Jepang

IP rumahan asli

Proxy residensial Jepang

Proxy residensial Jepang adalah alamat IP asli dari rumah tangga di Jepang, yang diberikan oleh ISP konsumen seperti NTT Communications, KDDI, SoftBank, dan Sony Network Communications. Proxy ini memungkinkan Anda menjelajah, melakukan scraping, dan memverifikasi etalase, harga, serta konten Jepang layaknya pengguna lokal sungguhan — di Tokyo, Osaka, Nagoya, dan Kyoto — alih-alih dari IP datacenter yang langsung ditandai dan diblokir oleh Rakuten Ichiba, Yahoo! Shopping, dan geo-gate lokal.

Coba seharga $1.99/GB Masuk dengan Google

HTTP / SOCKS5Penargetan kota & ISPTraffic tidak pernah kedaluwarsaDiverifikasi bersih setiap bulan

142.699IP dalam pool

25+Kota terjangkau

101Jaringan ISP

110 msLatensi median

99.4%Benar-benar bersih

Sekilas tentang proxy residensial Jepang

Proxy residensial Jepang adalah alamat IP asli dari rumah tangga Jepang, yang diberikan oleh ISP konsumen. IP ini memungkinkan Anda menjelajah, melakukan scraping, dan memverifikasi situs web, harga, serta konten Jepang layaknya pengguna lokal sungguhan — bukan dari IP datacenter yang ditandai dan diblokir oleh situs lokal.

Jenis pool: Residensial, multi-ISP
Kota terjangkau: Tokyo, Minato, Minato-ku
ISP teratas: KDDI · NTT Communications · SoftBank
Protokol: HTTP, SOCKS5
Rotasi: Per-request atau sticky
Akurasi geo: 99.99%
Kebersihan pool: 99.4% clean
Harga: from $2.00/GB
Terakhir diukur: 2026-06-23
Dukungan: 24/7

Mengapa tim memilih pool Jepang kami

IP residensial asli, penargetan presisi, dan kualitas yang tidak perlu Anda percayai begitu saja.

IP residensial asli

Koneksi rumahan sungguhan dari ISP konsumen Jepang — bukan rentang datacenter yang langsung diblokir.

Penargetan kota & ISP

Targetkan kota dan operator tertentu sejauh kedalaman pool memungkinkan — hingga ke level penyedia.

Rotasi atau sticky

Rotasi per-request untuk skala besar, atau sesi sticky hingga ~72 jam untuk alur multi-langkah.

HTTP & SOCKS5

Langsung berfungsi dengan klien, scraper, atau stack otomasi apa pun tanpa konfigurasi tambahan.

Bersumber secara etis

IP dari jaringan residensial opt-in — pengguna nyata yang menyetujui untuk berbagi bandwidth.

Diverifikasi bersih, tiap bulan

Kami mengukur ulang pool setiap bulan dan mempublikasikan angkanya, agar selalu mutakhir.

Kualitas yang bisa Anda verifikasi

Setiap bulan kami menjalankan benchmark yang sama — sampel acak IP diberi skor oleh Scamalytics, latensi diuji dari VPS netral, dan akurasi geo diperiksa lintas basis data independen. Angka di bawah mencerminkan kondisi produksi, bukan hasil lab skenario terbaik.

Kebersihan Scamalytics · 100.000 IP

Benar-benar bersih99.4%

Kontaminasi datacenter0%

Ada di blacklist mana pun0.19%

Risiko penipuan rendah (0–19)99.4%

Akurasi geo99.99%

Latensi & kecepatan VPS → Cloudflare

Latensi median110ms

Latensi p90 / p95151 / 185 ms

Keberhasilan koneksi98.9%

Throughput (median / p95)6.84 / 7.42 MB/s

Penyelesaian file besar96%

Komposisi jaringan

Jenis koneksi100% residensial

Jaringan ISP (ASN)101

Mode rotasiper-request · sticky

Operator teratasKDDI · NTT Communications · SoftBank

Diukur pada 100.000 alamat dari VPS netral terhadap edge Cloudflare, akurat per benchmark terakhir. Pengujian ulang mungkin berbeda dalam margin kecil, tetapi angka-angka ini sepenuhnya mencerminkan orde besarannya dan menjadi dasar yang kuat untuk menilai apakah pool cocok untuk kasus penggunaan Anda. Tingkat keberhasilan scraping per-target tidak dipublikasikan — hal itu bergantung pada fingerprint dan pengaturan Anda, bukan hanya pada IP.

benchmark.py — benchmark pool terbuka

Benchmark terbuka di balik angka-angka di atas. Ia mengambil sampel acak IP pool dan mengukur empat hal — kebersihan (risiko penipuan Scamalytics, datacenter, blacklist, dan akurasi geo), latensi (round-trip edge Cloudflare dan ip-api), rotasi (IP unik, ASN, dan subnet /24), serta throughput (kecepatan unduh dan time-to-first-byte) — lalu melaporkan masing-masing. Skrip ini dipublikasikan secara utuh agar metodologi di balik setiap angka tetap terbuka untuk diperiksa.

# -*- coding: utf-8 -*-

"""
JETPROXY — POOL BENCHMARK

End-to-end audit of a residential proxy pool. A single run measures cleanliness,
latency, rotation and throughput, then prints every metric as one list.

