Serialization, Deserialization & Pickling | 16/100 Days of Python Algo Trading

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If you’re here, it means you’re truly dedicated to mastering Python. Directly below, you’ll find a quiz designed to help you reinforce what you’ve just learned. This isn’t just about recalling facts; it’s about deeply understanding the concepts. Take a moment to answer the questions and see how well you can apply the knowledge from the video. You’re doing great—every question you tackle brings you one step closer to becoming a Python expert!

Day 16: Serialization, Deserialization & Pickling

1. What is serialization in the context of computing?

A) Converting data into a format suitable for storage or transmission.

B) Sorting data in ascending or descending order.

C) Compressing raw data into smaller sizes.

D) Scanning data for potential security threats.

2. What does deserialization mean?

A) Converting data back to its original form from a serialized format.

B) Removing extraneous information from data.

C) Increasing the size of data for easier handling.

D) Encrypting data for secure transmission.

3. What is pickling in Python?

A) A process to encrypt data.

B) A module that compresses Python objects.

C) A method for serializing Python objects into a byte stream.

D) A method to lock data for thread-safety.

4. Which Python library is traditionally used for serialization and deserialization?

A) json

B) os

C) sys

D) pickle

5. What are common use cases for serialization in algorithmic trading?

A) Storing configuration settings, saving model states.

B) Optimizing the trading algorithm's runtime.

C) Visualizing complex trading data.

D) Enhancing the security of data transmissions.

6. Which format is NOT typically used for serialization?

A) JSON

B) XML

C) CSV

D) EXE

7. What potential error can occur during serialization of custom objects in Python?

A) SyntaxError

B) AttributeError

C) ImportError

D) SerializationError

8. What is the difference between JSON and Pickle in Python?

A) JSON can serialize any Python object, while Pickle cannot.

B) JSON is human-readable and less secure, while Pickle is not human-readable but more secure.

C) Pickle can serialize any Python object, while JSON is limited to basic data types.

D) JSON is faster than Pickle at serialization.

9. How can you serialize a Python object to a file using Pickle?

A) pickle.load(object, file)

B) pickle.dumps(object, file)

C) pickle.dump(object, file)

D) pickle.serialize(object, file)

10. Which method is used to deserialize data from a JSON file?

A) json.load()

B) json.loads()

C) json.unload()

D) json.parse()

11. What is a primary benefit of using JSON over Pickle for data storage?

A) JSON files are executable and more versatile.

B) JSON is more secure and can handle complex objects better.

C) JSON is language-independent and human-readable.

D) JSON speeds up the deserialization process.

12. In what scenario might deserialization be a security risk?

A) When data is deserialized from a trusted source.

B) When deserializing data that includes executable code.

C) When deserializing data to JSON format.

D) When using deserialization to load numeric data.

13. Why is it important to manage versions in serialized data?

A) To track the number of times data is serialized.

B) To ensure compatibility between the data format and the application.

C) To secure the data against unauthorized access.

D) To comply with data serialization standards.

14. Which of the following is a risk when using the Pickle module?

A) Incompatibility with other programming languages.

B) The inability to serialize complex Python objects.

C) Slower performance compared to binary serialization.

D) Arbitrary code execution during deserialization.

15. How do you handle versioning in serialization for backward compatibility?

A) By including a version number in the serialized data.

B) By encrypting the data with a version-specific key.

C) By compressing the data using a standard algorithm.

D) By using the latest version of Python.

16. What does the json.dumps() method do?

A) It dumps data into a Python object.

B) It serializes a Python object as a JSON formatted string.

C) It deserializes a JSON file into Python.

D) It deletes JSON formatted data from the disk.

17. Why might you use a context manager when working with file-based serialization?

A) To ensure that files are deleted after reading.

B) To improve the speed of reading and writing.

C) To ensure files are properly closed after operations.

D) To encrypt data during serialization.

18. What functionality does the pickle.loads() provide?

A) It loads the Pickle module into memory.

B) It serializes a Python object into a pickle data format.

C) It deserializes a pickle data byte stream into a Python object.

D) It lists all pickled objects in a database.

19. Which practice enhances security when deserializing objects?

A) Using complex passwords.

B) Deserializing from only trusted sources.

C) Using faster serialization formats.

D) Always using the latest version of the serialization library.

20. How do you update serialized data structures to reflect changes in the source code?

A) Re-serialize all data whenever the code changes.

B) Change the data structure manually in the serialized file.

C) Update the code to adapt to the old data format.

D) Serialization formats automatically update with code changes.