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question:# Advanced Python Coding Task: Implementing a Custom Protocol and Transport Objective Demonstrate your understanding of the asyncio library's transports and protocols by creating a custom UDP protocol that manages a basic echo service and tracks some connection statistics. Problem Description You are required to implement a UDP echo server that: 1. **Echos Received Messages**: When the server receives a message, it should send back the same message to the sender. 2. **Tracks Connection Statistics**: - Total number of messages received. - Total bytes received. - Number of unique clients connected. Create a UDP echo server using asyncio's datagram API. The server should listen on IP `127.0.0.1` and port `9999`. Requirements 1. Implement a custom protocol class `EchoServerProtocol`. 2. The `EchoServerProtocol` should override the following methods from `asyncio.DatagramProtocol`: - `connection_made(transport)`: to set up the transport. - `datagram_received(data, addr)`: to handle incoming data. - `connection_lost(exc)`: to finalize the transport when the connection is lost. 3. Define a method `get_stats()` within `EchoServerProtocol` that returns the current statistics: total messages received, total bytes received, and number of unique clients. 4. Create a coroutine `start_server()` that sets up the server to listen on the specified IP and port. Expected Input and Output - The protocol does not expect any input from the user during its initialization. - The server will handle incoming UDP datagrams automatically. - The method `get_stats()` should output a dictionary with the following structure: ```python { "messages_received": <int>, "bytes_received": <int>, "unique_clients": <int> } ``` Constraints - Use only standard library modules. - Ensure thread safety where applicable. - Handle potential exceptions or errors in your implementation gracefully. Example Here is a brief example to demonstrate the usage of the server: ```python import asyncio class EchoServerProtocol(asyncio.DatagramProtocol): def __init__(self): self.transport = None self.messages_received = 0 self.bytes_received = 0 self.unique_clients = set() def connection_made(self, transport): self.transport = transport def datagram_received(self, data, addr): message = data.decode() print(f"Received {message} from {addr}") self.messages_received += 1 self.bytes_received += len(data) self.unique_clients.add(addr) self.transport.sendto(data, addr) # Echo the message back def connection_lost(self, exc): print("Connection lost") def get_stats(self): return { "messages_received": self.messages_received, "bytes_received": self.bytes_received, "unique_clients": len(self.unique_clients) } async def start_server(): loop = asyncio.get_running_loop() transport, protocol = await loop.create_datagram_endpoint( lambda: EchoServerProtocol(), local_addr=('127.0.0.1', 9999)) # Serve for a specified duration or forever try: await asyncio.sleep(3600) # Adjust the duration as required finally: transport.close() # Example usage asyncio.run(start_server()) ``` Performance Requirements - The server should handle multiple clients efficiently. - Ensure minimal latency in echoing messages back to the clients. Good luck, and happy coding!
answer:import asyncio class EchoServerProtocol(asyncio.DatagramProtocol): def __init__(self): self.transport = None self.messages_received = 0 self.bytes_received = 0 self.unique_clients = set() def connection_made(self, transport): self.transport = transport def datagram_received(self, data, addr): self.messages_received += 1 self.bytes_received += len(data) self.unique_clients.add(addr) self.transport.sendto(data, addr) # Echo the message back def connection_lost(self, exc): print("Connection closed") def get_stats(self): return { "messages_received": self.messages_received, "bytes_received": self.bytes_received, "unique_clients": len(self.unique_clients) } async def start_server(): loop = asyncio.get_running_loop() transport, protocol = await loop.create_datagram_endpoint( lambda: EchoServerProtocol(), local_addr=('127.0.0.1', 9999) ) return transport, protocol # To run the server, use asyncio.run(start_server())