  Cleanliness   fraud-risk, datacenter, blacklist and geo-accuracy (Scamalytics)
  Latency       Cloudflare edge (responsiveness) and ip-api origin (round-trip)
  Rotation      unique IPs / ASNs / subnets, success rate, country match
  Throughput    median & p95 download speed, time-to-first-byte, drop rate

Every stage size is a parameter, so the same script runs a quick check or a deep
audit:

    python benchmark.py --country ID
    python benchmark.py --quality 200 --downloads 50 --latency 1000 --rotation 5000 --country ID
    python benchmark.py --proxies proxies.txt --country ID --json result.json

Proxies   paste at the prompt (one per line) or pass --proxies FILE.
          host:port:user:pass  ·  host:port  ·  user:pass@host:port
The Scamalytics key for the cleanliness stage is read from the environment or
../.env (SCAMALYTICS_USER + SCAMALYTICS_KEY); without it that stage is skipped.
"""
from __future__ import annotations

import argparse
import asyncio
import csv
import ipaddress
import json
import os
import re
import statistics
import sys
import time
from collections import Counter
from datetime import datetime

try:
    sys.stdout.reconfigure(encoding="utf-8")
    sys.stderr.reconfigure(encoding="utf-8")
except Exception:
    pass

try:
    import aiohttp
    from rich.console import Console
    from rich.table import Table
    from rich import box
except ImportError:
    print("\n[!] Need: pip install aiohttp rich\n")
    sys.exit(1)

console = Console()

# ── endpoints ────────────────────────────────────────────────────────────────

IP_ENDPOINT = ("http://ip-api.com/json/?fields="
               "status,message,country,countryCode,regionName,city,isp,as,org,query")
CF_TRACE = "https://speed.cloudflare.com/cdn-cgi/trace"   # tiny edge response (~350 B)

FILE_MB = 10
DOWN_URL = f"https://speed.cloudflare.com/__down?bytes={FILE_MB * 1_000_000}"
SCAM_HOST = "https://api11.scamalytics.com/v3"            # US node (api12 = EU)


SCORE_CONCURRENCY = 10
DOWN_CONCURRENCY = 3   # downloads share the local uplink — keep low so the exit node is the bottleneck



# ── proxy parsing ──────────────────────────────────────────────────────────────

def parse_proxy(raw: str):
    """host:port | host:port:user:pass | user:pass@host:port | scheme://..."""
    raw = raw.strip()
    if not raw or raw.startswith("#"):
        return None
    scheme = "http"
    if "://" in raw:
        scheme, raw = raw.split("://", 1)
    user = pwd = host = port = None
    if "," in raw:
        parts = [p.strip() for p in raw.split(",")]
        if len(parts) == 4:
            host, port, user, pwd = parts
        elif len(parts) == 2:
            host, port = parts
        else:
            return None
    elif "@" in raw:
        cred, hostport = raw.rsplit("@", 1)
        if ":" in cred:
            user, pwd = cred.split(":", 1)
        host, port = hostport.rsplit(":", 1)
    else:
        parts = raw.split(":")
        if len(parts) == 2:
            host, port = parts
        elif len(parts) == 4:
            host, port, user, pwd = parts
        else:
            return None
    try:
        port = int(port)
    except (ValueError, TypeError):
        return None
    return {"scheme": scheme, "host": host, "port": port, "user": user, "pwd": pwd,
            "url": f"{scheme}://{host}:{port}", "label": f"{host}:{port}"}


def subnet24(ip: str) -> str:
    try:
        return str(ipaddress.ip_network(ip + "/24", strict=False))
    except ValueError:
        return ""


def pct(values, p):
    if not values:
        return 0.0
    s = sorted(values)
    k = min(len(s) - 1, max(0, int(round(p / 100 * (len(s) - 1)))))
    return s[k]


# ── ip-api request (identity + geo + round-trip) ───────────────────────────────

def _fail(idx, proxy, err, latency):
    return {"idx": idx, "ok": False, "proxy": proxy["label"], "error": err, "latency": latency}


async def _one_attempt(session, proxy, idx, timeout):
    t0 = time.perf_counter()
    auth = aiohttp.BasicAuth(proxy["user"], proxy["pwd"]) if proxy["user"] else None
    try:
        async with session.get(IP_ENDPOINT, proxy=proxy["url"], proxy_auth=auth,
                               timeout=aiohttp.ClientTimeout(total=timeout)) as r:
            latency = (time.perf_counter() - t0) * 1000
            if r.status != 200:
                return _fail(idx, proxy, f"HTTP {r.status}", latency)
            data = await r.json(content_type=None)
            if data.get("status") != "success":
                return _fail(idx, proxy, data.get("message", "api error"), latency)
            ip = data.get("query", "")
            asn = data.get("as", "").split(" ")[0] if data.get("as") else ""
            return {"idx": idx, "ok": True, "proxy": proxy["label"], "ip": ip,
                    "country": data.get("country", ""), "cc": data.get("countryCode", ""),
                    "region": data.get("regionName", ""), "city": data.get("city", ""),
                    "isp": data.get("isp") or data.get("org", ""), "asn": asn,
                    "org": data.get("org") or data.get("as", ""),
                    "subnet": subnet24(ip), "latency": latency, "error": ""}
    except asyncio.TimeoutError:
        return _fail(idx, proxy, "timeout", (time.perf_counter() - t0) * 1000)
    except Exception as e:
        return _fail(idx, proxy, type(e).__name__, (time.perf_counter() - t0) * 1000)


async def fetch(session, proxy, sem, idx, timeout, max_retries=2):
    async with sem:
        res = None
        for attempt in range(1, max_retries + 2):
            res = await _one_attempt(session, proxy, idx, timeout)
            if res["ok"]:
                res["attempts"] = attempt
                res["first_try_ok"] = (attempt == 1)
                return res
        res["attempts"] = max_retries + 1
        res["first_try_ok"] = False
        return res


