In Python, integer literals can be written as a sequence of digits without any separators. Therefore, 1000000 is a valid representation of the integer one million. Since Python 3.6 (PEP 515), underscores can be used as visual separators for grouping digits in numeric literals to improve readability. The interpreter ignores these underscores. Thus, 1000000 is also a valid way to write the integer one million. Both methods result in a variable of type int with the value 1000000.

A. var = 1e6 creates a floating-point number (float), not an integer (int), due to the scientific 'e' notation.

C. var = 1.000.000 is a SyntaxError because periods are used for decimal points, and multiple decimal points in a number are not allowed.

E. var = 1,000,000 creates a tuple (1, 0, 0), as commas are used to separate elements in a tuple, not as digit groupers in a number.

1. Python Software Foundation. The Python Language Reference, Version 3.12. Section 2.4.4. Integer literals. The documentation states, "Underscores are permitted for grouping digits for enhanced readability. An underscore must be surrounded by digits or other underscores." This validates options B and D.

2. Python Software Foundation. PEP 515 -- Underscores in Numeric Literals. This official proposal, which was accepted and implemented, details the rationale and syntax for using underscores in numeric literals, directly supporting option B.

3. Python Software Foundation. The Python Language Reference, Version 3.12. Section 2.4.5. Floating-point literals. This section explains that the 'e' or 'E' notation is used to define floating-point numbers, which confirms why option A is incorrect for an int type.

4. Guttag, J.V. (2016). Introduction to Computation and Programming Using Python, With Application to Understanding Data. MIT Press. Chapter 2, Section 2.1 Objects, Expressions, and Numerical Types. This text clarifies that standard integer literals consist of a sequence of digits, and floating-point literals can use scientific notation.

The goal is to create a loop where the variable level iterates through the values 5, 3, and 1 (descending order).

1. for level in: This initiates the loop, defining level as the iterator variable.
2. range(5, 0, -2): The range function generates the sequence of numbers.

• Start (5,): The sequence begins at 5.
• Stop (0,): The sequence ends before reaching 0 (meaning it includes 1 but stops there).
• Step (-2): The values decrease by 2 in each iteration.

1. Result: The generated sequence is 5, then (5-2)=3, then (3-2)=1. The next value (-1) is less than the stop value (0), so the loop terminates.

Python Software Foundation. (n.d.). Built-in Types - Ranges. Python 3 Documentation. Retrieved from https://docs.python.org/3/library/stdtypes.html#range

Reference confirms the range(start, stop, step) constructor syntax and behavior for negative steps.

Python Software Foundation. (n.d.). Compound Statements - The for statement. Python 3 Documentation. Retrieved from https://docs.python.org/3/reference/compound_stmts.html#the-for-statement

Reference confirms the syntax for iterating over a sequence using for and in.

The expression is evaluated according to Python's operator precedence rules. First, the innermost parenthesized expression (312) is calculated as 36. Next, the subtraction within the remaining parentheses (36-8) results in 28. The expression simplifies to 2 + 9 28 / 10. Multiplication and division have equal precedence and are evaluated from left to right. 9 28 equals 252. Then, 252 / 10 is performed, resulting in 25.2 because the / operator performs true (floating-point) division. Finally, the addition 2 + 25.2 is executed, yielding the final result of 27.2.

A. 25: This answer is incorrect. It likely results from a miscalculation or an improper application of operator precedence, possibly involving incorrect rounding or integer division.

B. 22: This is an incorrect arithmetic result. It does not follow the standard order of operations (PEMDAS/BODMAS) as implemented in Python.

D. 27.6: This answer stems from a calculation error. For example, incorrectly calculating 9 28 as 256 would lead to 2 + 25.6, which equals 27.6.

1. Python Software Foundation. (2023). The Python Language Reference: 6.17. Operator precedence. Python 3.12.0 documentation. Retrieved from https://docs.python.org/3/reference/expressions.html#operator-precedence (This table confirms the order of operations: parentheses, followed by and / (left-to-right), and finally +.)