question:# Python Coding Assessment Problem Statement You are tasked with customizing the representation of large lists such that their output size is limited. Specifically, you need to subclass the `Repr` class from the `reprlib` module to achieve this. Your subclass should implement a method that handles `list` objects, limiting the number of list elements displayed to a maximum of 10 and representing nested lists correctly with the same constraints. Requirements 1. Your custom class should be named `CustomRepr`. 2. Implement a method `repr_list(obj, level)` within `CustomRepr` to handle lists. 3. The method should limit the display of list elements to at most 10 elements. 4. For nested lists, apply the same constraints recursively. 5. You need to modify the `CustomRepr` class only for handling list objects. Input - A list of integers or nested lists of integers. Output - A string representation of the list conforming to the specified constraints. Constraints - List elements can be either integers or other lists (nested 2 levels deep). Example ```python from reprlib import Repr # Here, CustomRepr is your subclass class CustomRepr(Repr): def __init__(self): super().__init__() self.maxlist = 10 def repr_list(self, obj, level): if level <= 0: # Base case for recursion return '...' # Limiting number of list elements new_list = obj[:self.maxlist] represented_elements = [self.repr1(item, level - 1) for item in new_list] # Handle case when list was longer than maxlist if len(obj) > self.maxlist: represented_elements.append('...') return '[' + ', '.join(represented_elements) + ']' def main(): aRepr = CustomRepr() test_input = list(range(20)) # List with 20 elements nested_input = [list(range(5)), list(range(12)), list(range(3))] print(aRepr.repr(test_input)) # Expected: '[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ...]' print(aRepr.repr(nested_input)) # Expected: '[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ...], [0, 1, 2]]' if __name__ == "__main__": main() ``` Your task is to implement the `CustomRepr` class and complete the `repr_list` method to meet the specified requirements. **Note**: Use the `reprlib` module and the `Repr` class as a foundation for your implementation.
answer:from reprlib import Repr class CustomRepr(Repr): def __init__(self): super().__init__() self.maxlist = 10 def repr_list(self, obj, level): if level <= 0: # Base case for recursion return '...' # Limiting number of list elements new_list = obj[:self.maxlist] represented_elements = [self.repr1(item, level - 1) for item in new_list] # Handle case when list was longer than maxlist if len(obj) > self.maxlist: represented_elements.append('...') return '[' + ', '.join(represented_elements) + ']'
question:# Question: Implement a Secure File Integrity Verifier **Objective:** You need to implement a Python program that verifies the integrity of files using SHA256 and BLAKE2b hash algorithms. The program will generate and verify hash values to ensure that the files have not been tampered with. **Details:** 1. **Function 1: `generate_file_hashes`** - **Input:** - `file_path` (string): The path to the file to be hashed. - **Output:** - A dictionary with two keys: `sha256` and `blake2b`, each containing the hexadecimal digest of the file. - **Constraints:** - The file should be read in chunks to handle large files without consuming excessive memory. 2. **Function 2: `verify_file_hashes`** - **Input:** - `file_path` (string): The path to the file to be verified. - `expected_hashes` (dictionary): A dictionary with two keys: `sha256` and `blake2b`, each containing the expected hexadecimal digest string of the file. - **Output:** - Boolean: `True` if both hashes match the expected values, otherwise `False`. - **Constraints:** - The file should be read in chunks to handle large files without consuming excessive memory. **Example Usage:** ```python # Example file path file_path = 'example.txt' # Generate hashes for the file hashes = generate_file_hashes(file_path) print(hashes) # Output might look like: # {'sha256': 'a5b8c...d7f', 'blake2b': '6ff84...1a3'} # Verify the file integrity is_valid = verify_file_hashes(file_path, hashes) print(is_valid) # True # Tamper with the file and check again with open(file_path, 'a') as f: f.write('extra data') is_valid = verify_file_hashes(file_path, hashes) print(is_valid) # False ``` **Note:** - Ensure you handle file I/O errors gracefully. - Make sure to use efficient mechanisms to read and hash large files in chunks. - You can use `hashlib`'s `sha256()` and `blake2b()` functions as demonstrated in the documentation.
