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| Section | Objectives |
|---|
| Topic 1: Network Programming and Communication | - Web communication basics
- 1. Data exchange formats
- 2. HTTP requests and APIs
|
| Topic 2: GUI Programming | - Tkinter fundamentals
- 1. Widgets and layout management
- 2. Event handling
|
| Topic 3: Python Standard Library and Best Practices | - Testing and debugging
- 1. Unit testing with unittest/pytest concepts
- 2. Debugging techniques
- File and data processing
- 1. Serialization (JSON, CSV)
- 2. Working with files and directories
|
| Topic 4: Advanced Object-Oriented Programming | - Metaprogramming basics
- 1. Introspection techniques
- 2. Decorators and class decorators
- Class design and advanced inheritance
- 1. Multiple inheritance and MRO
- 2. Abstract classes and interfaces
|
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Python Institute PCPP1 - Certified Professional in Python Programming 1 Sample Questions (Q14-Q19):
NEW QUESTION # 14
Select the true statements related to PEP 257. (Select two answers.)
- A. There are two types of docstrings in Python: one-line and multi-line docstrings.
- B. The closing quotes of a one-line docstring should be put on a separate line.
- C. A docstring is a string literal that occurs anywhere in Python code, and is used to document Python functions, classes, and public methods.
- D. A docstring is a string literal that occurs as the first statement in a Python module, function, class, or method, and is used to document them.
Answer: A,D
Explanation:
The correct answers are C and D. PEP 257 defines a docstring as a string literal that appears as the first statement in a module, function, class, or method definition. This placement is important because Python assigns that string to the object's __doc__ attribute, making it available to tools such as help(), IDEs, documentation generators, and introspection utilities. Option D is also correct because PEP 257 distinguishes between one-line docstrings and multi-line docstrings. Option A is false because a one-line docstring keeps its closing quotes on the same line. Option B is too broad: ordinary string literals appearing anywhere in code are not automatically treated as official runtime docstrings.
NEW QUESTION # 15
What is a___traceback___?
(Select two answers )
- A. An attribute that is added to every object when the traceback module is imported
- B. A special method delivered by the traceback module to retrieve a full list of strings describing the traceback
- C. An attribute that holds interesting information that is particularly useful when the programmer wants to store exception details in other objects
- D. An attribute owned by every exception object
Answer: C,D
Explanation:
The correct answers are A. An attribute owned by every exception object and D. An attribute that holds interesting information that is particularly useful when the programmer wants to store exception details in other objects . A traceback is an attribute of an exception object that contains a stack trace representing the call stack at the point where the exception was raised. The traceback attribute holds information about the sequence of function calls that led to the exception, which can be useful for debugging and error reporting.
NEW QUESTION # 16
Select the true statements about the json.-dumps () function. (Select two answers.)
- A. It returns a JSON string.
- B. It takes Python data as its argument.
- C. It takes a JSON string as its argument
- D. It returns a Python entity.
Answer: A,B
Explanation:
The json.dumps() function is used to convert a Python object into a JSON string 1 . It takes Python data as its argument, such as a dictionary or a list, and returns a JSON string.
Reference: Official Python documentation on json.dumps(): https://docs.python.org/3/library/json.html#json.
dumps
A). It returns a JSON string.
This statement is true because the json.dumps () function takes a Python object as its argument and returns a JSON-formatted string that represents the object. For example, json.dumps ([1, 2, 3]) returns '[1, 2, 3] '.
D). It takes Python data as its argument.
This statement is true because the json.dumps () function accepts any Python object that can be serialized into JSON, such as lists, dictionaries, strings, numbers, booleans, or None. For example, json.dumps ({"name":
"Alice", "age": 25}) returns '{"name": "Alice", "age": 25}'.
NEW QUESTION # 17
What is the result of the following code?

What is the result of the following code?
- A. Loading data...
- B. Nothing will be displayed
- C. Debugging mode has been enabled
- D. Debugging mode has been enabled Loading data...
Answer: A
Explanation:
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...
NEW QUESTION # 18
In the JSON processing context, the term serialization:
- A. names a process in which a JSON string is remodeled and transformed into a new JSON string
- B. names a process in which Python data is turned into a JSON string.
- C. refers to nothing, because there is no such thing as JSON serialization.
- D. names a process in which a JSON string is turned into Python data.
Answer: B
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 # 19
......
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