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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Multithreading and Concurrency | 10% | - Concurrent programming
|
| Topic 2: Python Standard Library and Best Practices | 10% | - Advanced Python development
|
| Topic 3: Network Programming | 20% | - Communication and networking
|
| Topic 4: Advanced Object-Oriented Programming | 25% | - Object-oriented concepts
|
| Topic 5: File Processing and Serialization | 15% | - Data storage and transfer
|
| Topic 6: GUI Programming | 20% | - Graphical user interfaces with Tkinter
|
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NEW QUESTION # 41
Which of the following methods allow you to load a configuration using ConfigParser? (Select two answers.)
Answer: A,C
Explanation:
Explanation
ConfigParser is a built-in library in Python that allows you to read and write configuration files. The read method is used to read the configuration file which can be in any of the supported file formats, such as INI, YAML, and JSON. The read_dict method is used to read the configuration from a Python dictionary. The read_conf and read_str options are not valid methods in the ConfigParser module.
Therefore, the correct options to load a configuration using ConfigParser are A. read and D. read_string.
NEW QUESTION # 42
In the JSON processing context, the term serialization:
Answer: D
Explanation:
In the JSON processing context, the term serialization: A. names a process in which Python data is turned into a JSON string.
Serialization refers to the process of converting a data object, such as a Python object, into a format that can be easily transferred over a network or stored in a file. In the case of JSON, serialization refers to converting Python data into a string representation using the JSON format. This string can be sent over a network or stored as a file, and later deserialized back into the original Python data object.
Reference: Official Python documentation on json: https://docs.python.org/3/library/json.html#json- serialization
NEW QUESTION # 43
In the JSON processing context, the term serialization:
Answer: D
Explanation:
Explanation
In the JSON processing context, the term serialization: A. names a process in which Python data is turned into a JSON string.
Serialization refers to the process of converting a data object, such as a Python object, into a format that can be easily transferred over a network or stored in a file. In the case of JSON, serialization refers to converting Python data into a string representation using the JSON format. This string can be sent over a network or stored as a file, and later deserialized back into the original Python data object.
NEW QUESTION # 44
Select the true statements related to PEP 8 naming conventions. (Select two answers.)
Answer: C,D
Explanation:
The correct answers are C and D. PEP 8 recommends that module names should be short and entirely lower-case; underscores may be used only when they improve readability. This keeps imports clean and predictable. PEP 8 also warns against using the single-character variable names l, O, or I because they can be visually confused with 1 and 0 in many fonts. Option A is incorrect because Python class names should normally use the CapWords convention, not mixedCase. Option B is incorrect because exception names are class names and should follow class naming conventions; if the exception represents an error, the name should usually end with Error.
NEW QUESTION # 45
Analyze the following function and choose the statement that best describes it.
Answer: A
Explanation:
Explanation
In the given code snippet, the repeat function is a decorator that takes an argument num_times specifying the number of times the decorated function should be called. The repeat function returns an inner function wrapper_repeat that takes a function func as an argument and returns another inner function wrapper that calls func num_times times.
The provided code snippet represents an example of a decorator that accepts its own arguments.
The @decorator_function syntax is used to apply the decorator_function to the some_function function.
The decorator_function takes an argument arg1 and defines an inner function wrapper_function that takes the original function func as its argument. The wrapper_function then returns the result of calling func, along with the arg1 argument passed to the decorator_function.
Here is an example of how to use this decorator with some_function:
@decorator_function("argument 1")
defsome_function():
return"Hello world"
When some_function is called, it will first be passed as an argument to the decorator_function.
The decorator_function then adds the string "argument 1" to the result of calling some_function() and returns the resulting string. In this case, the final output would be "Hello world argument 1".
NEW QUESTION # 46
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