c2bb48db19
ROOT CAUSE: - Overview API prioritized database data (only Porkbun prices) - Compare API prioritized static data (5+ registrars) - This caused price mismatches between Overview table and Detail page SOLUTION: - Changed Overview API to prioritize static data for TLDs with rich multi-registrar pricing (like Compare API does) - Database data now used only for TLDs NOT in static data - This ensures all APIs return identical prices for same TLDs VERIFICATION: - .com: Overview=$10.75, Compare=$10.75 ✓ - .io: Overview=$32.33, Compare=$32.33 ✓ - .ai: Overview=$71.63, Compare=$71.63 ✓ - .xyz: Overview=$6.86, Compare=$6.86 ✓ DATA FLOW (now consistent): 1. Static TLDs (18): Use rich multi-registrar data 2. DB-only TLDs (869): Use Porkbun scraped data 3. Total: 887 TLDs with consistent pricing
741 lines
27 KiB
Python
741 lines
27 KiB
Python
"""TLD Price API endpoints with real market data from database + static fallback."""
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from datetime import datetime, timedelta
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from typing import Optional, List
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from fastapi import APIRouter, Query, HTTPException
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from pydantic import BaseModel
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from sqlalchemy import select, func, desc
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from app.api.deps import Database
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from app.models.tld_price import TLDPrice, TLDInfo
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router = APIRouter()
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async def get_db_prices(db, tld: str = None) -> dict:
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"""Get latest prices from database."""
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# Subquery to get latest record per TLD/registrar
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subq = (
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select(
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TLDPrice.tld,
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TLDPrice.registrar,
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func.max(TLDPrice.recorded_at).label("max_date")
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)
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.group_by(TLDPrice.tld, TLDPrice.registrar)
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.subquery()
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)
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query = (
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select(TLDPrice)
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.join(
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subq,
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(TLDPrice.tld == subq.c.tld) &
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(TLDPrice.registrar == subq.c.registrar) &
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(TLDPrice.recorded_at == subq.c.max_date)
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)
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)
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if tld:
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query = query.where(TLDPrice.tld == tld.lower().lstrip("."))
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result = await db.execute(query)
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prices = result.scalars().all()
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# Group by TLD
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tld_prices = {}
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for p in prices:
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if p.tld not in tld_prices:
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tld_prices[p.tld] = {
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"registrars": {},
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"prices": []
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}
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tld_prices[p.tld]["registrars"][p.registrar] = {
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"register": p.registration_price,
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"renew": p.renewal_price or p.registration_price,
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"transfer": p.transfer_price or p.registration_price,
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}
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tld_prices[p.tld]["prices"].append(p.registration_price)
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return tld_prices
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async def get_db_price_count(db) -> int:
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"""Get count of TLDs in database."""
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result = await db.execute(select(func.count(func.distinct(TLDPrice.tld))))
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return result.scalar() or 0
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# Real TLD price data based on current market research (December 2024)
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# Prices in USD, sourced from major registrars: Namecheap, Cloudflare, Porkbun, Google Domains
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TLD_DATA = {
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# Generic TLDs
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"com": {
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"type": "generic",
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"description": "Commercial - Most popular TLD worldwide",
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"registry": "Verisign",
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"introduced": 1985,
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"registrars": {
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"Cloudflare": {"register": 10.44, "renew": 10.44, "transfer": 10.44},
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"Namecheap": {"register": 9.58, "renew": 14.58, "transfer": 9.48},
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"Porkbun": {"register": 9.73, "renew": 10.91, "transfer": 9.73},
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"Google Domains": {"register": 12.00, "renew": 12.00, "transfer": 12.00},
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"GoDaddy": {"register": 11.99, "renew": 22.99, "transfer": 11.99},
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},
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"trend": "stable",
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"trend_reason": "Stable registry pricing, slight increase in 2024",
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},
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"net": {
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"type": "generic",
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"description": "Network - Popular for tech and infrastructure",
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"registry": "Verisign",
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"introduced": 1985,
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"registrars": {
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"Cloudflare": {"register": 11.94, "renew": 11.94, "transfer": 11.94},
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"Namecheap": {"register": 12.88, "renew": 16.88, "transfer": 12.78},
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"Porkbun": {"register": 11.52, "renew": 12.77, "transfer": 11.52},
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"Google Domains": {"register": 15.00, "renew": 15.00, "transfer": 15.00},
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},
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"trend": "stable",
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"trend_reason": "Mature market, predictable pricing",
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},
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"org": {
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"type": "generic",
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"description": "Organization - Non-profits and communities",
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"registry": "Public Interest Registry",
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"introduced": 1985,
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"registrars": {
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"Cloudflare": {"register": 10.11, "renew": 10.11, "transfer": 10.11},
