7 Python Scripts to Automate Your Daily Tasks in 2026

# python# automation# productivity# beginners
7 Python Scripts to Automate Your Daily Tasks in 2026Codes Me

Automating repetitive tasks is one of the highest-ROI things you can do as a developer in 2026. Here...

Automating repetitive tasks is one of the highest-ROI things you can do as a developer in 2026. Here are 7 ready-to-use Python scripts that will save you hours every week.

1. Bulk Rename Files in One Second 

from pathlib import Path

folder = Path("./my_files")
for i, file in enumerate(folder.iterdir()):
    new_name = f"document_{i+1}{file.suffix}"
    file.rename(folder / new_name)
    print(f"Renamed: {new_name}")
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Use cases: client photos, CSV exports, monthly reports.

2. Send Automated Emails with Attachments 

import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.base import MIMEBase
from email.mime.text import MIMEText
from email import encoders

def send_email(to, subject, body, attachment=None):
    msg = MIMEMultipart()
    msg["From"] = "you@gmail.com"
    msg["To"] = to
    msg["Subject"] = subject
    msg.attach(MIMEText(body, "plain"))

    if attachment:
        with open(attachment, "rb") as f:
            part = MIMEBase("application", "octet-stream")
            part.set_payload(f.read())
            encoders.encode_base64(part)
            part.add_header("Content-Disposition", f"attachment; filename={attachment}")
            msg.attach(part)

    with smtplib.SMTP_SSL("smtp.gmail.com", 465) as server:
        server.login("you@gmail.com", "your_app_password")
        server.send_message(msg)
        print(f"Email sent to {to}")

send_email("client@example.com", "Your Weekly Report", "Hi, please find the report attached.", "report.pdf")
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3. Scrape E-Commerce Prices 

import requests
from bs4 import BeautifulSoup

def scrape_price(url):
    headers = {"User-Agent": "Mozilla/5.0"}
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.text, "html.parser")
    title = soup.find("h1").text.strip()
    price = soup.find(class_="price").text.strip()
    print(f"Product : {title}")
    print(f"Price   : {price}")
    return {"title": title, "price": price}
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Use cases: competitive monitoring, price alerts.

4. Auto-Generate a PDF Report 

from fpdf import FPDF
from datetime import datetime

def generate_report(data: list[dict], filename="report.pdf"):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", "B", 16)
    pdf.cell(0, 10, f"Report — {datetime.now().strftime('%Y-%m-%d')}", ln=True)
    pdf.set_font("Arial", size=12)
    for row in data:
        pdf.cell(0, 8, f"- {row['label']}: {row['value']}", ln=True)
    pdf.output(filename)

generate_report([
    {"label": "Revenue", "value": "$12,340"},
    {"label": "New clients", "value": "47"},
])
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5. Monitor a Website and Get Alerts 

import requests, time

def monitor(url, interval=60):
    while True:
        try:
            r = requests.get(url, timeout=10)
            status = "Online" if r.status_code == 200 else f"Error {r.status_code}"
        except requests.ConnectionError:
            status = "Offline"
        print(f"[{time.strftime('%H:%M:%S')}] {url} — {status}")
        time.sleep(interval)

monitor("https://codes-me.com")
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6. Clean and Deduplicate a CSV File 

import pandas as pd

df = pd.read_csv("contacts.csv")
before = len(df)
df = df.drop_duplicates(subset=["email"]).dropna(subset=["email", "name"])
df["email"] = df["email"].str.lower().str.strip()
df.to_csv("contacts_clean.csv", index=False)
print(f"{before - len(df)} rows removed. {len(df)} contacts kept.")
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7. Batch Download Files from the Web 

import requests
from pathlib import Path

def download_files(urls: list[str], folder="./downloads"):
    Path(folder).mkdir(exist_ok=True)
    for url in urls:
        name = url.split("/")[-1]
        r = requests.get(url, stream=True)
        with open(f"{folder}/{name}", "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                f.write(chunk)
        print(f"Downloaded: {name}")
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Conclusion

These 7 scripts cover the most common automation use cases. With just a few lines of Python, you can eliminate hours of manual work every week.

Need something more advanced — scraping pipelines, API integrations, real-time dashboards? Check out codes-me.com — we build custom automation tools tailored to your needs.

Which script would save you the most time? Drop it in the comments!