Pickle Module - Serialization

Introduction

The pickle module implements binary protocols for serializing and deserializing Python object structures. It converts Python objects to byte streams and back.

Basic Pickling

import pickle

data = {"name": "Alice", "age": 30, "scores": [95, 87, 92]}

# Serialize to bytes
serialized = pickle.dumps(data)

# Deserialize back
deserialized = pickle.loads(serialized)
print(deserialized)

Working with Files

import pickle

data = {"key": "value"}

# Write to file
with open("data.pkl", "wb") as f:
    pickle.dump(data, f)

# Read from file
with open("data.pkl", "rb") as f:
    loaded = pickle.load(f)

Protocol Versions

import pickle

data = [1, 2, 3, 4, 5]

# Protocol 0 (ASCII, compatible)
p0 = pickle.dumps(data, protocol=0)

# Protocol 4 (Python 3.4+, efficient)
p4 = pickle.dumps(data, protocol=4)

# Protocol 5 (Python 3.8+, out-of-band data)
p5 = pickle.dumps(data, protocol=5)

print(f"Protocol 0 size: {len(p0)}")
print(f"Protocol 4 size: {len(p4)}")
print(f"Protocol 5 size: {len(p5)}")

Custom Object Serialization

import pickle

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age
    
    def __getstate__(self):
        return {"name": self.name, "age": self.age}
    
    def __setstate__(self, state):
        self.name = state["name"]
        self.age = state["age"]

person = Person("Bob", 25)
data = pickle.dumps(person)

Security Considerations

# NEVER unpickle untrusted data!
# Bad: pickle.loads(untrusted_input)

# Use a safer alternative like json or msgpack
import json

safe_data = json.dumps({"name": "Alice"})
safe_loaded = json.loads(safe_data)

Practice Problems

1. Serialize and deserialize a custom class
2. Use different protocol versions
3. Handle large objects efficiently
4. Implement reduce for complex objects
5. Compare pickle with json serialization