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"Namecheap": {"register": 10.98, "renew": 15.98, "transfer": 10.88},
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"Porkbun": {"register": 10.19, "renew": 11.44, "transfer": 10.19},
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"Google Domains": {"register": 12.00, "renew": 12.00, "transfer": 12.00},
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},
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"trend": "stable",
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"trend_reason": "Non-profit pricing commitment",
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},
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"io": {
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"type": "ccTLD",
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"description": "British Indian Ocean Territory - Popular for tech startups",
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"registry": "Internet Computer Bureau",
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"introduced": 1997,
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"registrars": {
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"Cloudflare": {"register": 33.98, "renew": 33.98, "transfer": 33.98},
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"Namecheap": {"register": 32.88, "renew": 38.88, "transfer": 32.78},
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"Porkbun": {"register": 32.47, "renew": 36.47, "transfer": 32.47},
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"Google Domains": {"register": 30.00, "renew": 30.00, "transfer": 30.00},
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},
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"trend": "up",
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"trend_reason": "High demand from tech/startup sector, +8% in 2024",
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},
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"co": {
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"type": "ccTLD",
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"description": "Colombia - Popular as 'Company' alternative",
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"registry": ".CO Internet S.A.S",
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"introduced": 1991,
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"registrars": {
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"Cloudflare": {"register": 11.02, "renew": 11.02, "transfer": 11.02},
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"Namecheap": {"register": 11.98, "renew": 29.98, "transfer": 11.88},
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"Porkbun": {"register": 10.77, "renew": 27.03, "transfer": 10.77},
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},
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"trend": "stable",
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"trend_reason": "Steady adoption as .com alternative",
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},
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"ai": {
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"type": "ccTLD",
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"description": "Anguilla - Extremely popular for AI companies",
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"registry": "Government of Anguilla",
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"introduced": 1995,
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"registrars": {
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"Namecheap": {"register": 74.98, "renew": 74.98, "transfer": 74.88},
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"Porkbun": {"register": 59.93, "renew": 79.93, "transfer": 59.93},
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"GoDaddy": {"register": 79.99, "renew": 99.99, "transfer": 79.99},
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},
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"trend": "up",
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"trend_reason": "AI boom driving massive demand, +35% since 2023",
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},
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"dev": {
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"type": "generic",
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"description": "Developer - For software developers",
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"registry": "Google",
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"introduced": 2019,
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"registrars": {
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"Cloudflare": {"register": 11.94, "renew": 11.94, "transfer": 11.94},
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"Namecheap": {"register": 14.98, "renew": 17.98, "transfer": 14.88},
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"Porkbun": {"register": 13.33, "renew": 15.65, "transfer": 13.33},
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"Google Domains": {"register": 14.00, "renew": 14.00, "transfer": 14.00},
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},
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"trend": "stable",
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"trend_reason": "Growing developer adoption",
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},
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"app": {
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"type": "generic",
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"description": "Application - For apps and software",
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"registry": "Google",
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"introduced": 2018,
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"registrars": {
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"Cloudflare": {"register": 14.94, "renew": 14.94, "transfer": 14.94},
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"Namecheap": {"register": 16.98, "renew": 19.98, "transfer": 16.88},
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"Porkbun": {"register": 15.45, "renew": 17.77, "transfer": 15.45},
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"Google Domains": {"register": 16.00, "renew": 16.00, "transfer": 16.00},
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},
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"trend": "stable",
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"trend_reason": "Steady growth in app ecosystem",
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},
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"xyz": {
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"type": "generic",
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"description": "XYZ - Generation XYZ, affordable option",
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"registry": "XYZ.COM LLC",
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"introduced": 2014,
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"registrars": {
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"Cloudflare": {"register": 10.44, "renew": 10.44, "transfer": 10.44},
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"Namecheap": {"register": 1.00, "renew": 13.98, "transfer": 1.00}, # Promo
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"Porkbun": {"register": 9.15, "renew": 10.40, "transfer": 9.15},
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},
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"trend": "down",
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"trend_reason": "Heavy promotional pricing competition",
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},
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"tech": {
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"type": "generic",
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"description": "Technology - For tech companies",
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"registry": "Radix",
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"introduced": 2015,
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"registrars": {
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"Namecheap": {"register": 5.98, "renew": 49.98, "transfer": 5.88},
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"Porkbun": {"register": 4.79, "renew": 44.52, "transfer": 4.79},
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"GoDaddy": {"register": 4.99, "renew": 54.99, "transfer": 4.99},
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},
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"trend": "stable",
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"trend_reason": "Low intro pricing, high renewals",
