Model Answer 3

This solution uses the os and os.path modules to perform recursive directory traversal and file filtering.

import os

def findandlisttextfiles(directorypath, outputfilename):

text_files = []

for root, , files in os.walk(directorypath):

for file in files:

if file.endswith(".txt"):

text_files.append(os.path.join(root, file))

try:

with open(output_filename, 'w') as outfile:

for filepath in textfiles:

outfile.write(file_path + "\n")

except Exception as e:

print(f"Error writing to file '{output_filename}': {e}")

if name == "main":

directory_path = input("Enter the directory path: ")

outputfile = "alltext_files.txt"

findandlisttextfiles(directorypath, outputfile)

Explanation:

• The code uses os.walk() to recursively traverse the directory specified by the user.
• For each directory it visits, it iterates through the files in that directory.
• It checks if the file name ends with ".txt".
• If it does, it constructs the full path to the file using os.path.join() and appends it to the text_files list.
• Finally, it writes each file path to the output file.
• Error handling is included for potential issues during file writing.

Model Answer 1

This solution demonstrates how to read a file, process the content (counting words), and write the results to another file. It includes error handling for file existence.

import re

def processfile(inputfilename, output_filename):

try:

with open(input_filename, 'r', encoding='utf-8') as infile:

text = infile.read()

except FileNotFoundError:

print(f"Error: File '{input_filename}' not found.")

return

words = re.findall(r'\b\w+\b', text.lower()) # Extract words, convert to lowercase

word_counts = {}

for word in words:

wordcounts[word] = wordcounts.get(word, 0) + 1

try:

with open(output_filename, 'w', encoding='utf-8') as outfile:

for word, count in word_counts.items():

outfile.write(f"{word}: {count}\n")

except Exception as e:

print(f"Error writing to file '{output_filename}': {e}")

if name == "main":

input_file = "data.txt"

outputfile = "wordcounts.txt"

processfile(inputfile, output_file)

Explanation:

• The code first attempts to open the input file. If the file is not found, it prints an error message and exits.
• It reads the entire content of the file into a string.
• The re.findall() function is used with a regular expression to extract all words from the text, converting them to lowercase for case-insensitive counting.
• A dictionary word_counts is used to store the count of each word.
• The code then iterates through the word_counts dictionary and writes each word and its count to the output file.
• Error handling is included for potential issues during file writing.

Model Answer 2

This solution uses the csv module to read and write CSV files, performing calculations on the data.

import csv

def calculateproductrevenue(inputfilename, outputfilename):

product_revenue = {}

try:

with open(input_filename, 'r', newline='') as infile:

reader = csv.reader(infile)

header = next(reader) # Skip the header row

for row in reader:

product_name, quantity, price = row

try:

quantity = int(quantity)

price = float(price)

except ValueError:

print(f"Warning: Invalid data in row: {row}. Skipping.")

continue

revenue = quantity * price

if productname in productrevenue:

productrevenue[productname] += revenue

else:

productrevenue[productname] = revenue

except FileNotFoundError:

print(f"Error: File '{input_filename}' not found.")

return

try:

with open(output_filename, 'w', newline='') as outfile:

writer = csv.writer(outfile)

writer.writerow(["Product Name", "Total Revenue"]) # Write header

for product, revenue in product_revenue.items():

writer.writerow([product, revenue])

except Exception as e:

print(f"Error writing to file '{output_filename}': {e}")

if name == "main":

inputfile = "salesdata.csv"

outputfile = "productrevenue.csv"

calculateproductrevenue(inputfile, outputfile)

Explanation:

• The code uses the csv module to read the input CSV file.
• It skips the header row.
• For each row, it extracts the product name, quantity, and price.
• It calculates the revenue for that sale.
• It aggregates the revenue for each product in the product_revenue dictionary.
• Finally, it writes the product names and their total revenue to the output CSV file.
• Error handling is included for file not found and invalid data in the input file.