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question:# File Organizer using `os` Module **Objective**: Implement a function to organize files in a given directory based on their file extension. The files will be moved into subdirectories named after their extensions. **Instructions**: Implement the function `organize_files_by_extension(directory: str) -> None` that takes a path to a directory as input and organizes the files inside this directory into subdirectories based on their file extensions. Your function should handle the following: 1. Create subdirectories for each file extension if they do not exist. 2. Move the files into their corresponding subdirectory based on their extension. 3. If a file does not have an extension, move it to a subdirectory named "no_extension". **Constraints**: 1. `directory` is guaranteed to be a valid path. 2. The function should handle cases where the directory contains nested subdirectories but should only organize files at the top level of the given directory. 3. Ensure the function handles edge cases such as empty directories gracefully. 4. Use only the `os` module for this task. **Example**: Suppose the directory `/path/to/directory` contains the following files and subdirectories: ``` /path/to/directory - file1.txt - file2.pdf - file3 - image1.png - image2.jpg - doc1.doc - readme.md - subdir/ - nested_file.txt ``` After calling `organize_files_by_extension('/path/to/directory')`, the directory should look like: ``` /path/to/directory - txt/ - file1.txt - pdf/ - file2.pdf - no_extension/ - file3 - png/ - image1.png - jpg/ - image2.jpg - doc/ - doc1.doc - md/ - readme.md - subdir/ - nested_file.txt ``` **Function Signature**: ```python def organize_files_by_extension(directory: str) -> None: pass ``` **Hints**: 1. Use `os.listdir()` to list the files in the directory. 2. Use `os.path.splitext()` to get the file extension. 3. Use `os.makedirs()` to create directories. 4. Use `os.rename()` or `os.replace()` to move files.
answer:import os def organize_files_by_extension(directory: str) -> None: if not os.path.exists(directory) or not os.path.isdir(directory): raise ValueError("The specified directory is not valid.") # Get the list of files and directories in the specified directory items = os.listdir(directory) for item in items: item_path = os.path.join(directory, item) # Check if the item is a file (not a directory) if os.path.isfile(item_path): _, extension = os.path.splitext(item) if extension: extension = extension[1:] # Remove the leading dot else: extension = "no_extension" new_dir = os.path.join(directory, extension) if not os.path.exists(new_dir): os.makedirs(new_dir) # Generate the new path for the file new_path = os.path.join(new_dir, item) # Move the file to the new directory os.rename(item_path, new_path)
question:# Custom SMTP Server Implementation **Objective**: Implement a custom SMTP server that processes incoming email messages and performs specific actions based on the email content. Problem Statement You are required to implement a custom SMTP server using the `smtpd` module provided by Python. The server should: 1. **Bind** to the local address `(localhost, 1025)`. 2. **Print** the details (peer, mailfrom, rcpttos, data) of every incoming message to the console. 3. **Respond** with a custom message if the subject of the email contains the word "Important". 4. **Handle** the SMTPUTF8 extension if enabled. Implementation Details 1. Create a subclass of `smtpd.SMTPServer` named `CustomSMTPServer`. 2. Override the `process_message` method to print incoming message details and check for the word "Important" in the email subject line. 3. The `process_message` method should accept `peer`, `mailfrom`, `rcpttos`, `data`, and `**kwargs` as its parameters and return appropriate responses. 4. The server should handle the `SMTPUTF8` extension if enabled. Input - You do not need to handle any input directly as part of this question. The server should be programmatically configured to bind to the specified address. Output - Print the following details for every incoming email: - Peer address - Mail from - Recipients (rcpttos) - Email data (content) - If the email subject contains the word "Important", return a custom response: `"250 Ok - Priority message received"`. - Otherwise, return the standard response: `"250 Ok"`. Constraints - The server must handle emails up to a size of 10 MB. - Both `decode_data` and `enable_SMTPUTF8` cannot be set to `True` simultaneously. Performance Requirements - The server should efficiently process incoming emails and respond promptly as per the SMTP protocol standards. Example Implementation ```python import smtpd import asyncore import email from email import policy class CustomSMTPServer(smtpd.SMTPServer): def process_message(self, peer, mailfrom, rcpttos, data, **kwargs): print(f"Peer: {peer}") print(f"Mail from: {mailfrom}") print(f"Recipients: {rcpttos}") print(f"Data: {data}") # Parse email data message = email.message_from_bytes(data, policy=policy.default) subject = message['subject'] # Check for 'Important' in subject if subject and "Important" in subject: return "250 Ok - Priority message received" return "250 Ok" # Initialize server server = CustomSMTPServer(('localhost', 1025), None, data_size_limit=10*1024*1024) # Start asyncore loop asyncore.loop() ``` **Explanation**: - Define a `CustomSMTPServer` class that inherits from `smtpd.SMTPServer`. - Override the `process_message` method to include logic for printing message details and handling "Important" in the subject. - Create an instance of the server and start the asyncore event loop to listen for incoming connections.