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},
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"online": {
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"type": "generic",
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"description": "Online - For online presence",
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"registry": "Radix",
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"introduced": 2015,
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"registrars": {
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"Namecheap": {"register": 2.98, "renew": 39.98, "transfer": 2.88},
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"Porkbun": {"register": 2.59, "renew": 34.22, "transfer": 2.59},
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},
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"trend": "stable",
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"trend_reason": "Budget-friendly option",
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},
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"store": {
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"type": "generic",
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"description": "Store - For e-commerce",
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"registry": "Radix",
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"introduced": 2016,
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"registrars": {
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"Namecheap": {"register": 3.88, "renew": 56.88, "transfer": 3.78},
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"Porkbun": {"register": 3.28, "renew": 48.95, "transfer": 3.28},
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},
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"trend": "stable",
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"trend_reason": "E-commerce growth sector",
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},
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"me": {
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"type": "ccTLD",
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"description": "Montenegro - Popular for personal branding",
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"registry": "doMEn",
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"introduced": 2007,
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"registrars": {
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"Cloudflare": {"register": 14.94, "renew": 14.94, "transfer": 14.94},
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"Namecheap": {"register": 5.98, "renew": 19.98, "transfer": 5.88},
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"Porkbun": {"register": 5.15, "renew": 17.45, "transfer": 5.15},
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},
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"trend": "stable",
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"trend_reason": "Personal branding market",
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},
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"info": {
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"type": "generic",
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"description": "Information - For informational sites",
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"registry": "Afilias",
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"introduced": 2001,
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"registrars": {
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"Cloudflare": {"register": 11.44, "renew": 11.44, "transfer": 11.44},
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"Namecheap": {"register": 4.98, "renew": 22.98, "transfer": 4.88},
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"Porkbun": {"register": 4.24, "renew": 19.45, "transfer": 4.24},
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},
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"trend": "down",
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"trend_reason": "Declining popularity vs newer TLDs",
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},
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"biz": {
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"type": "generic",
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"description": "Business - Alternative to .com",
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"registry": "GoDaddy Registry",
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"introduced": 2001,
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"registrars": {
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"Cloudflare": {"register": 13.44, "renew": 13.44, "transfer": 13.44},
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"Namecheap": {"register": 14.98, "renew": 20.98, "transfer": 14.88},
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"Porkbun": {"register": 13.96, "renew": 18.45, "transfer": 13.96},
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},
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"trend": "stable",
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"trend_reason": "Mature but declining market",
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},
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"ch": {
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"type": "ccTLD",
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"description": "Switzerland - Swiss domains",
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"registry": "SWITCH",
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"introduced": 1987,
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"registrars": {
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"Infomaniak": {"register": 9.80, "renew": 9.80, "transfer": 9.80},
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"Hostpoint": {"register": 11.90, "renew": 11.90, "transfer": 0.00},
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"Namecheap": {"register": 12.98, "renew": 12.98, "transfer": 12.88},
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},
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"trend": "stable",
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"trend_reason": "Stable Swiss market",
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},
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"de": {
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"type": "ccTLD",
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"description": "Germany - German domains",
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"registry": "DENIC",
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"introduced": 1986,
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"registrars": {
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"United Domains": {"register": 9.90, "renew": 9.90, "transfer": 9.90},
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"IONOS": {"register": 0.99, "renew": 12.00, "transfer": 0.00},
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"Namecheap": {"register": 9.98, "renew": 11.98, "transfer": 9.88},
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},
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"trend": "stable",
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"trend_reason": "Largest ccTLD in Europe",
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},
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"uk": {
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"type": "ccTLD",
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"description": "United Kingdom - British domains",
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"registry": "Nominet",
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"introduced": 1985,
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"registrars": {
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"Namecheap": {"register": 8.88, "renew": 10.98, "transfer": 8.78},
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"Porkbun": {"register": 8.45, "renew": 9.73, "transfer": 8.45},
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"123-reg": {"register": 9.99, "renew": 11.99, "transfer": 9.99},
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},
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"trend": "stable",
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"trend_reason": "Strong local market",
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},
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}
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def get_avg_price(tld_data: dict) -> float:
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"""Calculate average registration price across registrars."""
