Meksiko

IP rumahan asli

Proxy residensial Meksiko

Proxy residensial Meksiko adalah alamat IP asli dari rumah tangga di Meksiko, yang diberikan oleh ISP konsumen seperti Telmex (Infinitum), Total Play, Megacable, dan Izzi. Dengan proxy ini Anda bisa menjelajah, melakukan scraping, dan memverifikasi etalase, harga, serta konten Meksiko layaknya pengguna asli dari dalam negeri — di Mexico City, Guadalajara, Monterrey, dan Tijuana — alih-alih dari IP datacenter yang langsung ditandai dan diblokir oleh Mercado Libre, Coppel, serta geo-gate lokal.

Coba seharga $1.99/GB Masuk dengan Google

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

276.405IP dalam pool

25+Kota terjangkau

113Jaringan ISP

304 msLatensi median

99.4%Benar-benar bersih

Sekilas tentang proxy residensial Meksiko

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

Jenis pool: Residensial, multi-ISP
Kota terjangkau: Benito Juarez, Mexico City, Guadalajara
ISP teratas: Telmex (Infinitum) · Total Play · Megacable
Protokol: HTTP, SOCKS5
Rotasi: Per-request atau sticky
Akurasi geo: 100%
Kebersihan pool: 99.4% clean
Harga: from $2.00/GB
Terakhir diukur: 2026-06-23
Dukungan: 24/7

Mengapa tim memilih pool Meksiko kami

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

IP residensial asli

Koneksi rumahan sungguhan dari ISP konsumen Meksiko — 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 pun0.29%

Risiko penipuan rendah (0–19)99.5%

Akurasi geo100%

Latensi & kecepatan VPS → Cloudflare

Latensi median304ms

Latensi p90 / p95394 / 488 ms

Keberhasilan koneksi99.3%

Throughput (median / p95)1.59 / 4.02 MB/s

Penyelesaian file besar86%

Komposisi jaringan

Jenis koneksi100% residensial

Jaringan ISP (ASN)113

Mode rotasiper-request · sticky

Operator teratasTelmex (Infinitum) · Total Play · Megacable

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
Mexico City	303 ms	~5.654	Tinggi
México	305 ms	~1.953	Tinggi
Jalisco	314 ms	~1.896	Tinggi
Nuevo León	295 ms	~1.871	Tinggi
Baja California	262 ms	~1.330	Tinggi
Veracruz	320 ms	~1.264	Tinggi
Puebla	308 ms	~958	Tinggi
Guanajuato	307 ms	~950	Tinggi
Sonora	266 ms	~793	Tinggi
Sinaloa	290 ms	~698	Tinggi
Coahuila	293 ms	~694	Sedang
Tamaulipas	297 ms	~669	Sedang
Michoacán	304 ms	~657	Sedang
Chihuahua	298 ms	~628	Sedang
Querétaro	305 ms	~508	Sedang
Yucatán	332 ms	~458	Sedang
Chiapas	326 ms	~454	Sedang
San Luis Potosí	301 ms	~392	Sedang
Tabasco	322 ms	~355	Sedang
Quintana Roo	328 ms	~351	Sedang
Baja California Sur	289 ms	~281	Rendah
Hidalgo	317 ms	~260	Rendah
Aguascalientes	307 ms	~227	Rendah
Oaxaca	353 ms	~227	Rendah
Zacatecas	315 ms	~219	Rendah
Morelos	329 ms	~194	Rendah
Colima	287 ms	~186	Rendah
Durango	343 ms	~165	Rendah
Guerrero	313 ms	~157	Rendah
Tlaxcala	310 ms	~140	Rendah

Kota	Latensi	Rata-rata online	Pool
Benito Juarez	298 ms	~2.525	Tinggi
Mexico City	311 ms	~2.502	Tinggi
Guadalajara	327 ms	~1.530	Tinggi
Monterrey	296 ms	~1.454	Tinggi
Gustavo Adolfo Madero	316 ms	~1.354	Tinggi
Tijuana	254 ms	~1.331	Tinggi
Puebla City	308 ms	~1.316	Tinggi
Veracruz	314 ms	~972	Tinggi
León	313 ms	~849	Tinggi
Cuauhtémoc	284 ms	~826	Sedang
Zapopan	266 ms	~773	Sedang
Mexicali	282 ms	~773	Sedang
Querétaro City	303 ms	~757	Sedang
Hermosillo	255 ms	~742	Sedang
Iztapalapa	301 ms	~742	Sedang
Mérida	331 ms	~719	Sedang
Torreón	292 ms	~673	Rendah
Culiacán	282 ms	~643	Rendah
San Luis Potosí City	297 ms	~635	Rendah
Ciudad Juárez	290 ms	~627	Rendah
Morelia	304 ms	~620	Rendah
Guadalupe	292 ms	~604	Rendah
Tuxtla Gutiérrez	325 ms	~566	Rendah
Reynosa	301 ms	~536	Rendah
Naucalpan	307 ms	~520	Rendah