answer:import hashlib def generate_file_hashes(file_path): Generate SHA256 and BLAKE2b hashes for the given file. :param file_path: The path to the file to be hashed :return: A dictionary with 'sha256' and 'blake2b' keys containing the hexadecimal hash digests sha256_hash = hashlib.sha256() blake2b_hash = hashlib.blake2b() try: with open(file_path, 'rb') as file: while chunk := file.read(8192): sha256_hash.update(chunk) blake2b_hash.update(chunk) return { 'sha256': sha256_hash.hexdigest(), 'blake2b': blake2b_hash.hexdigest() } except IOError as e: print(f"Error reading file {file_path}: {e}") return None def verify_file_hashes(file_path, expected_hashes): Verify the integrity of a file by comparing its hashes to expected values. :param file_path: The path to the file to be verified :param expected_hashes: A dictionary with 'sha256' and 'blake2b' keys containing the expected hexadecimal hash digests :return: True if both hashes match the expected values, otherwise False generated_hashes = generate_file_hashes(file_path) if not generated_hashes: return False return (generated_hashes['sha256'] == expected_hashes['sha256'] and generated_hashes['blake2b'] == expected_hashes['blake2b'])
question:# Task You are required to implement an XML-RPC server using the `xmlrpc.server` module that performs the following: 1. Create an instance of `SimpleXMLRPCServer`. 2. Register several built-in Python functions such as `pow`, `abs`, and `max`. 3. Implement and register a custom function named `concatenate_strings` that takes two string arguments and returns their concatenation. 4. Register a class named `MathOperations` with methods: - `add`: Returns the sum of two numbers. - `subtract`: Returns the difference between two numbers. 5. Set up the server to listen on localhost at port `8080`. Additionally, include the client code that demonstrates how to call the registered functions using the XML-RPC protocol. # Requirements 1. **Server Implementation**: - Use `SimpleXMLRPCServer` to create the server. - Register the functions and class as described. 2. **Client Implementation**: - Use `xmlrpc.client.ServerProxy` to interact with the server. - Demonstrate calling each registered function and method. # Input/Output - **Server Side**: - Implement functions and class methods to be called via XML-RPC. - Start the server to handle XML-RPC requests. - **Client Side**: - Connect to the server and invoke the registered functions and methods. - Print the results of the calls to demonstrate proper functionality. # Constraints - Ensure the server handles multiple client requests concurrently. - Utilize necessary encryption or validation mechanisms to prevent malicious attacks as the server is exposed over a network. # Performance Requirements - The server should be capable of handling up to 100 concurrent requests. # Example Server Code Example ```python from xmlrpc.server import SimpleXMLRPCServer # Custom function def concatenate_strings(s1, s2): return s1 + s2 # Class for additional operations class MathOperations: def add(self, x, y): return x + y def subtract(self, x, y): return x - y # Setting up the server with SimpleXMLRPCServer(('localhost', 8080)) as server: server.register_function(pow) server.register_function(abs) server.register_function(max) server.register_function(concatenate_strings) server.register_instance(MathOperations()) print("Serving XML-RPC on localhost port 8080") server.serve_forever() ``` Client Code Example ```python import xmlrpc.client # Connect to the server proxy = xmlrpc.client.ServerProxy('http://localhost:8080') # Call the registered functions and methods print(proxy.pow(2, 3)) # Output: 8 print(proxy.abs(-10)) # Output: 10 print(proxy.max(1, 5, 3)) # Output: 5 print(proxy.concatenate_strings("Hello, ", "world!")) # Output: "Hello, world!" print(proxy.add(10, 5)) # Output: 15 print(proxy.subtract(10, 5)) # Output: 5 ``` Ensure to handle any exceptions and edge cases where input might be invalid or connections might fail.
answer:from xmlrpc.server import SimpleXMLRPCServer import threading # Custom function def concatenate_strings(s1, s2): return s1 + s2 # Class for additional operations class MathOperations: def add(self, x, y): return x + y def subtract(self, x, y): return x - y def run_server(): # Setting up the server with SimpleXMLRPCServer(('localhost', 8080)) as server: server.register_function(pow) server.register_function(abs) server.register_function(max) server.register_function(concatenate_strings) server.register_instance(MathOperations()) print("Serving XML-RPC on localhost port 8080") server.serve_forever() # Run server in a separate thread to allow client interaction for testing server_thread = threading.Thread(target=run_server, daemon=True) server_thread.start()