# ── Cloudflare edge probe (responsiveness + nearest datacenter) ────────────────

async def cf_probe(proxy, sem, timeout):
    """One warm-up request opens the tunnel + TLS, then the next request on the same
    kept-alive connection is timed — so the figure is the edge round-trip, not the
    one-off connection setup."""
    async with sem:
        auth = aiohttp.BasicAuth(proxy["user"], proxy["pwd"]) if proxy["user"] else None
        try:
            async with aiohttp.ClientSession(connector=aiohttp.TCPConnector(limit=2, ssl=False)) as sess:
                async with sess.get(CF_TRACE, proxy=proxy["url"], proxy_auth=auth,
                                    timeout=aiohttp.ClientTimeout(total=15)) as w:
                    await w.read()
                t0 = time.perf_counter()
                async with sess.get(CF_TRACE, proxy=proxy["url"], proxy_auth=auth,
                                    timeout=aiohttp.ClientTimeout(total=timeout)) as r:
                    txt = await r.text()
                    rtt = (time.perf_counter() - t0) * 1000
                    if r.status != 200:
                        return {"ok": False, "error": f"HTTP {r.status}"}
                    d = {}
                    for ln in txt.splitlines():
                        if "=" in ln:
                            k, v = ln.split("=", 1)
                            d[k] = v
                    return {"ok": True, "rtt": rtt, "ip": d.get("ip", ""),
                            "loc": d.get("loc", ""), "colo": d.get("colo", "")}
        except asyncio.TimeoutError:
            return {"ok": False, "error": "timeout"}
        except Exception as e:
            return {"ok": False, "error": type(e).__name__}


# ── download (throughput + TTFB + mid-transfer drops) ──────────────────────────

async def download(proxy, sem, idx, timeout, retries):
    async with sem:
        auth = aiohttp.BasicAuth(proxy["user"], proxy["pwd"]) if proxy["user"] else None
        last_err = ""
        dropped_at = []
        for attempt in range(1, retries + 2):
            try:
                async with aiohttp.ClientSession(connector=aiohttp.TCPConnector(limit=4, ssl=False)) as sess:
                    country = "?"
                    try:
                        async with sess.get(CF_TRACE, proxy=proxy["url"], proxy_auth=auth,
                                            timeout=aiohttp.ClientTimeout(total=15)) as tr:
                            for ln in (await tr.text()).splitlines():
                                if ln.startswith("loc="):
                                    country = ln[4:].strip() or "?"
                    except Exception:
                        pass
                    t0 = time.perf_counter()
                    async with sess.get(DOWN_URL, proxy=proxy["url"], proxy_auth=auth,
                                        timeout=aiohttp.ClientTimeout(total=timeout)) as r:
                        if r.status != 200:
                            last_err = f"HTTP {r.status}"
                            continue
                        first = None
                        nbytes = 0
                        try:
                            async for chunk in r.content.iter_chunked(65536):
                                if first is None:
                                    first = time.perf_counter()
                                nbytes += len(chunk)
                        except Exception as stream_err:
                            if nbytes > 0:
                                dropped_at.append(nbytes)
                                last_err = f"dropped@{nbytes // 1_000_000}MB"
                            else:
                                last_err = type(stream_err).__name__
                            continue
                        end = time.perf_counter()
                        if nbytes == 0:
                            last_err = "empty"
                            continue
                        ttfb = (first - t0) * 1000 if first else 0
                        dl_time = (end - first) if first and end > first else (end - t0)
                        mbps = (nbytes / 1_000_000) / dl_time if dl_time > 0 else 0
                        return {"idx": idx, "ok": True, "country": country, "bytes": nbytes,
                                "ttfb_ms": ttfb, "mbps": mbps, "dropped": bool(dropped_at), "error": ""}
            except asyncio.TimeoutError:
                last_err = "timeout"
            except Exception as e:
                last_err = type(e).__name__
        return {"idx": idx, "ok": False, "country": "?", "bytes": 0, "ttfb_ms": 0,
                "mbps": 0, "dropped": bool(dropped_at), "error": last_err}


