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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Network Programming | 18% | - REST API Basics - JSON/XML Data Exchange - HTTP & Client-Server Communication - TCP/IP & Socket Programming |
| Topic 2: Advanced Object-Oriented Programming | 25% | - Attribute Access & Descriptors - Design Patterns - Advanced Exceptions & Exception Chaining - Metaclasses & Metaprogramming - Abstract Base Classes - Shallow vs Deep Copy & Serialization - Multiple Inheritance & Mixins |
| Topic 3: File & Data Processing | 15% | - Logging & System Interaction - SQLite3 Database Operations - CSV & Configuration Files - XML & JSON Parsing |
| Topic 4: GUI Programming | 20% | - Event Handling & Callbacks - Event-Driven Paradigm - Tkinter Basics & Widgets - Dialogs & Application Structure |
| Topic 5: Modules, Packages & Advanced Features | 10% | - Decorators & Context Managers - Import System & Namespaces - Functional Programming Tools |
| Topic 6: Coding Conventions, Best Practices & Standardization | 12% | - PEP 1, PEP 8, PEP 20, PEP 257 - Pythonic Principles - Code Readability & Documentation |
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NEW QUESTION # 51
What is true about the invocation of the cget () method?
Answer: D
Explanation:
The cget() method in Python is used to read the configuration options of a widget in Tkinter. It retrieves the value of a specified configuration option for a Tkinter widget. Hence, option A is the correct answer.
NEW QUESTION # 52
Which of the following types cannot be pickled?
Answer: D
Explanation:
The correct answer is B because Python's pickle module can serialize many built-in data types, including integers, floating-point numbers, complex numbers, strings, bytes, bytearrays, booleans, and None. However, it does not serialize the actual implementation or definition body of functions and classes. Top-level functions and classes may sometimes be pickled by reference using their fully qualified names, but their code definitions are not stored inside the pickle byte stream. This distinction matters: pickle records enough information to locate an object again during unpickling, but it does not preserve source code, nested definitions, lambda functions, or dynamically created definitions in a portable way. Therefore, "function and class definitions" is the option that cannot truly be pickled as definitions.
NEW QUESTION # 53
Select a log that matches the following format:
'%(name)s[%(levelname)s][%(asctime)s] :%(message)s'
Answer: B
NEW QUESTION # 54
Which one of the following methods allows you to debug an XML tree in the xml.etree ELementTree module?
Answer: B
Explanation:
The dump() method in the xml.etree.ElementTree module allows you to output a debug representation of an XML tree to a file or standard output. This method is useful for analyzing the structure of the tree and tracking down errors.
Reference: Official Python documentation on the ElementTree module: https://docs.python.org/3/library/xml.
etree.elementtree.html
NEW QUESTION # 55
Select the true statements about the json.-dumps () function. (Select two answers.)
Answer: A,D
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 # 56
......
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