Penyedia	Latensi	Rata-rata online	Pool
Telmex (Infinitum)tetap	296 ms	~9.404	Tinggi
Total Playtetap	294 ms	~6.615	Tinggi
Megacabletetap	313 ms	~4.733	Tinggi
Izzitetap	252 ms	~3.161	Tinggi
Alestratetap	338 ms	~298	Tinggi
Velocom De CVtetap	340 ms	~74	Sedang
Television POR Cable Tepa De C.Vtetap	292 ms	~44	Sedang
Comunicación B15 de C.V.tetap	325 ms	~44	Sedang
Fibra A LA Casatetap	289 ms	~39	Rendah
Soluciones de Tecnologia Jah de Cvtetap	328 ms	~39	Rendah
ENI NETWORKS SAPI de CVtetap	488 ms	~35	Rendah
Doornet de cvtetap	307 ms	~35	Rendah
Javier Tamayo Garciatetap	344 ms	~35	Rendah
Digy Networks De C.V.tetap	359 ms	~31	Rendah

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

Proxy Meksiko 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

Mercado Libre MéxicoAmazon MexicoCoppelLiverpoolWalmart Mexico

Verifikasi & performa iklan

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

SERP lokal
Pengecekan kreatif
Halaman landing

FacebookInstagramTikTokYouTubeX (Twitter)

Perjalanan & intelijen harga

Tangkap tarif penerbangan dan hotel sebagaimana dilihat oleh pelanggan lokal.

Tarif berbasis geo
Pemantauan penawaran
Perbandingan tarif

Despegar MéxicoVolarisVivaAerobusAeroméxicoPrice Travel

Streaming & verifikasi geo

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

Pengecekan geo
Verifikasi katalog
Ketersediaan regional

ViXTUDNClaro VideoAzteca DeportesHBO Max Mexico

Iklan baris & listing lokal

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

Pemantauan listing
Pelacakan harga
Cakupan regional

Segundamano / VivanunciosMercado Libre AutosSeminuevosKavakSolo Autos

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

Developer API

Buat endpoint dengan cakupan Meksiko 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": "MX",
6  "city": "Benito Juarez",
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 Meksiko cocok untuk kasus penggunaan Anda? Tim kami menjawab pertanyaan nyata di Telegram, sepanjang waktu — sebelum dan sesudah Anda membeli.

Ngobrol di Telegram

Apakah proxy ini akan berfungsi untuk scraping Mercado Libre dan Coppel?

Itulah use case utamanya. Pool ini benar-benar residensial — karakteristik yang dicari sistem anti-bot marketplace lokal — sehingga IP ini lolos di tempat yang memblokir rentang datacenter. Hasilnya tetap bergantung pada fingerprint, header, dan ritme permintaan Anda, jadi padukan proxy dengan setup yang bersih dan zona waktu Meksiko yang sesuai (Central, atau Pacific/Mountain di barat laut).

Bisakah saya menargetkan kota tertentu seperti Mexico City atau Guadalajara?

Bisa, selama kedalaman pool memungkinkan — pilih kota saat Anda membuat daftar proxy. Tabel cakupan kami menampilkan konkurensi secara real-time untuk Mexico City, Guadalajara, Monterrey, Tijuana, Puebla, dan León, sehingga Anda bisa melihat kota mana yang memiliki rotasi terdalam sebelum memutuskan.

Apakah lokasi geografis IP-nya berada di dalam Meksiko?

Ya — pool ini terdeteksi berada di Meksiko dengan akurasi geo 100% terhadap Cloudflare dan di seluruh basis data geo independen pada benchmark terakhir kami, dengan exit node yang terkonfirmasi di Querétaro (QRO) dan Guadalajara (GDL). Akurasi geo yang tinggi adalah sinyal mendasar yang diandalkan oleh geo-gate Meksiko.

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

Bisa. Gunakan sesi sticky untuk mempertahankan exit IP Meksiko yang sama — durasi rata-rata sekitar 4,8 jam dan hingga 72 jam dalam pengukuran 3 hari kami. Untuk skala besar, lakukan rotasi setiap permintaan: exit IP berubah pada sekitar 96% permintaan, biasanya ke provider yang berbeda, bukan sekadar alamat tetangga.

Operator dan kota Meksiko mana saja yang tercakup?

Pool ini mencakup 113 jaringan Meksiko yang dipimpin oleh Telmex (Infinitum), Total Play, Megacable, Izzi, dan Alestra, di 30 wilayah dan 25 kota — mulai dari Mexico City dan Guadalajara hingga Monterrey, Tijuana, Puebla, León, dan Mexicali.