# ── Scamalytics scoring ────────────────────────────────────────────────────────

def load_creds():
    user = os.environ.get("SCAMALYTICS_USER")
    key = os.environ.get("SCAMALYTICS_KEY")
    if user and key:
        return user.strip(), key.strip()
    found = {}
    for path in ("../.env", "../.env.local", ".env"):
        p = os.path.join(os.path.dirname(__file__), path)
        if os.path.exists(p):
            with open(p, encoding="utf-8") as f:
                for line in f:
                    m = re.match(r'\s*(SCAMALYTICS_USER|SCAMALYTICS_KEY)\s*=\s*"?([^"\s]+)"?', line)
                    if m:
                        found[m.group(1)] = m.group(2)
    return found.get("SCAMALYTICS_USER"), found.get("SCAMALYTICS_KEY")


def parse_scam(ip, data):
    s = data.get("scamalytics", {})
    if s.get("status") != "ok":
        return {"ip": ip, "ok": False, "error": s.get("status") or "bad_response"}
    ext = data.get("external_datasources", {})
    score = s.get("scamalytics_score")
    risk = s.get("scamalytics_risk", "?")
    px = s.get("scamalytics_proxy", {})
    is_dc = bool(px.get("is_datacenter"))
    is_vpn = bool(px.get("is_vpn"))
    fh = bool(ext.get("firehol", {}).get("is_proxy"))
    ips_bl = bool(ext.get("ipsum", {}).get("ip_blacklisted"))
    sh = bool(ext.get("spamhaus_drop", {}).get("ip_blacklisted"))
    x4 = bool(ext.get("x4bnet", {}).get("is_blacklisted_spambot"))
    on_bl = bool(s.get("is_blacklisted_external")) or fh or ips_bl or sh or x4
    cc = (ext.get("dbip", {}).get("ip_country_code")
          or ext.get("ipinfo", {}).get("ip_country_code")
          or ext.get("maxmind_geolite2", {}).get("ip_country_code")
          or ext.get("ip2proxy_lite", {}).get("ip_country_code") or "?")
    isp = (ext.get("dbip", {}).get("isp_name")
           or ext.get("ip2proxy_lite", {}).get("isp_name")
           or s.get("scamalytics_isp") or "?")
    asn = ext.get("ipinfo", {}).get("asn") or ext.get("ip2proxy_lite", {}).get("asn") or "?"
    return {"ip": ip, "ok": True, "error": "", "score": score if isinstance(score, int) else 0,
            "risk": risk, "is_dc": is_dc, "is_vpn": is_vpn, "on_bl": on_bl,
            "country": cc, "isp": isp, "asn": asn,
            "credits": s.get("credits", {}).get("remaining"),
            "strict_clean": (risk == "low" and not is_dc and not on_bl)}


async def score_one(session, user, key, ip, sem):
    async with sem:
        try:
            async with session.get(f"{SCAM_HOST}/{user}/", params={"key": key, "ip": ip},
                                   timeout=aiohttp.ClientTimeout(total=20)) as r:
                return parse_scam(ip, await r.json(content_type=None))
        except Exception as e:
            return {"ip": ip, "ok": False, "error": type(e).__name__}


# ── stage runners ──────────────────────────────────────────────────────────────

def progress(tag, done, total):
    step = max(1, total // 10)
    if done % step == 0 or done == total:
        console.print(f"   [{tag}] {done}/{total}", highlight=False)


async def run_ipapi(proxies, n, concurrency, timeout, retries, tag):
    sem = asyncio.Semaphore(concurrency)
    conn = aiohttp.TCPConnector(limit=concurrency * 3, ssl=False)
    out = []
    async with aiohttp.ClientSession(connector=conn) as http:
        tasks = [asyncio.create_task(fetch(http, proxies[i % len(proxies)], sem, i, timeout, retries))
                 for i in range(n)]
        for done, coro in enumerate(asyncio.as_completed(tasks), 1):
            out.append(await coro)
            progress(tag, done, n)
    return out


async def run_cf(proxies, n, concurrency, timeout, tag):
    sem = asyncio.Semaphore(concurrency)
    tasks = [asyncio.create_task(cf_probe(proxies[i % len(proxies)], sem, timeout))
             for i in range(n)]
    out = []
    for done, coro in enumerate(asyncio.as_completed(tasks), 1):
        out.append(await coro)
        progress(tag, done, n)
    return out


async def run_download(proxies, n, timeout, retries, tag):
    sem = asyncio.Semaphore(DOWN_CONCURRENCY)
    tasks = [asyncio.create_task(download(proxies[i % len(proxies)], sem, i, timeout, retries))
             for i in range(n)]
    out = []
    for done, coro in enumerate(asyncio.as_completed(tasks), 1):
        out.append(await coro)
        progress(tag, done, n)
    return out


async def score_ips(ips, user, key, tag):
    sem = asyncio.Semaphore(SCORE_CONCURRENCY)
    out = []
    async with aiohttp.ClientSession() as session:
        tasks = [asyncio.create_task(score_one(session, user, key, ip, sem)) for ip in ips]
        for done, coro in enumerate(asyncio.as_completed(tasks), 1):
            out.append(await coro)
            progress(tag, done, len(ips))
    return out


# ── input ──────────────────────────────────────────────────────────────────────

def read_proxies(path):
    if path:
        with open(path, encoding="utf-8") as f:
            lines = f.readlines()
    else:
        console.print("Paste proxies (one per line), then an empty line:")
        lines = []
        while True:
            try:
                ln = input()
            except EOFError:
                break
            if ln.strip() == "":
                if lines:
                    break
                continue
            lines.append(ln)
    return [p for p in (parse_proxy(l) for l in lines) if p]


def fmt(v, suffix=""):
    return f"{v}{suffix}"