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prices = [r["register"] for r in tld_data["registrars"].values()]
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return round(sum(prices) / len(prices), 2)
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def get_min_price(tld_data: dict) -> float:
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"""Get minimum registration price."""
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return min(r["register"] for r in tld_data["registrars"].values())
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def get_max_price(tld_data: dict) -> float:
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"""Get maximum registration price."""
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return max(r["register"] for r in tld_data["registrars"].values())
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# Top TLDs by popularity (based on actual domain registration volumes)
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TOP_TLDS_BY_POPULARITY = [
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"com", "net", "org", "de", "uk", "cn", "ru", "nl", "br", "au",
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"io", "co", "ai", "app", "dev", "xyz", "online", "site", "tech", "store",
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"info", "biz", "me", "tv", "cc", "eu", "fr", "it", "es", "pl",
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"ch", "at", "be", "se", "no", "dk", "fi", "ie", "nz", "in",
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]
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@router.get("/overview")
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async def get_tld_overview(
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db: Database,
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limit: int = Query(25, ge=1, le=100),
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offset: int = Query(0, ge=0),
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sort_by: str = Query("popularity", enum=["popularity", "price_asc", "price_desc", "name"]),
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search: str = Query(None, description="Search TLDs by name"),
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source: str = Query("auto", enum=["auto", "db", "static"]),
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):
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"""Get overview of TLDs with current pricing, pagination, and search.
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Data source priority:
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- For TLDs with rich static data (multiple registrars): Use static data for consistency
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- For TLDs only in database: Use database data
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- This ensures Overview and Compare/Detail pages show identical prices
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Args:
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limit: Number of results per page (default 25)
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offset: Skip N results for pagination
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search: Filter TLDs by name (e.g., "com", "io")
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sort_by: Sort order - popularity (default), price_asc, price_desc, name
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source: Data source - "auto" (best available), "db" (only DB), "static" (only static)
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"""
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tld_list = []
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tld_seen = set()
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data_source = "combined"
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# FIRST: Add all static data TLDs (these have rich multi-registrar data)
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# This ensures consistency with /compare endpoint which also uses static data first
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if source in ["auto", "static"]:
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for tld, data in TLD_DATA.items():
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tld_list.append({
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"tld": tld,
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"type": data["type"],
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"description": data["description"],
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"avg_registration_price": get_avg_price(data),
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"min_registration_price": get_min_price(data),
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"max_registration_price": get_max_price(data),
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"registrar_count": len(data["registrars"]),
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"trend": data["trend"],
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"popularity_rank": TOP_TLDS_BY_POPULARITY.index(tld) if tld in TOP_TLDS_BY_POPULARITY else 999,
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})
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tld_seen.add(tld)
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# SECOND: Add TLDs from database that are NOT in static data
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# This adds the 800+ TLDs scraped from Porkbun
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if source in ["auto", "db"]:
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db_count = await get_db_price_count(db)
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if db_count > 0:
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db_prices = await get_db_prices(db)
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for tld, data in db_prices.items():
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if tld not in tld_seen: # Only add if not already from static
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prices = data["prices"]
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tld_list.append({
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"tld": tld,
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"type": guess_tld_type(tld),
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"description": f".{tld} domain extension",
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"avg_registration_price": round(sum(prices) / len(prices), 2),
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"min_registration_price": min(prices),
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"max_registration_price": max(prices),
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"registrar_count": len(data["registrars"]),
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"trend": "stable",
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"popularity_rank": TOP_TLDS_BY_POPULARITY.index(tld) if tld in TOP_TLDS_BY_POPULARITY else 999,
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})
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tld_seen.add(tld)
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# Determine source label
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if source == "static":
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data_source = "static"
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elif source == "db":
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data_source = "database"
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else:
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data_source = "combined"
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# Apply search filter
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if search:
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search_lower = search.lower().lstrip(".")
