""" ═══════════════════════════════════════════════════════════════════════════════ FIXNEZA PYTHON AUTOMATION TOOLKIT — STARTER PACK (FREE) ═══════════════════════════════════════════════════════════════════════════════ 3 ready-to-use Python automation scripts to get you started. The full toolkit (30 scripts + video tutorials) launches soon. Get the full version: https://fixneza.com ───────────────────────────────────────────────────────────────────────────── WHAT'S INCLUDED IN THIS STARTER: 1. Web Scraper — Extract product prices from any e-commerce site 2. Email Sender — Send personalized bulk emails (with rate-limiting) 3. CSV Cleaner — Auto-clean and deduplicate messy CSV files ───────────────────────────────────────────────────────────────────────────── REQUIREMENTS: Python 3.8+ Install dependencies: pip install requests beautifulsoup4 pandas ───────────────────────────────────────────────────────────────────────────── """ # ═══════════════════════════════════════════════════════════════════════════════ # SCRIPT 1: WEB SCRAPER — Extract prices from any e-commerce site # ═══════════════════════════════════════════════════════════════════════════════ def scrape_product_prices(url, css_selector): """ Scrape product prices from any e-commerce page. Args: url (str): The page URL to scrape css_selector (str): CSS selector for the price elements Example: '.price' or 'span.product-price' Returns: list: All price strings found on the page """ import requests from bs4 import BeautifulSoup headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) ' 'AppleWebKit/537.36 (KHTML, like Gecko) ' 'Chrome/120.0.0.0 Safari/537.36' } try: response = requests.get(url, headers=headers, timeout=10) response.raise_for_status() soup = BeautifulSoup(response.text, 'html.parser') prices = [el.get_text(strip=True) for el in soup.select(css_selector)] print(f"✓ Scraped {len(prices)} prices from {url}") return prices except requests.RequestException as e: print(f"✗ Error scraping {url}: {e}") return [] # Example usage: # prices = scrape_product_prices( # 'https://example-shop.com/products', # '.product-price' # ) # print(prices) # ═══════════════════════════════════════════════════════════════════════════════ # SCRIPT 2: EMAIL SENDER — Send personalized bulk emails (with rate-limiting) # ═══════════════════════════════════════════════════════════════════════════════ def send_bulk_emails(recipients, subject, body_template, smtp_config): """ Send personalized bulk emails with built-in rate-limiting to avoid spam flags. Args: recipients (list): List of dicts with 'email' and 'name' keys subject (str): Email subject (can use {name} placeholder) body_template (str): Email body (can use {name} placeholder) smtp_config (dict): {'host', 'port', 'user', 'password'} Example smtp_config for Gmail: { 'host': 'smtp.gmail.com', 'port': 587, 'user': 'you@gmail.com', 'password': 'your-app-password' } """ import smtplib import time from email.mime.text import MIMEText from email.mime.multipart import MIMEMultipart sent = 0 failed = 0 try: with smtplib.SMTP(smtp_config['host'], smtp_config['port']) as server: server.starttls() server.login(smtp_config['user'], smtp_config['password']) for recipient in recipients: try: msg = MIMEMultipart() msg['From'] = smtp_config['user'] msg['To'] = recipient['email'] msg['Subject'] = subject.format(name=recipient.get('name', '')) body = body_template.format(name=recipient.get('name', '')) msg.attach(MIMEText(body, 'plain')) server.send_message(msg) sent += 1 print(f"✓ Sent to {recipient['email']}") # Rate-limit: 1 email per 2 seconds (avoids spam flags) time.sleep(2) except Exception as e: failed += 1 print(f"✗ Failed to send to {recipient['email']}: {e}") except Exception as e: print(f"✗ SMTP connection error: {e}") print(f"\n📊 Summary: {sent} sent, {failed} failed") return {'sent': sent, 'failed': failed} # Example usage: # recipients = [ # {'email': 'alice@example.com', 'name': 'Alice'}, # {'email': 'bob@example.com', 'name': 'Bob'}, # ] # # send_bulk_emails( # recipients=recipients, # subject="Hi {name}, quick update!", # body_template="Hello {name},\n\nJust wanted to share...", # smtp_config={ # 'host': 'smtp.gmail.com', # 'port': 587, # 'user': 'your@email.com', # 'password': 'your-app-password' # } # ) # ═══════════════════════════════════════════════════════════════════════════════ # SCRIPT 3: CSV CLEANER — Auto-clean and deduplicate messy CSV files # ═══════════════════════════════════════════════════════════════════════════════ def clean_csv(input_file, output_file, dedupe_column=None): """ Clean a messy CSV file: - Strips whitespace from all string fields - Removes empty rows - Removes duplicate rows (optionally based on a specific column) - Standardizes column names (lowercase, no spaces) Args: input_file (str): Path to input CSV output_file (str): Path to save cleaned CSV dedupe_column (str, optional): Column to dedupe on (e.g., 'email') If None, dedupes on all columns Returns: dict: Stats about the cleaning operation """ import pandas as pd try: # Load CSV df = pd.read_csv(input_file) original_rows = len(df) # 1. Standardize column names df.columns = [col.strip().lower().replace(' ', '_') for col in df.columns] # 2. Strip whitespace from string fields for col in df.select_dtypes(include='object').columns: df[col] = df[col].astype(str).str.strip() # 3. Remove empty rows df = df.dropna(how='all') # 4. Deduplicate if dedupe_column and dedupe_column in df.columns: df = df.drop_duplicates(subset=[dedupe_column], keep='first') else: df = df.drop_duplicates(keep='first') # 5. Save cleaned file df.to_csv(output_file, index=False) cleaned_rows = len(df) removed = original_rows - cleaned_rows print(f"✓ Cleaned {input_file}") print(f" Original rows: {original_rows}") print(f" Cleaned rows: {cleaned_rows}") print(f" Removed: {removed} ({(removed/original_rows*100):.1f}%)") print(f" Saved to: {output_file}") return { 'original': original_rows, 'cleaned': cleaned_rows, 'removed': removed } except Exception as e: print(f"✗ Error cleaning {input_file}: {e}") return None # Example usage: # clean_csv('messy_contacts.csv', 'clean_contacts.csv', dedupe_column='email') # ═══════════════════════════════════════════════════════════════════════════════ # WANT MORE? GET THE FULL TOOLKIT # ═══════════════════════════════════════════════════════════════════════════════ # # This is just the starter pack. The full Python Automation Toolkit includes: # # ✓ 30 production-ready scripts (PDF generation, image batch processing, # SEO scrapers, social media schedulers, file organizers, and more) # ✓ Video tutorials walking through each script # ✓ Lifetime updates as we add new automations # ✓ Discord community for help and ideas # # Coming soon at: https://fixneza.com # # Be the first to know — drop your email at fixneza.com to get early access # and an exclusive launch discount. # # ═══════════════════════════════════════════════════════════════════════════════ if __name__ == '__main__': print(""" ╔═══════════════════════════════════════════════════════════════╗ ║ ║ ║ FIXNEZA PYTHON AUTOMATION TOOLKIT — STARTER PACK ║ ║ ║ ║ 3 free scripts to get you started. ║ ║ Full version (30 scripts) launches soon. ║ ║ ║ ║ Get notified: https://fixneza.com ║ ║ ║ ╚═══════════════════════════════════════════════════════════════╝ """) print("👉 Open this file in your editor to see the 3 scripts.") print("👉 Read the comments at the top for setup instructions.") print("👉 Each script has example usage at the bottom of its section.")