# ── main ─────────────────────────────────────────────────────────────────────

def build_report(M):
    t = Table(title="POOL BENCHMARK — RESULTS", box=box.DOUBLE_EDGE, header_style="bold cyan",
              title_style="bold green")
    t.add_column("Metric", style="cyan")
    t.add_column("Value", style="bold white", justify="right")
    for section, rows in M["sections"]:
        t.add_row(f"[bold yellow]{section}[/]", "")
        for k, v in rows:
            t.add_row(f"  {k}", str(v))
    console.print()
    console.print(t)


async def run(args, proxies):
    M = {"label": args.label, "country": args.country or None,
         "timestamp": datetime.now().isoformat(timespec="seconds"),
         "proxies_input": len(proxies), "stages": {}}
    user = key = None

    # 1 — cleanliness (Scamalytics)

    clean_rows = []
    if not args.no_quality and args.quality > 0:
        user, key = load_creds()
        if not user or not key:
            console.print("[yellow]Scamalytics key not found — skipping cleanliness stage.[/]")
        else:
            console.rule(f"[bold]Cleanliness — {args.quality} IPs[/]")
            collected = await run_ipapi(proxies, int(args.quality * 1.6) + 10,
                                        args.concurrency, 15, 1, "collect")
            uniq = {}
            for r in collected:
                if r.get("ok") and r.get("ip") and r["ip"] not in uniq:
                    uniq[r["ip"]] = r
            ips = list(uniq.keys())[:args.quality]
            scored = await score_ips(ips, user, key, "score")
            ok = [r for r in scored if r.get("ok")]
            n = len(ok)
            if n:
                strict = sum(r["strict_clean"] for r in ok) / n * 100
                low = sum(1 for r in ok if r["risk"] == "low") / n * 100
                dc = sum(r["is_dc"] for r in ok) / n * 100
                bl = sum(r["on_bl"] for r in ok) / n * 100
                vpn = sum(r["is_vpn"] for r in ok)
                geo = None
                if args.country:
                    geo = sum(1 for r in ok if (r["country"] or "").upper() == args.country.upper()) / n * 100
                M["stages"]["cleanliness"] = {
                    "n": n, "strict_clean_pct": round(strict, 1), "low_risk_pct": round(low, 1),
                    "datacenter_pct": round(dc, 1), "blacklist_pct": round(bl, 1),
                    "geo_accuracy_pct": round(geo, 1) if geo is not None else None, "vpn": vpn}
                clean_rows = [("Strictly clean", f"{strict:.1f}%"),
                              ("Low fraud-risk (0–19)", f"{low:.1f}%"),
                              ("Datacenter", f"{dc:.1f}%"),
                              ("Blacklisted", f"{bl:.1f}%")]
                if geo is not None:
                    clean_rows.append((f"Geo-accuracy ({args.country.upper()})", f"{geo:.1f}%"))
                # per-IP CSV

                ts = datetime.now().strftime("%Y%m%d_%H%M%S")
                with open(f"benchmark_ips_{ts}.csv", "w", newline="", encoding="utf-8") as f:
                    w = csv.writer(f)
                    w.writerow(["ip", "score", "risk", "is_datacenter", "is_vpn", "on_blacklist",
                                "country", "isp", "asn", "strict_clean"])
                    for r in scored:
                        if r.get("ok"):
                            w.writerow([r["ip"], r["score"], r["risk"], r["is_dc"], r["is_vpn"],
                                        r["on_bl"], r["country"], r["isp"], r["asn"], r["strict_clean"]])

    # 2 — throughput

    console.rule(f"[bold]Throughput — {args.downloads} downloads[/]")
    dl = await run_download(proxies, args.downloads, 60, 1, "download")
    dok = [r for r in dl if r["ok"]]
    dl_rows = []
    if dok:
        mbps = [r["mbps"] for r in dok]
        ttfb = [r["ttfb_ms"] for r in dok]
        nodrop = sum(1 for r in dl if r["ok"] and not r["dropped"]) / len(dl) * 100
        M["stages"]["throughput"] = {
            "n": len(dl), "ok": len(dok),
            "median_mbps": round(statistics.median(mbps), 2), "p95_mbps": round(pct(mbps, 95), 2),
            "median_ttfb_ms": round(statistics.median(ttfb)), "completed_no_drop_pct": round(nodrop, 1)}
        dl_rows = [("Median download", f"{statistics.median(mbps):.1f} MB/s ({statistics.median(mbps)*8:.0f} Mbps)"),
                   ("p95 download", f"{pct(mbps,95):.1f} MB/s ({pct(mbps,95)*8:.0f} Mbps)"),
                   ("Median TTFB", f"{statistics.median(ttfb):.0f} ms"),
                   ("Completed without drop", f"{nodrop:.0f}%")]