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tld_list = [t for t in tld_list if search_lower in t["tld"].lower()]
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# Store total before pagination
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total = len(tld_list)
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# Sort
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if sort_by == "popularity":
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tld_list.sort(key=lambda x: (x["popularity_rank"], x["tld"]))
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elif sort_by == "price_asc":
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tld_list.sort(key=lambda x: x["avg_registration_price"])
|
|
elif sort_by == "price_desc":
|
|
tld_list.sort(key=lambda x: x["avg_registration_price"], reverse=True)
|
|
elif sort_by == "name":
|
|
tld_list.sort(key=lambda x: x["tld"])
|
|
|
|
# Apply pagination
|
|
paginated = tld_list[offset:offset + limit]
|
|
|
|
return {
|
|
"tlds": paginated,
|
|
"total": total,
|
|
"limit": limit,
|
|
"offset": offset,
|
|
"has_more": offset + limit < total,
|
|
"source": data_source,
|
|
}
|
|
|
|
|
|
def guess_tld_type(tld: str) -> str:
|
|
"""Guess TLD type based on pattern."""
|
|
if len(tld) == 2:
|
|
return "ccTLD"
|
|
if tld in {"com", "net", "org", "info", "biz"}:
|
|
return "generic"
|
|
return "gTLD"
|
|
|
|
|
|
@router.get("/trending")
|
|
async def get_trending_tlds(db: Database):
|
|
"""Get trending TLDs based on price changes."""
|
|
trending = []
|
|
|
|
for tld, data in TLD_DATA.items():
|
|
if data["trend"] in ["up", "down"]:
|
|
# Calculate approximate price change
|
|
price_change = 8.5 if data["trend"] == "up" else -5.2
|
|
if tld == "ai":
|
|
price_change = 35.0 # AI domains have seen massive increase
|
|
elif tld == "io":
|
|
price_change = 8.0
|
|
elif tld == "xyz":
|
|
price_change = -12.0
|
|
elif tld == "info":
|
|
price_change = -8.0
|
|
|
|
trending.append({
|
|
"tld": tld,
|
|
"reason": data["trend_reason"],
|
|
"price_change": price_change,
|
|
"current_price": get_avg_price(data),
|
|
})
|
|
|
|
# Sort by price change magnitude
|
|
trending.sort(key=lambda x: abs(x["price_change"]), reverse=True)
|
|
|
|
return {"trending": trending[:6]}
|
|
|
|
|
|
@router.get("/{tld}/history")
|
|
async def get_tld_price_history(
|
|
tld: str,
|
|
db: Database,
|
|
days: int = Query(90, ge=30, le=365),
|
|
):
|
|
"""Get price history for a specific TLD.
|
|
|
|
Returns real historical data from database if available,
|
|
otherwise generates simulated data based on current price.
|
|
"""
|
|
import math
|
|
|
|
tld_clean = tld.lower().lstrip(".")
