickle) data that was serialized (pickled) using a newer protocol introduced in Python 3.8. This happens because Python 3.7 and earlier versions do not support the pickle protocol 5, leading to compatibility issues.

Understanding Pickle Protocols

Pickle Protocols in Python:

• Pickle is a module in Python used for serializing (pickling) and deserializing (unpickling) Python object structures.
• Protocols: Different versions of the pickle protocol offer varying levels of efficiency and compatibility.
  • Protocol 0: Original ASCII protocol, human-readable, compatible with earlier Python versions.
  • Protocol 1: Old binary format, also compatible with earlier versions.
  • Protocol 2: Introduced in Python 2.3, supports efficient pickling of new-style classes.
  • Protocol 3: Added in Python 3.0, supports bytes objects.
  • Protocol 4: Introduced in Python 3.4, supports large objects, more efficient.
  • Protocol 5: Introduced in Python 3.8, includes out-of-band data for large data structures.

Error Explanation:

• “Python 3.7 error unsupported pickle protocol 5” occurs because Protocol 5 is not supported in Python versions earlier than 3.8.
• Solutions:
  • Upgrade Python: Use Python 3.8 or later.
  • Use pickle5 module: Backports Protocol 5 features to older Python versions.
  • Use a lower protocol: Serialize with Protocol 4 or lower.

Causes of the Error

The error “unsupported pickle protocol: 5” in Python 3.7 occurs due to the following specific causes:

1. Version Incompatibility: Pickle protocol 5 was introduced in Python 3.8. Python 3.7 and earlier versions do not support this protocol. Attempting to deserialize data serialized with protocol 5 in Python 3.7 results in this error.

2. Deserialization with Unsupported Protocols: When data is serialized (pickled) using Python 3.8 or later with protocol 5 and then deserialized (unpickled) using Python 3.7 or earlier, the unsupported protocol error is triggered.

To resolve this, you can:

• Use the pickle5 module to backport protocol 5 support to Python 3.7.
• Serialize data with a lower protocol version (e.g., protocol 4) to ensure compatibility.
• Upgrade to Python 3.8 or later.

Solutions to the Error

1. Upgrade Python version: Install Python 3.8 or later.
2. Use pickle5 module:

   import pickle5 as pickle
   

   Install with:

   pip install pickle5
   

3. Serialize with lower protocol:

   pickle.dump(obj, file, protocol=4)
   

Example Scenarios

Scenario 1: Pickling in Python 3.8 and Unpickling in Python 3.7

Code Example:

# Pickling in Python 3.8
import pickle

data = {'key': 'value'}
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file, protocol=5)

# Unpickling in Python 3.7
import pickle

with open('data.pkl', 'rb') as file:
    data = pickle.load(file)  # Raises ValueError: unsupported pickle protocol: 5

Fix:

Use the pickle5 module in Python 3.7:

# Unpickling in Python 3.7 with pickle5
import pickle5 as pickle

with open('data.pkl', 'rb') as file:
    data = pickle.load(file)
print(data)

Scenario 2: Using Joblib with Protocol 5 in Python 3.8 and Loading in Python 3.7

Code Example:

# Saving with joblib in Python 3.8
import joblib

data = {'key': 'value'}
joblib.dump(data, 'data.pkl', protocol=5)

# Loading with joblib in Python 3.7
import joblib

data = joblib.load('data.pkl')  # Raises ValueError: unsupported pickle protocol: 5

Fix:

Specify a lower protocol version when saving:

# Saving with joblib in Python 3.8 using protocol 4
import joblib

data = {'key': 'value'}
joblib.dump(data, 'data.pkl', protocol=4)

# Loading with joblib in Python 3.7
import joblib

data = joblib.load('data.pkl')
print(data)

Scenario 3: Using a Custom Pickle Protocol in a Distributed System

Code Example:

# Node A (Python 3.8)
import pickle

data = {'key': 'value'}
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file, protocol=5)

# Node B (Python 3.7)
import pickle

with open('data.pkl', 'rb') as file:
    data = pickle.load(file)  # Raises ValueError: unsupported pickle protocol: 5

Fix:

Ensure all nodes use a compatible protocol:

# Node A (Python 3.8) using protocol 4
import pickle

data = {'key': 'value'}
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file, protocol=4)

# Node B (Python 3.7)
import pickle

with open('data.pkl', 'rb') as file:
    data = pickle.load(file)
print(data)

These examples should help you understand and resolve the unsupported pickle protocol: 5 error in Python 3.7.

Resolving ‘Unsupported Pickle Protocol’ Errors in Python

When working with Python 3.7, you may encounter an 'unsupported pickle protocol: 5' error when trying to load data saved with a higher protocol version (e.g., protocol 5) in Python 3.8 or later.

This is because the default protocol version used by pickle has changed between Python versions.

Solution: Ensure Compatible Protocol Versions

To resolve this issue, ensure that all nodes or systems using pickle are running compatible Python versions and use the same protocol version when saving and loading data. In general, it’s recommended to stick with a lower protocol version (e.g., protocol 4) for compatibility across different Python versions.

Specifying Protocol Version

When saving data, specify the desired protocol version using the protocol parameter of the dump() function. For example:

import pickle

data = {'key': 'value'}
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file, protocol=4)

Loading Data

When loading data, use the same protocol version to avoid compatibility issues. If you’re unsure about the protocol version used when saving the data, try using a lower protocol version (e.g., protocol 4) to ensure compatibility.

import pickle

twith open('data.pkl', 'rb') as file:
    data = pickle.load(file)

Best Practices

By following these guidelines and being mindful of the protocol versions used in your code, you can avoid the 'unsupported pickle protocol: 5' error and ensure seamless data exchange between different Python systems.