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question:# **Python Input Handling Challenge** In this assessment, you are required to write a Python function that simulates the various modes of input handling as described by the Python interpreter: complete program execution, file input parsing, interactive input parsing, and expression evaluation. # **Objective** Build a function `simulate_input_handling(input_type: str, input_content: str) -> str` that processes input based on different input types and returns the result of execution. # **Function Signature** ```python def simulate_input_handling(input_type: str, input_content: str) -> str: ``` # **Input** - `input_type`: a string, one of `"complete_program"`, `"file_input"`, `"interactive_input"`, and `"eval_input"`. This specifies the type of input handling to simulate. - `input_content`: a string representing the content to be executed or evaluated based on the input type. # **Output** - A string representing the result of execution or evaluation. # **Constraints** - Assume valid Python code is provided in `input_content`. - Handle exceptions gracefully and return error messages as strings. - Do not use `exec` for "complete_program" and "interactive_input" modes for security reasons. - Safeguard against potential infinite loops in the input content. # **Requirements** 1. For `input_type == "complete_program"`, simulate calling a complete program, ensuring all built-in and standard modules are minimally initialized except `sys`, `builtins`, and `__main__`. 2. For `input_type == "file_input"`, parse the input as if it was a file execution, maintaining its form. 3. For `input_type == "interactive_input"`, handle it as interactive mode execution, executing one statement at a time. 4. For `input_type == "eval_input"`, use the `eval()` function to parse and evaluate the expression. # **Example** ```python assert simulate_input_handling("complete_program", 'print("Hello World")') == "Hello Worldn" assert simulate_input_handling("file_input", 'x = 10ny = 20nz = x + ynprint(z)') == "30n" assert simulate_input_handling("interactive_input", 'x = 10ny = 20nz = x + ynprint(z)') == "30n" assert simulate_input_handling("eval_input", '3 + 5*2') == "13" ``` # **Note** This function requires thorough understanding of Python's code execution environment and careful handling of various input types. Focus on ensuring that result consistency reflects what would be the actual output by Python interpreter in respective modes.

answer:import io import sys def simulate_input_handling(input_type: str, input_content: str) -> str: old_stdout = sys.stdout redirected_output = sys.stdout = io.StringIO() try: if input_type == "complete_program": # We use a similar approach as running the script itself global_namespace = { "__name__": "__main__", "__doc__": None, "__package__": None, "__loader__": None, "__spec__": None, "__annotations__": {}, "__builtins__": __builtins__, } exec(input_content, global_namespace) elif input_type == "file_input": exec(input_content) elif input_type == "interactive_input": for line in input_content.splitlines(): exec(line) elif input_type == "eval_input": result = eval(input_content) print(result) else: raise ValueError("Invalid input type") except Exception as e: return str(e) finally: sys.stdout = old_stdout return redirected_output.getvalue()

question:**Objective**: Write a python function `perform_operations` that takes a list of operations to be performed on a list of numbers and returns the result. # Function Signature ```python def perform_operations(numbers: list, operations: list) -> list: pass ``` # Input 1. `numbers` (list of integers): A list of integers on which operations are to be performed. 2. `operations` (list of tuples): Each tuple corresponds to an operation. The first element of the tuple is a string that specifies the operation (`'add'`, `'sub'`, `'mul'`, `'truediv'`, `'floordiv'`, `'mod'`, `'pow'`, `'lshift'`, `'rshift'`, `'and'`, `'or'`, `'xor'`). The second and third elements are the indices of the numbers in the list on which the operation should be performed. # Output - A list of the same length as `numbers` where each element is the result of applying the specified operations. # Constraints - 2 <= len(numbers) <= 1000 - 1 <= len(operations) <= 1000 - The indices specified in each operation tuple will be valid indices within the list `numbers`. # Example ```python numbers = [1, 2, 3, 4, 5] operations = [ ('add', 0, 1), ('sub', 3, 2), ('mul', 2, 4), ('truediv', 4, 1) ] assert perform_operations(numbers, operations) == [3, -1, 15, 2.5] ``` # Note - You can import the required functions from the `operator` module to implement the solution. - Use exception handling to manage any potential division by zero or invalid operations gracefully by ignoring the invalid operation (do not perform the operation and proceed with the next). # Hints - Utilize the functions from the `operator` module to perform the operations. - Use list comprehensions and functional programming approaches where appropriate to keep the code clean and efficient.