2. Guttag, J. V. (2016). Introduction to Computation and Programming Using Python, With Application to Understanding Data. MIT Press. (Chapter 2.2, "Objects, Expressions, and Numerical Types," discusses how expressions are formed from operators and operands and evaluated based on precedence rules.)

3. MIT OpenCourseWare. (2016). 6.0001 Introduction to Computer Science and Programming in Python, Fall 2016. Lecture 2: Objects, Expressions, Numerical Types. Retrieved from https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lec2/ (The lecture notes detail arithmetic operators and the evaluation order.)

To print "Unavailable," the program must trap the specific error raised by the try block. Accessing a non-existent key ("calzone") in a dictionary raises a KeyError. Therefore, the first box must contain except KeyError: to catch this specific exception and execute the immediate indented command print("Unavailable").

The second box requires a valid statement that accepts an indented block to maintain syntax validity. except: is the correct choice here, serving as a catch-all handler for any other exceptions. While it will not execute in this scenario (as the error is already caught), it is structurally required for the subsequent print("Out of bounds"). The pass statement is incorrect because it does not accept an indented block, which would cause an IndentationError.

Python Software Foundation. (n.d.). Errors and Exceptions - 8.3 Handling Exceptions. Python 3 Documentation. Retrieved from https://docs.python.org/3/tutorial/errors.html#handling-exceptions

Reference confirms the syntax for try...except blocks and that a class-based exception (like KeyError) matches if it is the same class or a base class.

Python Software Foundation. (n.d.). Built-in Exceptions - KeyError. Python 3 Documentation. Retrieved from https://docs.python.org/3/library/exceptions.html#KeyError

Reference confirms that a KeyError is raised when a mapping (dictionary) key is not found in the set of existing keys.

Python Software Foundation. (n.d.). Simple Statements - The pass statement. Python 3 Documentation. Retrieved from https://docs.python.org/3/reference/simple_stmts.html#the-pass-statement

Reference confirms pass is a null operation used when a statement is required syntactically but no code needs to be executed; it does not introduce a new indented block.

The del statement is Python's primary mechanism for unbinding a name from an object, effectively deleting the variable. The most direct syntax is del coursename. The syntax del(coursename) is also valid, as the parentheses simply group the target name. The globals() built-in function returns a dictionary representing the current global symbol table. Therefore, one can manipulate this dictionary directly to remove a variable, making del globals()['coursename'] a correct, albeit less common, method for deleting a global variable. These three methods successfully remove the coursename variable from the global scope.

A. remove is not a Python keyword for deleting variables; it is a method for mutable collection types like lists and sets.

C. rm is a command-line utility for removing files in Unix-like systems, not a valid statement or keyword in the Python language.

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1. Official Python Documentation, The Python Language Reference:

Section 7.4. The del statement: This section explicitly defines the syntax and semantics of the del statement for removing name bindings. It states, "Deletion of a name removes the binding of that name from the local or global namespace...". The syntax shown includes del targetlist, where a target can be a simple name like coursename.

URL: https://docs.python.org/3/reference/simplestmts.html#the-del-statement

2. Official Python Documentation, The Python Standard Library:

Built-in Functions, globals(): The documentation for globals() states, "Return a dictionary representing the current global symbol table. This is always the dictionary of the current module...". Modifying this returned dictionary, such as by deleting a key, directly modifies the global namespace.

URL: https://docs.python.org/3/library/functions.html#globals

3. MIT OpenCourseWare, 6.0001 Introduction to Computer Science and Programming in Python:

Lecture 5 Notes: In discussions on scopes and namespaces, the course materials explain that variables exist within specific namespaces (local, global, etc.). The del statement is introduced as the mechanism to remove a name from a namespace. The concept of the global namespace being accessible via globals() aligns with using dictionary operations on its return value.

Reference: MIT OCW 6.0001, Fall 2016, Lecture 5: Tuples, Lists, Aliasing, Mutability, Cloning. (The principles of namespaces and variable management are foundational in this lecture).

