Python Scripts for File Management, Data Processing, Automation, and More

File and Directory Management

Batch rename files in a directory based on a rule:

import os
for filename in os.listdir('.'):    
    if filename.endswith(".txt"):
        os.rename(filename, "new_" + filename)

Find large files exceeding a size threshold:

import os
for root, dirs, files in os.walk('.'):    
    for file in files:
        path = os.path.join(root, file)
        if os.path.getsize(path) > 1e6:  # larger than 1 MB
            print(path)

Copy only the folder structure without file contents:

import shutil
shutil.copytree('source_folder', 'destination_folder', copy_function=lambda src, dst: None)

Data Processing and Analysis

Merge multiple CSV files into one:

import pandas as pd
df_list = [pd.read_csv(f) for f in ['file1.csv', 'file2.csv']]
combined_df = pd.concat(df_list, ignore_index=True)
combined_df.to_csv('combined.csv', index=False)

Convert an Excel file to CSV:

import pandas as pd
excel_data = pd.read_excel('data.xlsx')
excel_data.to_csv('data.csv', index=False)

Remove duplicate lines from a text file:

with open('input.txt') as f_in, open('output.txt', 'w') as f_out:
    seen = set()
    for line in f_in:
        if line not in seen:
            f_out.write(line)
            seen.add(line)

Read and write JSON data:

import json
data = {'key': 'value'}
with open('data.json', 'w') as f:
    json.dump(data, f)
with open('data.json') as f:
    loaded_data = json.load(f)

Network Requests and API Interaction

Send a GET request and print the JSON response:

import requests
response = requests.get('https://api.example.com/data')
print(response.json())

Download a file from the internet and save it locally:

import requests
url = 'https://example.com/file.zip'
r = requests.get(url)
with open('file.zip', 'wb') as f:
    f.write(r.content)

Automation Tasks

Schedule a recurring job using APScheduler:

from apscheduler.schedulers.blocking import BlockingScheduler
sched = BlockingScheduler()
def job():
    print("Task executed!")
sched.add_job(job, 'interval', minutes=1)
sched.start()

Send an email automatically via SMTP:

import smtplib
from email.mime.text import MIMEText
msg = MIMEText('This is the body of the email.')
msg['Subject'] = 'Subject line'
msg['From'] = '[email protected]'
msg['To'] = '[email protected]'
with smtplib.SMTP('smtp.example.com') as server:
    server.login('user', 'pass')
    server.sendmail('[email protected]', ['[email protected]'], msg.as_string())

Document Processing

Create a simple Word document:

from docx import Document
doc = Document()
doc.add_paragraph('Hello World!')
doc.save('hello.docx')

Merge multiple PDF files into one:

from PyPDF2 import PdfFileMerger
merger = PdfFileMerger()
for pdf in ['file1.pdf', 'file2.pdf']:
    merger.append(pdf)
merger.write("merged.pdf")

Image Processing

Resize an image using Pillow:

from PIL import Image
img = Image.open('image.jpg')
resized_img = img.resize((800, 600))
resized_img.save('resized_image.jpg')

Text Analysis

Count word frequencies in a text file:

from collections import Counter
with open('text.txt') as f:
    words = f.read().split()
    word_counts = Counter(words)
    print(word_counts.most_common(10))

System Information

Get current CPU usage percentage:

import psutil
print(psutil.cpu_percent(interval=1))

Data Visualization

Plot a simple line chart with Matplotlib:

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [1, 4, 9, 16]
plt.plot(x, y)
plt.show()

Data Cleaning

Remove empty rows from a CSV file:

import pandas as pd
df = pd.read_csv('dirty_data.csv')
df.dropna(inplace=True)
df.to_csv('clean_data.csv', index=False)

Logging

Record log messages to a file using the logging module:

import logging
logging.basicConfig(filename='app.log', level=logging.INFO)
logging.info('This is an info message.')

Web Scraping

Fetch a webpage and extract all H1 titles with BeautifulSoup:

import requests
from bs4 import BeautifulSoup
url = 'http://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
titles = soup.find_all('h1')
for title in titles:
    print(title.text.strip())