|
|
|
|
# Get current price from database
|
|
db_prices = await get_db_prices(db, tld_clean)
|
|
current_price = 0
|
|
|
|
if db_prices and tld_clean in db_prices:
|
|
prices = db_prices[tld_clean]["prices"]
|
|
current_price = round(sum(prices) / len(prices), 2) if prices else 0
|
|
|
|
# Get static data for metadata and trend info
|
|
static_data = TLD_DATA.get(tld_clean, {})
|
|
|
|
# Determine trend and current price
|
|
if not current_price and static_data:
|
|
current_price = get_avg_price(static_data)
|
|
|
|
if not current_price:
|
|
raise HTTPException(status_code=404, detail=f"TLD '.{tld_clean}' not found")
|
|
|
|
# Get trend info
|
|
trend = static_data.get("trend", "stable")
|
|
trend_reason = static_data.get("trend_reason", "Price tracking available")
|
|
|
|
# Generate historical data (simulated for now, real when we have more scrapes)
|
|
history = []
|
|
current_date = datetime.utcnow()
|
|
|
|
# Calculate trend factor based on known trends
|
|
trend_factor = 1.0
|
|
if trend == "up":
|
|
trend_factor = 0.92 # Prices were ~8% lower
|
|
elif trend == "down":
|
|
trend_factor = 1.05 # Prices were ~5% higher
|
|
|
|
# Generate weekly data points
|
|
for i in range(days, -1, -7):
|
|
date = current_date - timedelta(days=i)
|
|
progress = 1 - (i / days)
|
|
|
|
if trend == "up":
|
|
price = current_price * (trend_factor + (1 - trend_factor) * progress)
|
|
elif trend == "down":
|
|
price = current_price * (trend_factor - (trend_factor - 1) * progress)
|
|
else:
|
|
# Add small fluctuation for stable prices
|
|
fluctuation = math.sin(i * 0.1) * 0.02
|
|
price = current_price * (1 + fluctuation)
|
|
|
|
history.append({
|
|
"date": date.strftime("%Y-%m-%d"),
|
|
"price": round(price, 2),
|
|
})
|
|
|
|
# Calculate price changes
|
|
price_7d_ago = history[-2]["price"] if len(history) >= 2 else current_price
|
|
price_30d_ago = history[-5]["price"] if len(history) >= 5 else current_price
|
|
price_90d_ago = history[0]["price"] if history else current_price
|
|
|
|
return {
|
|
"tld": tld_clean,
|
|
"type": static_data.get("type", guess_tld_type(tld_clean)),
|
|
"description": static_data.get("description", f".{tld_clean} domain extension"),
|
|
"registry": static_data.get("registry", "Unknown"),
|
|
"current_price": current_price,
|
|
"price_change_7d": round((current_price - price_7d_ago) / price_7d_ago * 100, 2) if price_7d_ago else 0,
|
|
"price_change_30d": round((current_price - price_30d_ago) / price_30d_ago * 100, 2) if price_30d_ago else 0,
|
|
"price_change_90d": round((current_price - price_90d_ago) / price_90d_ago * 100, 2) if price_90d_ago else 0,
|
|
"trend": trend,
|
|
"trend_reason": trend_reason,
|
|
"history": history,
|
|
"source": "simulated" if not static_data else "static",
|
|
}
|
|
|
|
|
|
def calculate_trend(history: list) -> str:
|
|
"""Calculate trend from price history."""
|
|
if len(history) < 2:
|
|
return "stable"
|
|
|
|
first_price = history[0]["price"]
|
|
last_price = history[-1]["price"]
|
|
|
|
if first_price == 0:
|
|
return "stable"
|
|
|
|
change_percent = (last_price - first_price) / first_price * 100
|
|
|
|
if change_percent > 5:
|
|
return "up"
|
|
elif change_percent < -5:
|
|
return "down"
|
|
return "stable"
|
|
|
|
|
|
@router.get("/{tld}/compare")
|
|
async def compare_tld_prices(
|
|
tld: str,
|
|
db: Database,
|
|
):
|
|
"""Compare prices across different registrars for a TLD."""
|
|
tld_clean = tld.lower().lstrip(".")
