from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
from datetime import datetime, timedelta

def generate_invoice(client_name, client_email, services, invoice_num=None):
    if invoice_num is None:
        invoice_num = f"INV-{datetime.now().strftime('%Y%m%d%H%M')}"

    total = sum(item['amount'] for item in services)
    due_date = datetime.now() + timedelta(days=30)

    filename = f"invoice_{invoice_num}.pdf"
    c = canvas.Canvas(filename, pagesize=letter)
    width, height = letter

    c.setFont("Helvetica-Bold", 24)
    c.drawString(50, height - 60, "INVOICE")
    c.setFont("Helvetica", 10)
    c.drawString(50, height - 80, f"Invoice #: {invoice_num}")
    c.drawString(50, height - 95, f"Date: {datetime.now().strftime('%B %d, %Y')}")
    c.drawString(50, height - 110, f"Due: {due_date.strftime('%B %d, %Y')}")

    c.setFont("Helvetica-Bold", 12)
    c.drawString(50, height - 150, "Bill To:")
    c.setFont("Helvetica", 11)
    c.drawString(50, height - 168, client_name)
    c.drawString(50, height - 183, client_email)

    y = height - 230
    c.setFont("Helvetica-Bold", 11)
    c.drawString(50, y, "Description")
    c.drawString(430, y, "Amount")
    c.line(50, y - 5, 550, y - 5)

    y -= 25
    c.setFont("Helvetica", 11)
    for item in services:
        c.drawString(50, y, item['description'])
        c.drawString(430, y, f"${item['amount']:,.2f}")
        y -= 20

    c.line(50, y - 5, 550, y - 5)
    y -= 25
    c.setFont("Helvetica-Bold", 12)
    c.drawString(350, y, "TOTAL:")
    c.drawString(430, y, f"${total:,.2f}")

    c.save()
    return filename

invoice = generate_invoice(
    "Acme Corp",
    "billing@acme.com",
    [
        {"description": "Web Development (40 hours @ $75/hr)", "amount": 3000},
        {"description": "Domain & Hosting Setup", "amount": 150},
    ]
)
print(f"Invoice generated: {invoice}")

import smtplib, sqlite3
from email.mime.text import MIMEText
from datetime import datetime

def check_and_remind_overdue(db_path="invoices.db"):
    conn = sqlite3.connect(db_path)
    cursor = conn.cursor()
    today = datetime.now().date()

    cursor.execute("""
        SELECT invoice_num, client_name, client_email, amount, due_date
        FROM invoices WHERE paid = 0 AND due_date < ?
        ORDER BY due_date ASC
    """, (str(today),))

    for inv_num, name, email, amount, due_date in cursor.fetchall():
        days_overdue = (today - datetime.strptime(due_date, "%Y-%m-%d").date()).days

        if days_overdue <= 7:
            subject = f"Gentle Reminder: Invoice {inv_num}"
            body = f"Hi {name}, just a reminder that Invoice {inv_num} for ${amount:,.2f} was due {due_date}. No worries, please process when you can!"
        elif days_overdue <= 30:
            subject = f"OVERDUE: Invoice {inv_num} — {days_overdue} days past due"
            body = f"Hi {name}, Invoice {inv_num} for ${amount:,.2f} is now {days_overdue} days overdue. Please arrange payment ASAP."
        else:
            subject = f"Final Notice: Invoice {inv_num}"
            body = f"Hi {name}, Invoice {inv_num} (${amount:,.2f}) is {days_overdue} days overdue. Immediate payment required."

        send_email(email, subject, body)  # your email sending function
        print(f"Reminded {name}: {inv_num} ({days_overdue}d overdue)")

    conn.close()

import pandas as pd

CATEGORIES = {
    "Software": ["aws", "github", "notion", "slack", "figma", "adobe"],
    "Marketing": ["facebook ads", "google ads", "mailchimp"],
    "Travel": ["uber", "lyft", "airbnb", "delta"],
    "Meals": ["restaurant", "doordash", "starbucks"],
    "Office": ["amazon", "staples", "best buy"],
}

def categorize(description):
    desc = description.lower()
    for cat, keywords in CATEGORIES.items():
        if any(kw in desc for kw in keywords):
            return cat
    return "Other"

def process_statement(csv_file):
    df = pd.read_csv(csv_file, names=["date", "description", "amount"])
    df["category"] = df["description"].apply(categorize)

    summary = df.groupby("category")["amount"].agg(["sum", "count"])
    for cat, row in summary.iterrows():
        print(f"{cat:15} ${abs(row['sum']):8,.2f} ({int(row['count'])} txns)")

    # Flag large unusual charges
    threshold = df["amount"].abs().mean() * 3
    unusual = df[df["amount"].abs() > threshold]
    if len(unusual):
        print("\n⚠️  Large transactions to review:")
        print(unusual[["date", "description", "amount"]].to_string())