everfern-ai/everfern/txt

# Read all content
with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    content = f.read()
    print(content)
# Read line by line
with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    for line in f:
        print(line.strip())
# Read into list
with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    lines = f.readlines()
    print(f"Total lines: {len(lines)}")

content = "Hello, World!\nLine 2\nLine 3"
with open(r'C:\path\to\output.txt', 'w', encoding='utf-8') as f:
    f.write(content)

with open(r'C:\path\to\file.txt', 'a', encoding='utf-8') as f:
    f.write("\nNew line appended")

lines = [
    "Line 1",
    "Line 2",
    "Line 3",
    "Line 4"
]
with open(r'C:\path\to\output.txt', 'w', encoding='utf-8') as f:
    f.writelines([line + '\n' for line in lines])

with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    content = f.read()
# Simple replace
new_content = content.replace('old_text', 'new_text')
# Using regular expressions
import re
new_content = re.sub(r'pattern', 'replacement', content)
with open(r'C:\path\to\output.txt', 'w', encoding='utf-8') as f:
    f.write(new_content)

with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    lines = f.readlines()
# Get lines 5-10
selected_lines = lines[4:10]  # Zero-indexed
# Get lines matching pattern
import re
pattern = re.compile(r'keyword')
matching_lines = [line for line in lines if pattern.search(line)]
with open(r'C:\path\to\output.txt', 'w', encoding='utf-8') as f:
    f.writelines(matching_lines)

with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    content = f.read()
    lines = content.splitlines()
    words = content.split()
    chars = len(content)
print(f"Lines: {len(lines)}")
print(f"Words: {len(words)}")
print(f"Characters: {chars}")

import re
with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    content = f.read()
# Extract emails
emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', content)
# Extract URLs
urls = re.findall(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', content)
# Extract numbers
numbers = re.findall(r'\d+', content)
print(f"Emails found: {emails}")
print(f"URLs found: {urls}")
print(f"Numbers found: {numbers}")

with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    lines = f.readlines()
# Parse pipe-delimited data
data = []
for line in lines:
    fields = [field.strip() for field in line.split('|')]
    data.append(fields)
print(data)

import os
files = [
    r'C:\path\to\file1.txt',
    r'C:\path\to\file2.txt',
    r'C:\path\to\file3.txt'
]
with open(r'C:\path\to\merged.txt', 'w', encoding='utf-8') as outfile:
    for file in files:
        with open(file, 'r', encoding='utf-8') as infile:
            outfile.write(infile.read())
            outfile.write('\n')  # Add separator

def split_file(file_path, lines_per_file=1000):
    with open(file_path, 'r', encoding='utf-8') as f:
        lines = f.readlines()
    for i in range(0, len(lines), lines_per_file):
        chunk = lines[i:i + lines_per_file]
        output_file = f'part_{i//lines_per_file}.txt'
        with open(output_file, 'w', encoding='utf-8') as f:
            f.writelines(chunk)
split_file(r'C:\path\to\large_file.txt')

from collections import Counter
with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    content = f.read().lower()
    words = content.split()
    filtered_words = [w for w in words if len(w) > 3]  # Skip short words
word_counts = Counter(filtered_words)
print(word_counts.most_common(20))  # Top 20 words

with open(r'C:\path\to\file.txt', 'r', encoding='utf-8') as f:
    lines = f.readlines()
unique_lines = list(set(lines))
with open(r'C:\path\to\output.txt', 'w', encoding='utf-8') as f:
    f.writelines(unique_lines)