PCEP-30-02 Exam Dumps - Python Institute PCEP Questions and Answers

One possible way to drag and drop the literals to match their data type names is:

• STRING: “All The King’s Men”
• BOOLEAN: False
• INTEGER: 42
• FLOAT: -6.62607015E-34

A literal is a value that is written exactly as it is meant to be interpreted by the Python interpreter. A data type is a category of values that share some common characteristics or operations. Python has four basic data types: string, boolean, integer, and float.

A string is a sequence of characters enclosed by either single or double quotes. A string can represent text, symbols, or any other information that can be displayed as text. For example, “All The King’s Men” is a string literal that represents the title of a novel.

A boolean is a logical value that can be either True or False. A boolean can represent the result of a comparison, a condition, or a logical operation. For example, False is a boolean literal that represents the opposite of True.

An integer is a whole number that can be positive, negative, or zero. An integer can represent a count, an index, or any other quantity that does not require fractions or decimals. For example, 42 is an integer literal that represents the answer to life, the universe, and everything.

A float is a number that can have a fractional part after the decimal point. A float can represent a measurement, a ratio, or any other quantity that requires precision or approximation. For example, -6.62607015E-34 is a float literal that represents the Planck constant in scientific notation.

You can find more information about the literals and data types in Python in the following references:

• [Python Data Types]
• [Python Literals]
• [Python Basic Syntax]

number = phone_dir["Martin Eden"]

This code uses the square brackets notation to access the value associated with the key “Martin Eden” in the phone_dir dictionary. The value is then assigned to the variable number. A dictionary is a data structure that stores key-value pairs, where each key is unique and can be used to retrieve its corresponding value. You can find more information about dictionaries in Python in the following references:

• [Python Dictionaries - W3Schools]
• [Python Dictionary (With Examples) - Programiz]
• [5.5. Dictionaries — How to Think Like a Computer Scientist …]

The code snippet that you have sent is defining and calling a function in Python. The code is as follows:

def runner(brand, model, year): return (brand, model, year)

print(runner(“Fermi”))

The code starts with defining a function called “runner” with three parameters: “brand”, “model”, and “year”. The function returns a tuple with the values of the parameters. A tuple is a data type in Python that can store multiple values in an ordered and immutable way. A tuple is created by using parentheses and separating the values with commas. For example, (1, 2, 3) is a tuple with three values.

Then, the code calls the function “runner” with the value “Fermi” for the “brand” parameter and prints the result. However, the function expects three arguments, but only one is given. This will cause a TypeError exception, which is an error that occurs when a function or operation receives an argument that has the wrong type or number. The code does not handle the exception, and therefore it will terminate with an error message.

However, if the code had handled the exception, or if the function had used default values for the missing parameters, the expected output of the code would be ('Fermi ', ‘2021’, ‘False’). This is because the function returns a tuple with the values of the parameters, and the print function displays the tuple to the screen. Therefore, the correct answer is D. ('Fermi ', ‘2021’, ‘False’).

Exceptions and debugging are two important concepts in Python programming that are related to handling and preventing errors. Exceptions are errors that occur when the code cannot be executed properly, such as syntax errors, type errors, index errors, etc. Debugging is the process of finding and fixing errors in the code, using various tools and techniques. Some of the facts about exceptions and debugging are:

• A tool that allows you to precisely trace program execution is called a debugger. A debugger is a program that can run another program step by step, inspect the values of variables, set breakpoints, evaluate expressions, etc. A debugger can help you find the source and cause of an error, and test possible solutions. Python has a built-in debugger module called pdb, which can be used from the command line or within the code. There are also other third-party debuggers available for Python, such as PyCharm, Visual Studio Code, etc12
• If some Python code is executed without errors, this does not prove that there are no errors in it. It only means that the code did not encounter any exceptions that would stop the execution. However, the code may still have logical errors, which are errors that cause the code to produce incorrect or unexpected results. For example, if you write a function that is supposed to calculate the area of a circle, but you use the wrong formula, the code may run without errors, but it will give you the wrong answer. Logical errors are harder to detect and debug than syntax or runtime errors, because they do not generate any error messages. You have to test the code with different inputs and outputs, and compare them with the expected results34
• One try-except block may contain more than one except branch. A try-except block is a way of handling exceptions in Python, by using the keywords try and except. The try block contains the code that may raise an exception, and the except block contains the code that will execute if an exception occurs. You can have multiple except blocks for different types of exceptions, or for different actions to take. For example, you can write a try-except block like this:

try: # some code that may raise an exception except ValueError: # handle the ValueError exception except ZeroDivisionError: # handle the ZeroDivisionError exception except: # handle any other exception

This way, you can customize the error handling for different situations, and provide more informative messages or alternative solutions5

• The default (anonymous) except branch can be the last branch in the try-except block. The default except branch is the one that does not specify any exception type, and it will catch any exception that is not handled by the previous except branches. The default except branch can be the last branch in the try-except block, but it cannot be the first or the only branch. For example, you can write a try-except block like this:

try: # some code that may raise an exception except ValueError: # handle the ValueError exception except: # handle any other exception

This is a valid try-except block, and the default except branch will be the last branch. However, you cannot write a try-except block like this:

try: # some code that may raise an exception except: # handle any exception

This is an invalid try-except block, because the default except branch is the only branch, and it will catch all exceptions, even those that are not errors, such as KeyboardInterrupt or SystemExit. This is considered a bad practice, because it may hide or ignore important exceptions that should be handled differently or propagated further. Therefore, you should always specify the exception types that you want to handle, and use the default except branch only as a last resort5

Therefore, the correct answers are A. A tool that allows you to precisely trace program execution is called a debugger. and C. One try-except block may contain more than one except branch.