    # 3 — latency (Cloudflare edge + ip-api origin)

    console.rule(f"[bold]Latency — {args.latency} probes[/]")
    cf = await run_cf(proxies, args.latency, args.concurrency, 15, "cf")
    cfok = [r for r in cf if r["ok"]]
    lat_rows = []
    if cfok:
        rtts = [r["rtt"] for r in cfok]
        colo = Counter(r["colo"] for r in cfok if r["colo"]).most_common(1)
        M["stages"].setdefault("latency", {})
        M["stages"]["latency"]["cloudflare"] = {
            "n": len(cfok), "p50_ms": round(statistics.median(rtts)),
            "p90_ms": round(pct(rtts, 90)), "p95_ms": round(pct(rtts, 95)),
            "top_colo": colo[0][0] if colo else None}
        lat_rows += [("Cloudflare edge — p50", f"{statistics.median(rtts):.0f} ms"),
                     ("Cloudflare edge — p90", f"{pct(rtts,90):.0f} ms"),
                     ("Cloudflare edge — p95", f"{pct(rtts,95):.0f} ms")]
        if colo:
            lat_rows.append(("Nearest datacenter", colo[0][0]))

    # 4 — rotation (also yields ip-api round-trip latency)

    console.rule(f"[bold]Rotation — {args.rotation} requests[/]")
    rot = await run_ipapi(proxies, args.rotation, args.concurrency, args.timeout, 2, "rotation")
    rok = [r for r in rot if r["ok"]]
    rot_rows = []
    if rok:
        uips = {r["ip"] for r in rok if r.get("ip")}
        uasn = {r["asn"] for r in rok if r.get("asn")}
        usub = {r["subnet"] for r in rok if r.get("subnet")}
        success = len(rok) / len(rot) * 100
        first = sum(1 for r in rok if r.get("first_try_ok")) / len(rot) * 100
        cmatch = None
        if args.country:
            cmatch = sum(1 for r in rok if (r["cc"] or "").upper() == args.country.upper()) / len(rok) * 100
        ipapi_rtts = [r["latency"] for r in rok]
        M["stages"]["rotation"] = {
            "n": len(rot), "success_pct": round(success, 1), "first_try_pct": round(first, 1),
            "unique_ips": len(uips), "unique_asns": len(uasn), "unique_subnets": len(usub),
            "country_match_pct": round(cmatch, 2) if cmatch is not None else None}
        M["stages"].setdefault("latency", {})
        M["stages"]["latency"]["ip_api"] = {
            "n": len(ipapi_rtts), "p50_ms": round(statistics.median(ipapi_rtts)),
            "p90_ms": round(pct(ipapi_rtts, 90))}
        lat_rows += [("ip-api origin — p50", f"{statistics.median(ipapi_rtts):.0f} ms"),
                     ("ip-api origin — p90", f"{pct(ipapi_rtts,90):.0f} ms")]
        rot_rows = [("Success rate", f"{success:.1f}%"),
                    ("First-try success", f"{first:.1f}%"),
                    ("Unique exit IPs", f"{len(uips)}"),
                    ("Unique networks (ASN)", f"{len(uasn)}"),
                    ("Unique /24 subnets", f"{len(usub)}")]
        if cmatch is not None:
            rot_rows.append((f"Country match ({args.country.upper()})", f"{cmatch:.2f}%"))

    M["sections"] = [s for s in [
        ("CLEANLINESS", clean_rows), ("LATENCY", lat_rows),
        ("ROTATION", rot_rows), ("THROUGHPUT", dl_rows)] if s[1]]
    build_report(M)

    out_path = args.json or f"benchmark_{args.label}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
    M.pop("sections", None)
    with open(out_path, "w", encoding="utf-8") as f:
        json.dump(M, f, indent=2, ensure_ascii=False)
    console.print(f"\n[green]✓[/] Saved: [bold]{out_path}[/]")


def main():
    ap = argparse.ArgumentParser(description="Jetproxy pool benchmark")
    ap.add_argument("--quality", type=int, default=100, help="IPs scored for cleanliness")
    ap.add_argument("--downloads", type=int, default=50, help="download samples")
    ap.add_argument("--latency", type=int, default=1000, help="latency probes")
    ap.add_argument("--rotation", type=int, default=2000, help="rotation requests")
    ap.add_argument("--concurrency", type=int, default=20)
    ap.add_argument("--timeout", type=float, default=15.0)
    ap.add_argument("--country", default="", help="expected ISO code for geo-accuracy")
    ap.add_argument("--proxies", default="", help="proxy list file (else paste)")
    ap.add_argument("--label", default="pool")
    ap.add_argument("--json", default="")
    ap.add_argument("--no-quality", action="store_true", help="skip the cleanliness stage")
    args = ap.parse_args()

    console.print("\n[bold cyan]═══  JETPROXY — POOL BENCHMARK  ═══[/]\n")
    proxies = read_proxies(args.proxies)
    if not proxies:
        console.print("[red]No valid proxies.[/]")
        return
    console.print(f"[green]✓[/] Proxies loaded: [bold]{len(proxies)}[/]")
    asyncio.run(run(args, proxies))


if __name__ == "__main__":
    try:
        main()
    except KeyboardInterrupt:
        console.print("\n[yellow]Interrupted.[/]")

Targetkan hingga ke level kota

«Rata-rata online» adalah jumlah rata-rata perangkat berbeda yang terhubung dan tersedia pada saat bersamaan — bukan total kumulatif. Dikelompokkan menjadi Tinggi / Sedang / Rendah.

