B.Tech • Chapter 6

File I/O and Serialization

B.Tech level module on File I/O and Serialization.

6 note blocks4 exam topics

🎯 Exam Focus Areas

Evaluate time complexity of related algorithms.Understand memory management and background architecture.Analyze code snippets for bugs or inefficiencies.Explain theoretical concepts with real-world technical examples.

Interacting with the filesystem is fundamental. B.Tech engineers must understand buffers, file modes, encoding (UTF-8), and serialization formats like JSON and Pickle.

Advanced Engineering Concepts

Using the 'with' statement (Context Managers) ensures that file resources are properly cleaned up and released back to the OS, even if an exception occurs during execution. Serialization (Pickling) converts Python object hierarchies into byte streams for storage or network transmission. However, Pickle is Python-specific and insecure for untrusted data, making JSON the preferred standard for web APIs.

1Understand the Big O time and space complexities involved.
2Ensure memory leaks and race conditions are mitigated.
3Adhere to PEP 8 standards for clean, readable code.
4Utilize unit testing to verify algorithmic correctness.

Code Implementation

import json
import pickle

data = {"course": "B.Tech", "subjects": ["DSA", "OS", "DBMS"]}

# JSON Serialization (Cross-language, text-based)
with open("data.json", "w") as f:
    json.dump(data, f)

# Pickle Serialization (Python-specific, binary)
with open("data.pkl", "wb") as f:
    pickle.dump(data, f)

# Context manager guarantees file.close() is called

📝 Quick Revision Points

1Review the CPython implementation details.
2Practice the code snippets until syntax is committed to memory.
3Test edge cases and exception handling.
4Understand trade-offs between different data structures.

← PreviousFunctions, Generators, & Decorators Next →Exception Handling & Logging

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import json import pickle data = {"course": "B.Tech", "subjects": ["DSA", "OS", "DBMS"]} # JSON Serialization (Cross-language, text-based) with open("data.json", "w") as f: json.dump(data, f) # Pickle Serialization (Python-specific, binary) with open("data.pkl", "wb") as f: pickle.dump(data, f) # Context manager guarantees file.close() is called