The correct order of the binary numeric operators in Python according to their priorities is:

• Exponentiation (**)
• Multiplication (*) and Division (/, //, %)
• Addition (+) and Subtraction (-)

This order follows the standard mathematical convention of operator precedence, which can be remembered by the acronym PEMDAS (Parentheses, Exponents, Multiplication/Division, Addition/Subtraction). Operators with higher precedence are evaluated before those with lower precedence, but operators with the same precedence are evaluated from left to right. Parentheses can be used to change the order of evaluation by grouping expressions.

For example, in the expression 2 + 3 * 4 ** 2, the exponentiation operator (**) has the highest priority, so it is evaluated first, resulting in 2 + 3 * 16. Then, the multiplication operator (*) has the next highest priority, so it is evaluated next, resulting in 2 + 48. Finally, the addition operator (+) has the lowest priority, so it is evaluated last, resulting in 50.

You can find more information about the operator precedence in Python in the following references:

• 6. Expressions — Python 3.11.5 documentation
• Precedence and Associativity of Operators in Python - Programiz
• Python Operator Priority or Precedence Examples Tutorial

The code snippet that you have sent is assigning a list of four values to a variable called “the_list”. The code is as follows:

the_list = [‘1’, 1, 1, 1]

The code creates a list object that contains the values ‘1’, 1, 1, and 1, and assigns it to the variable “the_list”. The list can be accessed by using the variable name or by using the index of the values. The index starts from 0 for the first value and goes up to the length of the list minus one for the last value. The index can also be negative, in which case it counts from the end of the list. For example, the_list[0] returns ‘1’, and the_list[-1] returns 1.

The expressions that you have given are trying to evaluate some conditions on the list and return a boolean value, either True or False. Some of them are valid, and some of them are invalid and will raise an exception. An exception is an error that occurs when the code cannot be executed properly. The expressions are as follows:

A. the_List.index {“1”} in the_list: This expression is trying to check if the index of the value ‘1’ in the list is also a value in the list. However, this expression is invalid, because it uses curly brackets instead of parentheses to call the index method. The index method is used to return the first occurrence of a value in a list. For example, the_list.index(‘1’) returns 0, because ‘1’ is the first value in the list. However, the_list.index {“1”} will raise a SyntaxError exception and output nothing.

B. 1.1 in the_list |1:3 |: This expression is trying to check if the value 1.1 is present in a sublist of the list. However, this expression is invalid, because it uses a vertical bar instead of a colon to specify the start and end index of the sublist. The sublist is obtained by using the slicing operation, which uses square brackets and a colon to get a part of the list. For example, the_list[1:3] returns [1, 1], which is the sublist of the list from the index 1 to the index 3, excluding the end index. However, the_list |1:3 | will raise a SyntaxError exception and output nothing.

C. len (the list [0:2]} <3: This expression is trying to check if the length of a sublist of the list is less than 3. This expression is valid, because it uses the len function and the slicing operation correctly. The len function is used to return the number of values in a list or a sublist. For example, len(the_list) returns 4, because the list has four values. The slicing operation is used to get a part of the list by using square brackets and a colon. For example, the_list[0:2] returns [‘1’, 1], which is the sublist of the list from the index 0 to the index 2, excluding the end index. The expression len (the list [0:2]} <3 returns True, because the length of the sublist [‘1’, 1] is 2, which is less than 3.

D. the_list. index {‘1’} – 0: This expression is trying to check if the index of the value ‘1’ in the list is equal to 0. This expression is valid, because it uses the index method and the equality operator correctly. The index method is used to return the first occurrence of a value in a list. For example, the_list.index(‘1’) returns 0, because ‘1’ is the first value in the list. The equality operator is used to compare two values and return True if they are equal, or False if they are not. For example, 0 == 0 returns True, and 0 == 1 returns False. The expression the_list. index {‘1’} – 0 returns True, because the index of ‘1’ in the list is 0, and 0 is equal to 0.

Therefore, the correct answers are C. len (the list [0:2]} <3 and D. the_list. index {‘1’} – 0.

In Python, the ** operator is used for exponentiation, the / operator is used for floating-point division, and the // operator is used for integer division. The order of operations is parentheses, exponentiation, multiplication/division, and addition/subtraction. Therefore, the expressions can be evaluated as follows:

A. 2 ** 3 / A - 2 = 8 / A - 2 (assuming A is a variable that is not zero or undefined) B. 4 / 2 * * 3 - 2 = 4 / 8 - 2 = 0.5 - 2 = -1.5 C. 1 * * 3 / 4 - 1 = 1 / 4 - 1 = 0.25 - 1 = -0.75 D. 1 * 4 // 2 ** 3 = 4 // 8 = 0

Only expressions A and B evaluate to non-zero results.

Syntax is the branch of linguistics that studies the structure and rules of sentences in natural languages. Lexis is the vocabulary of a language. Semantics is the study of meaning in language. A dictionary is a collection of words and their definitions, synonyms, pronunciations, etc.