WilayahKotaPenyedia

Wilayah	Latensi	Rata-rata online	Pool
Tokyo	106 ms	~4.417	Tinggi
Osaka	107 ms	~1.089	Tinggi
Aichi	107 ms	~869	Tinggi
Saitama	101 ms	~748	Tinggi
Kanagawa	105 ms	~734	Tinggi
Chiba	102 ms	~423	Tinggi
Hyōgo	108 ms	~412	Tinggi
Hokkaido	132 ms	~359	Tinggi
Fukuoka	126 ms	~357	Tinggi
Shizuoka	115 ms	~348	Tinggi
Kyoto	108 ms	~291	Sedang
Hiroshima	117 ms	~245	Sedang
Tochigi	105 ms	~226	Sedang
Gunma	114 ms	~204	Sedang
Ibaraki	105 ms	~178	Sedang
Niigata	119 ms	~169	Sedang
Gifu	110 ms	~160	Sedang
Miyagi	125 ms	~160	Sedang
Okayama	121 ms	~153	Sedang
Fukushima	111 ms	~142	Sedang
Shiga	111 ms	~124	Rendah
Mie	108 ms	~119	Rendah
Kagoshima	135 ms	~117	Rendah
Nagano	117 ms	~108	Rendah
Shimane	116 ms	~98	Rendah
Kumamoto	130 ms	~94	Rendah
Nara	106 ms	~94	Rendah
Oita	124 ms	~87	Rendah
Okinawa	155 ms	~87	Rendah
Yamaguchi	126 ms	~82	Rendah

Kota	Latensi	Rata-rata online	Pool
Tokyo	100 ms	~2.061	Tinggi
Minato	108 ms	~1.562	Tinggi
Minato-ku	109 ms	~1.516	Tinggi
Osaka	109 ms	~989	Tinggi
Chiyoda City	116 ms	~893	Tinggi
Nagoya	107 ms	~765	Tinggi
Kyoto	108 ms	~541	Tinggi
Sapporo	130 ms	~508	Tinggi
Yokohama	103 ms	~431	Tinggi
Hiroshima	117 ms	~312	Sedang
Kawaguchi	102 ms	~302	Sedang
Fukuoka	123 ms	~266	Sedang
Nakano City	116 ms	~243	Sedang
Kobe	106 ms	~238	Sedang
Funabashi	102 ms	~229	Sedang
Suita	101 ms	~206	Sedang
Sakai	99 ms	~202	Rendah
Hamamatsu	121 ms	~188	Rendah
Shinjuku	102 ms	~188	Rendah
Sendai	131 ms	~188	Rendah
Okayama	124 ms	~183	Rendah
Kagoshima	131 ms	~179	Rendah
Ōtsu	109 ms	~179	Rendah
Utsunomiya	108 ms	~169	Rendah
Tsukuba	104 ms	~156	Rendah

Penyedia	Latensi	Rata-rata online	Pool
KDDItetap	113 ms	~2.860	Tinggi
NTT Communicationstetap	115 ms	~2.530	Tinggi
SoftBanktetap	110 ms	~2.027	Tinggi
So-net (Sony Network Communications)tetap	98 ms	~1.113	Tinggi
OPTAGEtetap	102 ms	~680	Tinggi
JCNtetap	129 ms	~659	Sedang
Arteriatetap	96 ms	~571	Sedang
BIGLOBEtetap	111 ms	~496	Sedang
Chubu Telecommunicationstetap	106 ms	~413	Sedang
ASAHI Nettetap	105 ms	~386	Rendah
J:COMtetap	120 ms	~335	Rendah
QTnettetap	128 ms	~265	Rendah
TOKAI Communicationstetap	106 ms	~182	Rendah
Internet Multifeedtetap	97 ms	~177	Rendah

Akurasi geo — setiap IP yang dijual sebagai Jepang terpetakan ke Jepang di tiga basis data geo independen (db-ip, MaxMind, ipinfo); akurasi geo yang tinggi adalah sinyal yang diandalkan oleh geo-gate lokal.

Proxy Jepang berdasarkan kasus penggunaan

Disusun berdasarkan apa yang Anda lakukan, bukan berdasarkan platform. Layanan lokal dicantumkan di tempat yang relevan.

E-commerce & riset pasar

Periksa etalase, harga, dan listing lokal dari dalam pasar itu sendiri.

Pemantauan etalase
Pelacakan harga lokal
Riset penjual

Rakuten IchibaAmazon JapanYahoo! ShoppingYodobashi.comBic Camera

Verifikasi & performa iklan

Lihat bagaimana iklan, materi kreatif, dan SERP tampil bagi pengguna lokal — tanpa pergantian manual.

SERP lokal
Pengecekan kreatif
Halaman landing

LINEX (Twitter)Instagram

Perjalanan & intelijen harga

Tangkap tarif penerbangan dan hotel sebagaimana dilihat oleh pelanggan lokal.

Tarif berbasis geo
Pemantauan penawaran
Perbandingan tarif

Rakuten TravelJalanIkyu.comJALANA

Streaming & verifikasi geo

Verifikasi katalog yang dikunci wilayah dan geo-gate dari lokasi yang tepat.

Pengecekan geo
Verifikasi katalog
Ketersediaan regional

U-NEXTABEMATVerHulu JapanLemino

Iklan baris & listing lokal

Pantau barang bekas, mobil, dan sewaan di berbagai iklan baris lokal.