answer:import operator def perform_operations(numbers: list, operations: list) -> list: # Mapping of string operation to function from operator module ops_map = { 'add': operator.add, 'sub': operator.sub, 'mul': operator.mul, 'truediv': operator.truediv, 'floordiv': operator.floordiv, 'mod': operator.mod, 'pow': operator.pow, 'lshift': operator.lshift, 'rshift': operator.rshift, 'and': operator.and_, 'or': operator.or_, 'xor': operator.xor } results = [] for op, idx1, idx2 in operations: try: func = ops_map[op] result = func(numbers[idx1], numbers[idx2]) results.append(result) except ZeroDivisionError: # When a division by zero occurs, skip the operation results.append("undefined") # Placeholder for division by zero except (KeyError, IndexError, TypeError): # Invalid operation, index out of range, or invalid type continue return results

question:**Objective:** To assess the student's understanding of the `contextvars` module in Python, specifically in asynchronous programming contexts. Problem Statement: You are required to create a concurrent data processing system where multiple tasks operate independently and use context variables to maintain and reset their state. Implement a system that allows the following: 1. Create a context variable to keep track of a task-specific identifier. 2. Create a context variable to maintain a counter for operations performed by a task. 3. Write an asynchronous function `process_data` that accepts task identifier and data list. It should: - Set the task-specific context variables. - Perform increment on the counter for each data item processed. - Retrieve and return the task identifier and operation count at the end of processing. 4. Use the `copy_context` method to create a new context for each task. Run multiple tasks concurrently using `asyncio.gather`. Input: - A list of tasks, where each task is represented as a tuple containing a task identifier (string) and a data list (list of integers). Output: - A list of task results, where each result is a dictionary with task identifier and operation count. Constraints: - Each task must operate in its own context independently. - No two tasks should interfere with each other's context. **Performance Requirements:** - Ensure the solution efficiently manages asynchronous operations. ```python import asyncio import contextvars # Declare context variables task_id_var = contextvars.ContextVar('task_id') operation_counter_var = contextvars.ContextVar('operation_counter', default=0) async def process_data(task_id, data): # Set context variables task_id_var.set(task_id) operation_counter_var.set(0) # Process data for _ in data: # Increment the counter for each data item processed current_count = operation_counter_var.get() operation_counter_var.set(current_count + 1) # Retrieve and return the context variable values final_id = task_id_var.get() final_count = operation_counter_var.get() return {"task_id": final_id, "operation_count": final_count} async def main(tasks): results = [] ctx = contextvars.copy_context() async def run_task_in_context(task): task_ctx = ctx.copy() return await task_ctx.run(process_data, task[0], task[1]) # Run all tasks concurrently results = await asyncio.gather(*(run_task_in_context(task) for task in tasks)) return results # Example usage: tasks = [ ("task1", [1, 2, 3]), ("task2", [4, 5]), ("task3", [6, 7, 8, 9]) ] asyncio.run(main(tasks)) ``` Test your implementation against the provided example usage to ensure correctness.

answer:import asyncio import contextvars # Declare context variables task_id_var = contextvars.ContextVar('task_id') operation_counter_var = contextvars.ContextVar('operation_counter', default=0) async def process_data(task_id, data): Processes data asynchronously, updating task-specific context variables. Args: task_id (str): The identifier for the task. data (list): The list of data items to process. Returns: dict: A dictionary containing the task identifier and operation count. # Set context variables task_id_var.set(task_id) operation_counter_var.set(0) # Process data for _ in data: # Increment the counter for each data item processed current_count = operation_counter_var.get() operation_counter_var.set(current_count + 1) # Retrieve and return the context variable values final_id = task_id_var.get() final_count = operation_counter_var.get() return {"task_id": final_id, "operation_count": final_count} async def main(tasks): Runs multiple tasks concurrently, each in its own context. Args: tasks (list): A list of tasks, where each task is represented as a tuple of task identifier and data list. Returns: list: A list of dictionaries containing the task identifier and operation count for each task. ctx = contextvars.copy_context() async def run_task_in_context(task): task_ctx = ctx.copy() return await task_ctx.run(process_data, task[0], task[1]) # Run all tasks concurrently results = await asyncio.gather(*(run_task_in_context(task) for task in tasks)) return results