The code initializes x to 0 and enters a while loop that continues as long as x is less than 6. In each iteration, x is incremented by 1. The if statement checks if the new value of x is even (x % 2 == 0). If x is even, the continue statement is executed, which immediately skips the rest of the current iteration (the print statement) and starts the next one. Consequently, the print('') statement is only executed when x is odd. The loop runs for x values of 1, 2, 3, 4, 5, and 6. The star is printed for x = 1, x = 3, and x = 5, resulting in a total of three stars.

A. two: This is incorrect. The loop prints for three odd numbers (1, 3, and 5) before the condition x < 6 becomes false.

B. one: This count is too low. It incorrectly stops after the first successful print, ignoring subsequent iterations where x is also odd.

D. zero: This is incorrect. The print statement is reachable and executes whenever the if condition (x % 2 == 0) is false.

1. Python Software Foundation. (2024). The Python Tutorial, 4. More Control Flow Tools. Python 3.12.3 Documentation. Retrieved from https://docs.python.org/3/tutorial/controlflow.html#break-and-continue-statements-and-else-clauses-on-loops.

Reference Details: Section 4.4 explains that the continue statement "continues with the next iteration of the loop." This directly supports the analysis that the print statement is skipped for even numbers.

2. Guttag, J. V. (2016). Introduction to Computation and Programming Using Python, With Application to Understanding Data (2nd ed.). MIT Press.

Reference Details: Chapter 3, "Some Simple Numerical Programs," discusses iteration and the while loop. Section 3.2 specifically covers how loop control works, which is the core concept tested.

3. MIT OpenCourseWare. (2016). 6.0001 Introduction to Computer Science and Programming in Python, Fall 2016.

Reference Details: Lecture 3, "Branching, Conditionals, and Iteration," provides examples of while loops and conditional logic, which are fundamental to understanding the provided code snippet's behavior.

4. Python Institute. (2024). PCEP-30-02 – Exam Syllabus.

Reference Details: Section 3.2, "Loops – while, for, range(), break and continue, else," confirms that understanding the while loop and the continue statement is a required skill for the PCEP certification.

In Python, a scope refers to the region of a program where a name (such as a variable or function) is directly accessible. It defines the visibility and lifetime of that name. When Python encounters a name, it searches for its binding in a specific order of scopes: local, enclosing function, global, and finally, the built-in scope. This mechanism ensures that names used in one part of a program do not interfere with names in another, providing a structured way to manage objects and their accessibility.

A. This describes the len() built-in function, which returns the length or number of items of an object, not the concept of scope.

B. This describes the range() function or a general numerical interval, which is unrelated to the visibility and accessibility of names in code.

D. Scope is a conceptual rule about name resolution and program structure; it is not a built-in data type like an integer (int) or a string (str).

1. Python Software Foundation. "Python Scopes and Namespaces". The Python Tutorial, Section 9.2. The documentation states, "A scope is a textual region of a Python program where a namespace is directly accessible." This directly supports the definition in the correct answer. Available at: https://docs.python.org/3/tutorial/classes.html#python-scopes-and-namespaces

2. Python Software Foundation. "Naming and binding". The Python Language Reference, Section 4.2. This section details how scopes are determined and used: "A scope defines the visibility of a name within a block. If a local variable is defined in a block, its scope includes that block." Available at: https://docs.python.org/3/reference/executionmodel.html#naming-and-binding

3. Guttag, J. V. (2016). Introduction to Computation and Programming Using Python, With Application to Understanding Data (2nd ed.). MIT Press. Chapter 4, "Functions, Scoping, and Abstraction," explains that a function's scope is the part of the program in which its name is recognized. This aligns with the concept of availability and visibility.

To retrieve a value associated with a specific key from a Python dictionary and store it, you must use the assignment operator (=). The syntax for accessing a dictionary value requires placing the key inside square brackets ([]) immediately following the dictionary name.

1. Target Variable: number is placed on the left side of the assignment to receive the retrieved value.
2. Assignment: The = operator assigns the result of the expression on the right to the variable on the left.
3. Dictionary Access: phone_dir is the dictionary object. The key "Martin Eden" is enclosed in brackets [ and ] to look up the associated value (the phone number).