answer:import smtpd import asyncore import email from email import policy class CustomSMTPServer(smtpd.SMTPServer): def process_message(self, peer, mailfrom, rcpttos, data, **kwargs): print(f"Peer: {peer}") print(f"Mail from: {mailfrom}") print(f"Recipients: {rcpttos}") print(f"Data: {data.decode('utf-8') if isinstance(data, bytes) else data}") # Parse email data message = email.message_from_string(data.decode('utf-8') if isinstance(data, bytes) else data, policy=policy.SMTP) subject = message['subject'] # Check for 'Important' in subject if subject and "Important" in subject: return "250 Ok - Priority message received" return "250 Ok" # Initialize server def run_server(): print("Starting Custom SMTP Server on localhost:1025") server = CustomSMTPServer(('localhost', 1025), None, data_size_limit=10*1024*1024) try: asyncore.loop() except KeyboardInterrupt: print("Stopping server.") pass # Comment out the server run for unit testing purposes # if __name__ == "__main__": # run_server()
question:You are required to demonstrate your understanding and proficiency with seaborn's `clustermap` function. Below is the detailed task you need to accomplish. # Task 1. Load the `iris` dataset using seaborn. 2. Remove the `species` column from the dataset, but keep track of it for later use. 3. Create a hierarchical cluster map for the modified dataset: - **Figure Size:** 10 inches by 7 inches. - **Colormap:** Use the `'coolwarm'` colormap. - **Color Range:** Standardized within the columns (set `standard_scale` parameter to 1). - **Cluster Parameters:** - Use 'euclidean' as the metric for distance. - Use 'complete' as the method for clustering. - **Row Clustering:** Disable row clustering. - **Color bar:** Position the color bar on the left. - **Colored Labels:** Add colored labels for the `species` column to identify the observations. Use distinct colors for each species. # Constraints - The output figure should be correctly configured as described. - Ensure that the clustering method and metric are correctly applied. - The standardized color range must reflect the data's standardization within columns. - The colored labels should distinctly identify the species. # Expected Output Your function should output a seaborn cluster map adhering to the specifications mentioned above. # Implementation ```python import seaborn as sns import matplotlib.pyplot as plt def custom_clustermap(): # Load the 'iris' dataset from seaborn iris = sns.load_dataset("iris") # Remove the species column but keep track of it species = iris.pop("species") # Create a mapping of species to colors lut = dict(zip(species.unique(), "rgb")) row_colors = species.map(lut) # Generate the cluster map sns.clustermap( iris, figsize=(10, 7), cmap="coolwarm", standard_scale=1, metric="euclidean", method="complete", row_cluster=False, cbar_pos=(0, .2, .03, .4), row_colors=row_colors ) plt.show() # Call the function to display the clustermap custom_clustermap() ```
answer:import seaborn as sns import matplotlib.pyplot as plt def custom_clustermap(): # Load the 'iris' dataset from seaborn iris = sns.load_dataset("iris") # Remove the species column but keep track of it species = iris.pop("species") # Create a mapping of species to colors lut = dict(zip(species.unique(), "rgb")) row_colors = species.map(lut) # Generate the cluster map sns.clustermap( iris, figsize=(10, 7), cmap="coolwarm", standard_scale=1, metric="euclidean", method="complete", row_cluster=False, cbar_pos=(0, .2, .03, .4), row_colors=row_colors ) plt.show() # Call the function to display the clustermap custom_clustermap()
question:# Custom Descriptor Implementation **Objective:** Students will implement a custom descriptor in Python to manage the access and modification of an attribute in a class. The descriptor should utilize the getter and setter methods provided by Python descriptors. **Task:** You need to implement a class `ManagedAttribute` that uses the descriptor protocol (i.e., defining `__get__`, `__set__`, and `__delete__` methods). This descriptor should validate and manage the value of a specific attribute in a host class, `HostClass`. The `ManagedAttribute` class should: - Ensure that the attribute's value is always an integer. - Raise a `TypeError` if an attempt is made to set the attribute to a non-integer value. - Allow reading, setting, and deleting the attribute value. Implement the following: 1. The `ManagedAttribute` class, which includes: - A constructor that initializes the descriptor. - The `__get__`, `__set__`, and `__delete__` methods to manage the attribute. 2. A `HostClass` which uses `ManagedAttribute` as the descriptor for an attribute named `value`. **Input/Output:** ```python class ManagedAttribute: def __init__(self): # Your code here def __get__(self, instance, owner): # Your code here def __set__(self, instance, value): # Your code here def __delete__(self, instance): # Your code here class HostClass: value = ManagedAttribute() # Example Usage host = HostClass() host.value = 42 # No error print(host.value) # Output: 42 host.value = "abc" # Raises TypeError del host.value # Attribute is deleted print(host.value) # Raises AttributeError ``` **Constraints:** - The `ManagedAttribute` descriptor must specifically ensure that the values are managed correctly. - The `HostClass` should not allow any other type except integers for the `value` attribute. **Performance Requirement:** - The solution should handle the attribute access and modification efficiently using the descriptor protocol. **Guideline:** - Utilize the Python descriptor protocol methods: `__get__`, `__set__`, and `__delete__`. - Proper error handling should be implemented for setting values of incorrect type and accessing deleted attributes.
answer:class ManagedAttribute: def __init__(self): self._value = None def __get__(self, instance, owner): if self._value is None: raise AttributeError("Attribute is not set") return self._value def __set__(self, instance, value): if not isinstance(value, int): raise TypeError("Attribute value must be an integer") self._value = value def __delete__(self, instance): self._value = None class HostClass: value = ManagedAttribute()