PCPP-32-101 1.11 (De)serialize Python Objects PCPP-32-1 Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   A developer is writing a function that receives a Python object from a network socket as a bytes object. The object was originally a tuple of integers. The developer needs to reconstruct the original tuple in memory. Which code snippet correctly performs this task?

   • Adata = pickle.loads(received_bytes)
   • Bdata = pickle.load(received_bytes)
   • Cdata = pickle.dumps(received_bytes)
   • Ddata = bytes(received_bytes)
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2. 7foundation · easy

   Which statement correctly describes the relationship between persistence, serialization, and deserialization?

   • ADeserialization is the process of converting an object into a byte stream, and serialization is the reverse process of loading it back into memory.
   • BPersistence and serialization are synonyms, both referring to saving an object to disk, while deserialization is the process of deleting the saved data.
   • CSerialization converts an object into a storable format, deserialization reconstructs the object from that format, and persistence is the act of storing data so it outlives the program that created it.
   • DPersistence is the process of converting an object into a byte stream, while serialization is the process of saving that byte stream to a file.
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4. 8expert · hard

   A developer is responsible for a legacy Python application that uses pickle to serialize a custom class instance to a file. The class definition has changed: a new attribute was added, and an old attribute was renamed. When the application tries to load a previously saved pickle file, it fails with an AttributeError. The developer needs to load the old data and migrate it to the new class structure. What is the most appropriate approach?

   • ADelete the old pickle file and recreate the data from scratch.
   • BOpen the pickle file in a text editor and manually edit the attribute names.
   • CModify the class to temporarily include the old attribute name, load the pickle, and then migrate the data.
   • DUse pickle.loads() with a custom unpickler that ignores missing attributes.
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5. 9expert · hard

   A developer is using shelve to store a large dataset. The developer notices that the shelf file is growing much larger than expected. The developer suspects that deleted keys are not being removed from the file. Which action should the developer take to reclaim the space used by deleted keys?

   • ACall the sync() method on the shelf object.
   • BUse the shelve module's built-in compact() method.
   • CClose the shelf, delete the file, and recreate it from the remaining data.
   • DClose the shelf and reopen it with the 'n' flag.
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6. 10expert · hard

   A developer is using shelve to store session data. The developer opens the shelf in read-write mode and modifies a value. Later, the developer opens the same shelf in another part of the program and reads the value, but it still shows the old value. What is the most likely cause?

   • AThe developer did not call sync() or close() on the first shelf before opening the second one.
   • BThe developer used a different file name for the second shelf.
   • CThe developer used pickle instead of shelve for the second open.
   • DThe developer opened the second shelf in read-only mode.
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