Python Software Foundation. (n.d.). The Python Tutorial: 5.5. Dictionaries. Python 3.12 Documentation. Retrieved from https://docs.python.org/3/tutorial/datastructures.html#dictionaries

Relevance: Explains that dictionaries are indexed by keys and demonstrates the syntax dictionary[key] for retrieving values.

Python Software Foundation. (n.d.). The Python Language Reference: 6.3.3. Subscription. Python 3.12 Documentation. Retrieved from https://docs.python.org/3/reference/expressions.html#subscription

Relevance: Defines the formal syntax for subscription (using square brackets) to select an item from a mapping (dictionary) object.

In Python, a single leading underscore () is a strong, widely-accepted convention outlined in PEP 8, the official style guide. It is used to indicate that a name (a variable or method) is intended for internal use within a class or module. This serves as a hint to other programmers that the name is not part of the public API and should be treated as a non-public implementation detail. Using this convention for a simple local variable is discouraged because it creates confusion, misrepresenting the variable's intended scope and clashing with its established meaning as a "private" or "protected" member of a class.

A. The Python interpreter is not confused by identifiers starting with an underscore; they are syntactically valid.

B. The common convention for global constants is all uppercase letters (e.g., MAXSIZE), not a leading underscore.

C. The naming of a variable has no impact on the code's execution speed or performance.

1. PEP 8 -- Style Guide for Python Code: In the "Naming Conventions" section, under "Descriptive: Naming Styles", it specifies: singleleadingunderscore: weak "internal use" indicator. E.g. from M import does not import objects whose names start with an underscore. (Source: https://peps.python.org/pep-0008/#naming-conventions)

2. The Official Python 3 Tutorial: Section 9.6, "Private Variables," explains that names prefixed with an underscore are treated by convention as non-public parts of an API. It states, "Since there is a valid use-case for class-private members... there is a convention that is honored by most Python code: a name prefixed with an underscore (e.g. spam) should be treated as a non-public part of the API." (Source: https://docs.python.org/3/tutorial/classes.html#private-variables)

3. MIT OpenCourseWare, Introduction to Computer Science and Programming in Python (Fall 2016): Lecture 8 notes on Object-Oriented Programming discuss encapsulation and mention that by convention, attributes starting with an underscore are intended to be private and not accessed directly from outside the class. (Source: MIT OCW, 6.0001, Lecture 8 Notes, Section on "Classes and Object-Oriented Programming").

The goal is to empty the list technames while keeping the list object itself intact. Both selected methods achieve this by modifying the list in-place.

The list.clear() method is the most direct and readable way to remove all elements from a list.

The statement del technames[:] uses slice notation. technames[:] selects all elements in the list, and the del statement then removes that slice. This effectively empties the list, producing the same result as clear(). Both operations leave technames as an empty list [].

del technames: This statement deletes the entire variable technames and its reference to the list object, rather than just clearing its contents. The name technames would no longer exist.

rm technames: rm is a shell command for removing files and is not valid Python syntax. It would raise a SyntaxError if executed in a Python interpreter.

1. Python 3.12.3 Documentation, Library Reference, 5.6. Sequence Types — list, tuple, range: In the section on "Mutable Sequence Types," the documentation explicitly states for the s.clear() method: "removes all items from s (same as del s[:])". This confirms both A and D are equivalent and correct operations.

Source: Official Python Documentation, docs.python.org/3/library/stdtypes.html#mutable-sequence-types

2. Python 3.12.3 Documentation, The Python Tutorial, 5.1. More on Lists: This section details list methods, including clear(), describing it as the method to "Remove all items from the list."

Source: Official Python Documentation, docs.python.org/3/tutorial/datastructures.html#more-on-lists

3. Python 3.12.3 Documentation, Language Reference, 7.2. The del statement: This section explains that del can be used on a slice. It states, "Deletion of a slice is equivalent to assignment of an empty slice of the right type." Assigning an empty slice to technames[:] would also clear the list.

Source: Official Python Documentation, docs.python.org/3/reference/simplestmts.html#the-del-statement