Pemantauan listing
Pelacakan harga
Cakupan regional

MercariYahoo! Auctions (Yahuoku)Rakuma (Rakuten)Yahoo! Flea MarketJmty

Dev & otomasi

IP residensial untuk pipeline, pengujian, dan pengumpulan data yang diizinkan melalui API.

Integrasi pipeline
Manajemen API
Sesi sticky

PythonScrapycURLGitHub

Selain situs lokal, pool Jepang yang sama juga berfungsi untuk platform global besar — Google, Meta, Amazon, YouTube, TikTok, dan Netflix — dilihat dari locale Jepang: harga lokal, iklan, katalog, SERP, dan konten.

Developer API

Buat endpoint dengan cakupan Jepang di dashboard, salin snippet yang sudah teruji, atau otomatiskan daftar proxy melalui API publik. Kota, ISP, sesi sticky, dan daftar tersimpan tetap dalam satu alur kerja yang rapi.

Dokumentasi API

1import requests
2 
3headers = {"x-api-key": "gpx_live_YOUR_KEY"}
4payload = {
5  "country_code": "JP",
6  "city": "Tokyo",
7  "session_type": "sticky",
8  "quantity": 5,
9  "protocol": "socks5"
10}
11 
12response = requests.post(
13  "https://jetproxy.io/api/v1/generate",
14  headers=headers,
15  json=payload,
16  timeout=30
17)
18print(response.json()["proxies"])

Paket tanpa syarat tersembunyi

Semakin besar volume, semakin rendah harga per gigabyte. Tanpa langganan atau biaya tersembunyi.

1 GB$3.70

$3.70 / GB

Pilih

5 GB$18.00

$3.60 / GB

Pilih

10 GB$34.50

$3.45 / GB

Pilih

Populer

25 GB$80.00

$3.20 / GB

Pilih

50 GB$147.50

$2.95 / GB

Pilih

100 GB$270.00

$2.70 / GB

Pilih

250 GB$612.50

$2.45 / GB

Pilih

500 GB$1,100.00

$2.20 / GB

Pilih

1 TB$2,000.00

$2.00 / GB

Pilih

Paket

Harga per GB

Total

1 GB

$3.70 / GB

$3.70Pilih

5 GB

$3.60 / GB

$18.00Pilih

10 GB

$3.45 / GB

$34.50Pilih

Populer

25 GB

$3.20 / GB

$80.00Pilih

50 GB

$2.95 / GB

$147.50Pilih

100 GB

$2.70 / GB

$270.00Pilih

250 GB

$2.45 / GB

$612.50Pilih

500 GB

$2.20 / GB

$1,100.00Pilih

1 TB

$2.00 / GB

$2,000.00Pilih

Metode pembayaran yang tersedia

Pertanyaan yang benar-benar ditanyakan pembeli

Masih menimbang apakah pool Jepang cocok untuk kasus penggunaan Anda? Tim kami menjawab pertanyaan nyata di Telegram, sepanjang waktu — sebelum dan sesudah Anda membeli.

Ngobrol di Telegram

Apakah ini akan berfungsi untuk scraping Rakuten Ichiba dan Yahoo! Shopping?

Itulah use case utamanya. Pool ini residensial asli — karakteristik yang dicari oleh sistem anti-bot marketplace lokal — sehingga IP-IP ini lolos di tempat yang memblokir rentang datacenter. Hasilnya tetap bergantung pada fingerprint, header, dan ritme permintaan Anda, jadi padukan proxy dengan konfigurasi yang bersih dan zona waktu Jepang yang sesuai (JST).

Bisakah saya menargetkan kota tertentu seperti Tokyo atau Osaka?

Bisa, selama kedalaman pool memungkinkan — pilih kota saat Anda membuat daftar proxy. Tabel cakupan kami menampilkan konkurensi langsung untuk Tokyo, Osaka, Nagoya, Kyoto, Yokohama, Sapporo, dan lainnya, sehingga Anda dapat melihat kota mana yang memiliki rotasi terdalam sebelum memutuskan.

Apakah IP-nya terdeteksi berlokasi di Jepang?

Ya — pool ini terdeteksi berada di Jepang dengan akurasi geo 99,99% terhadap Cloudflare dan di berbagai basis data geo independen pada benchmark terakhir kami, dengan exit node yang terkonfirmasi di Tokyo (NRT), Osaka (KIX), dan Fukuoka (FUK). Akurasi geo yang tinggi adalah sinyal mendasar yang diandalkan oleh geo-gate Jepang.

Bisakah saya mempertahankan satu IP Jepang untuk alur multi-langkah?

Bisa. Gunakan sticky session untuk mempertahankan exit IP Jepang yang sama — durasi rata-rata sekitar 4,5 jam dan hingga 72 jam dalam pengukuran 3 hari kami. Untuk skala besar, rotasikan per permintaan: exit IP berubah pada sekitar 96% permintaan, biasanya beralih ke penyedia yang berbeda, bukan sekadar alamat tetangga.

Operator dan kota Jepang mana saja yang tercakup?

Pool ini mencakup 14 ISP Jepang yang dipimpin oleh NTT Communications, KDDI, SoftBank, Sony Network Communications, OPTAGE, dan BIGLOBE, di 30 wilayah dan 25 kota — mulai dari Tokyo, Yokohama, dan Nagoya hingga Osaka, Kyoto, Sapporo, dan Fukuoka.