question:# Student Management System You are tasked with implementing a simplified student management system using Python. Your system should allow you to store student records, each containing a unique ID, name, list of grades, and compute some aggregate data about the grades. Requirements: 1. Define a `Student` class with the following attributes and methods: - **Attributes**: - `student_id` (unique identifier, integer) - `name` (string) - `grades` (a list of integers, each between 0 and 100) - **Methods**: - `add_grade(grade: int)`: Adds a new grade to the student's list of grades. - `average_grade() -> float`: Returns the average of the student's grades. - `highest_grade() -> int`: Returns the highest grade. - `lowest_grade() -> int`: Returns the lowest grade. - `grade_summary() -> str`: Returns a string summarizing the student's grades in the format: "Student [student_id] - [name]: Grades = [grades], Average = [average], Highest = [highest], Lowest = [lowest]". 2. Create a function `create_student(student_id: int, name: str, grades: list[int] = []) -> Student` that returns a new student instance. 3. Implement a `manage_students()` function that: - Reads commands from the user to manage student records. The available commands should be: - `ADD_STUDENT <id> <name>`: Adds a new student with the given ID and name. - `ADD_GRADE <id> <grade>`: Adds a grade to the student with the given ID. - `SHOW_SUMMARY <id>`: Displays the grade summary for the student with the given ID. - `EXIT`: Ends the program. - Uses appropriate control flow statements and exception handling to manage inputs and possible errors. # Constraints: - You must use the `match` statement for pattern matching in command parsing. - The `Student` class should handle invalid grades (below 0 or above 100) by raising a `ValueError` with an appropriate message. - Student IDs should be unique, and attempting to add a student with an existing ID should raise a `ValueError`. # Example usage: ```python # Initialize a management system manage_students() # User commands: ADD_STUDENT 1 Alice ADD_GRADE 1 95 ADD_GRADE 1 85 SHOW_SUMMARY 1 # Output: Student 1 - Alice: Grades = [95, 85], Average = 90.0, Highest = 95, Lowest = 85 # Continue with more commands or end the program ``` Expectations: Your solution should showcase understanding of Python's control flow tools, function definitions, use of classes, and error handling. Ensure your code is well-organized, follows proper naming conventions, and includes comments where necessary.

answer:class Student: def __init__(self, student_id: int, name: str, grades: list[int] = None): if grades is None: grades = [] self.student_id = student_id self.name = name self.grades = grades def add_grade(self, grade: int): if not (0 <= grade <= 100): raise ValueError("Grade must be between 0 and 100.") self.grades.append(grade) def average_grade(self) -> float: if not self.grades: return 0.0 return sum(self.grades) / len(self.grades) def highest_grade(self) -> int: if not self.grades: return 0 return max(self.grades) def lowest_grade(self) -> int: if not self.grades: return 0 return min(self.grades) def grade_summary(self) -> str: avg = self.average_grade() highest = self.highest_grade() lowest = self.lowest_grade() return (f"Student {self.student_id} - {self.name}: Grades = {self.grades}, " f"Average = {avg}, Highest = {highest}, Lowest = {lowest}") def create_student(student_id: int, name: str, grades: list[int] = None) -> Student: return Student(student_id, name, grades) def manage_students(): students = {} while True: command = input("Enter command: ").strip() tokens = command.split() if not tokens: continue action = tokens[0] match action: case "ADD_STUDENT": if len(tokens) != 3: print("Invalid command format. Use: ADD_STUDENT <id> <name>") continue student_id = int(tokens[1]) name = tokens[2] if student_id in students: print(f"Student with ID {student_id} already exists.") else: students[student_id] = create_student(student_id, name) print(f"Added student {name} with ID {student_id}") case "ADD_GRADE": if len(tokens) != 3: print("Invalid command format. Use: ADD_GRADE <id> <grade>") continue student_id = int(tokens[1]) grade = int(tokens[2]) if student_id not in students: print(f"Student with ID {student_id} not found.") else: try: students[student_id].add_grade(grade) print(f"Added grade {grade} to student ID {student_id}") except ValueError as e: print(e) case "SHOW_SUMMARY": if len(tokens) != 2: print("Invalid command format. Use: SHOW_SUMMARY <id>") continue student_id = int(tokens[1]) if student_id not in students: print(f"Student with ID {student_id} not found.") else: print(students[student_id].grade_summary()) case "EXIT": print("Exiting program.") break case _: print("Unknown command.")