Unsupported Pickle Protocol 5 Error in Python

Problem Statement

When attempting to load a pickled file in Python 3.7, you may encounter the error:

ValueError: unsupported pickle protocol: 5

This error occurs because Python 3.7 only supports pickle protocols up to version 4, while the file you're trying to load was created using protocol 5, which was introduced in Python 3.8.

Common scenarios where this occurs:

• Loading models or data files created in Python 3.8+ into older Python versions
• Working with pickled files from ML frameworks like RLLib, stable-baselines3, or pandas
• Deployment issues when production and development environments use different Python versions

Solutions

Solution 1: Install and Use pickle5 (Recommended)

The most straightforward solution is to install the pickle5 backport package, which adds protocol 5 support to Python 3.6+:

pip install pickle5

Then use it to load your protocol 5 pickle files:

import pickle5 as pickle

with open("path/to/your/file.pkl", "rb") as f:
    data = pickle.load(f)

TIP

After loading the data, you can re-save it using protocol 4 for compatibility with older Python versions:

# For pandas DataFrames
data.to_pickle("path/to/protocol4/file.pkl")

# For general Python objects
with open("path/to/protocol4/file.pkl", "wb") as f:
    pickle.dump(data, f, protocol=4)

Solution 2: Stable-Baselines3 Specific Solution

If you encounter this error with stable-baselines3 models:

pip install --upgrade cloudpickle pickle5

Then load your model with appropriate custom objects:

from stable_baselines3 import PPO

custom_objects = {
    "lr_schedule": lambda x: .003,
    "clip_range": lambda x: .02
}
model = PPO.load("path/to/model.zip", custom_objects=custom_objects)

Solution 3: Environment Consistency

For deployment scenarios (like Heroku), ensure consistent Python versions:

1. Create a runtime.txt file in your project root
2. Specify your Python version (e.g., python-3.9.2)
3. This ensures your development and production environments use the same Python version

Solution 4: Switch Python Interpreters

If you're working across different IDEs (like Spyder and IDLE) with different Python versions:

1. Ensure you're using the same Python interpreter across all environments
2. Install necessary dependencies for your chosen interpreter:

pip install spyder-kernels  # If using Spyder with a non-default interpreter

Understanding Pickle Protocols

Pickle protocols are version numbers that define how Python objects are serialized. Newer protocols:

• Support more Python features
• May have performance improvements
• Are not backward compatible with older Python versions

Protocol Version	Python Version	Key Features
4	3.4+	Support for large objects
5	3.8+	Out-of-band data, performance improvements

Best Practices

1. Always specify protocol version when saving pickle files:

import pickle

# Explicitly use protocol 4 for maximum compatibility
with open("file.pkl", "wb") as f:
    pickle.dump(data, f, protocol=4)

2. Document the Python version and dependencies used to create pickle files
3. Consider alternative serialization formats (JSON, MessagePack) for better compatibility
4. Use version-controlled environments (conda, virtualenv) to ensure consistency

WARNING

Pickle files can execute arbitrary code during deserialization. Only load pickle files from trusted sources to avoid security risks.

When to Use Each Solution

• For quick data loading: Use pickle5 package
• For production systems: Standardize Python versions across environments
• For ML models: Check framework-specific solutions and update dependencies
• For long-term storage: Use protocol 4 or alternative serialization formats

By understanding the root cause of the protocol 5 error and applying the appropriate solution, you can successfully work with pickle files across different Python versions.