|
|
|
|
# Try static data first
|
|
if tld_clean in TLD_DATA:
|
|
data = TLD_DATA[tld_clean]
|
|
|
|
registrars = []
|
|
for name, prices in data["registrars"].items():
|
|
registrars.append({
|
|
"name": name,
|
|
"registration_price": prices["register"],
|
|
"renewal_price": prices["renew"],
|
|
"transfer_price": prices["transfer"],
|
|
})
|
|
|
|
registrars.sort(key=lambda x: x["registration_price"])
|
|
|
|
return {
|
|
"tld": tld_clean,
|
|
"type": data["type"],
|
|
"description": data["description"],
|
|
"registry": data.get("registry", "Unknown"),
|
|
"introduced": data.get("introduced"),
|
|
"registrars": registrars,
|
|
"cheapest_registrar": registrars[0]["name"],
|
|
"cheapest_price": registrars[0]["registration_price"],
|
|
"price_range": {
|
|
"min": get_min_price(data),
|
|
"max": get_max_price(data),
|
|
"avg": get_avg_price(data),
|
|
},
|
|
}
|
|
|
|
# Fall back to database
|
|
db_prices = await get_db_prices(db, tld_clean)
|
|
if not db_prices:
|
|
raise HTTPException(status_code=404, detail=f"TLD '.{tld_clean}' not found")
|
|
|
|
tld_data = db_prices[tld_clean]
|
|
registrars = [
|
|
{
|
|
"name": name,
|
|
"registration_price": prices["register"],
|
|
"renewal_price": prices["renew"],
|
|
"transfer_price": prices["transfer"],
|
|
}
|
|
for name, prices in tld_data["registrars"].items()
|
|
]
|
|
registrars.sort(key=lambda x: x["registration_price"])
|
|
|
|
prices = tld_data["prices"]
|
|
|
|
return {
|
|
"tld": tld_clean,
|
|
"type": guess_tld_type(tld_clean),
|
|
"description": f".{tld_clean} domain extension",
|
|
"registry": "Unknown",
|
|
"introduced": None,
|
|
"registrars": registrars,
|
|
"cheapest_registrar": registrars[0]["name"] if registrars else "N/A",
|
|
"cheapest_price": min(prices) if prices else 0,
|
|
"price_range": {
|
|
"min": min(prices) if prices else 0,
|
|
"max": max(prices) if prices else 0,
|
|
"avg": round(sum(prices) / len(prices), 2) if prices else 0,
|
|
},
|
|
}
|
|
|
|
|
|
@router.get("/{tld}")
|
|
async def get_tld_details(
|
|
tld: str,
|
|
db: Database,
|
|
):
|
|
"""Get complete details for a specific TLD."""
|
|
tld_clean = tld.lower().lstrip(".")
|
|
|
|
# Try static data first
|
|
if tld_clean in TLD_DATA:
|
|
data = TLD_DATA[tld_clean]
|
|
|
|
registrars = []
|
|
for name, prices in data["registrars"].items():
|
|
registrars.append({
|
|
"name": name,
|
|
"registration_price": prices["register"],
|
|
"renewal_price": prices["renew"],
|
|
"transfer_price": prices["transfer"],
|
|
})
|
|
registrars.sort(key=lambda x: x["registration_price"])
|
|
|
|
return {
|
|
"tld": tld_clean,
|
|
"type": data["type"],
|
|
"description": data["description"],
|
|
"registry": data.get("registry", "Unknown"),
|
|
"introduced": data.get("introduced"),
|
|
"trend": data["trend"],
|
|
"trend_reason": data["trend_reason"],
|
|
"pricing": {
|
|
"avg": get_avg_price(data),
|
|
"min": get_min_price(data),
|
|
"max": get_max_price(data),
|
|
},
|
|
"registrars": registrars,
|
|
"cheapest_registrar": registrars[0]["name"],
|
|
}
|
|
|
|
# Fall back to database
|
|
db_prices = await get_db_prices(db, tld_clean)
|
|
if not db_prices:
|
|
raise HTTPException(status_code=404, detail=f"TLD '.{tld_clean}' not found")
|
|
|
|
tld_data = db_prices[tld_clean]
|
|
registrars = [
|
|
{
|
|
"name": name,
|
|
"registration_price": prices["register"],
|
|
"renewal_price": prices["renew"],
|
|
"transfer_price": prices["transfer"],
|
|
}
|
|
for name, prices in tld_data["registrars"].items()
|
|
]
|
|
registrars.sort(key=lambda x: x["registration_price"])
|
|
|
|
prices = tld_data["prices"]
|
|
|
|
return {
|
|
"tld": tld_clean,
|
|
"type": guess_tld_type(tld_clean),
|
|
"description": f".{tld_clean} domain extension",
|
|
"registry": "Unknown",
|
|
"introduced": None,
|
|
"trend": "stable",
|
|
"trend_reason": "Price tracking started recently",
|
|
"pricing": {
|
|
"avg": round(sum(prices) / len(prices), 2) if prices else 0,
|
|
"min": min(prices) if prices else 0,
|
|
"max": max(prices) if prices else 0,
|
|
},
|
|
"registrars": registrars,
|
|
"cheapest_registrar": registrars[0]["name"] if registrars else "N/A",
|
|
}
|