Python Institute PCPP-32-101 Dumps Questions Answers

Answer: A. Deserialization is the process of converting data that has been serialized or encoded in a specific format, back into its original form as an object or a data structure in memory. In Python, this typically involves creating Python objects based on sequences of bytes that have been serialized using a protocol such as JSON, Pickle, or YAML.

For example, if you have a Python object my_obj and you want to serialize it to a JSON string, you might do something like this:

importjson

serialized_obj = json.dumps(my_obj)

To deserialize the JSON string back into a Python object, you would use the json.loads() method:

deserialized_obj = json.loads(serialized_obj)

This would convert the JSON string back into its original Python object form.

Option B is correct because it sets the font option of the button to a tuple containing the font family (‘Arial’), size (12), and style (‘italic’).

Option C is correct because it sets the font option of the button to a string containing the font family (‘Arial’), size (12), and style (‘italic’) separated by spaces.

This statement is true because the code uses the logging module to create a logger object and set its level to logging.INFO. The logging module provides a way of reporting events that occur during the execution of a program. The logging level determines which events are reported and which are ignored. The logging module defines five levels of severity: DEBUG, INFO, WARNING, ERROR, and CRITICAL. The lower the level, the more events are reported.

The code then uses the logger object to log two messages: one with the level logging.DEBUG and one with the level logging.INFO. The logger object only reports the messages that have a level equal or higher than its own level. Therefore, the message with the level logging.DEBUG is ignored, while the message with the level logging.INFO is reported. The default format for reporting messages is “level name: message”. Therefore, the output of the code is:

INFO: Loading data…