Wiring Doex Pro into a market-data and execution pipeline

Quotes move, the order book updates tens of times a second, and a futures position can reprice on every tick — that is the data inside Doex Pro that a daily CSV never captures. So an integration that earns its keep starts on the streaming side: WebSocket ingestion for ticks and depth, signed REST snapshots for the slower-moving surfaces (balances, fills, fee tiers), and a normalized account view that hides the wallet split behind one schema. The rest of this brief is what that build actually contains for Doex Pro specifically, and the route the studio takes to get there.

What lives behind the Doex Pro app

The app's marketing names a small set of capabilities — buy, sell, manage, monitor — but the backend keeps a wider record per user. The table below maps the practical data domains an integrator would care about, with the granularity the surface typically exposes on exchange-mobile pairs of this shape.

Three workable routes to the data

The studio looks at each route by what it actually reaches and how it holds up under change. For a crypto exchange the practical short list is three.

Route 1 — Authorized account access using customer API keys

The most direct path. The customer creates an API key inside Doex Pro with the scopes the build needs (read-only for analytics, read-plus-trade for execution), signs requests with HMAC, and the client speaks REST plus WebSocket exactly as the exchange backend expects. Reachable: everything the account itself can see — balances, positions, order placement, history, the streaming book. Effort: low to medium, mostly in the protocol analysis pass to confirm the signing chain and the streaming subscription model. Durability: high while keys are valid; key rotation is part of operations, not engineering. Onboarding: the studio walks the customer through key creation, scope selection, and IP allowlisting during kickoff.

Route 2 — Authorized protocol analysis of the mobile pairing

Where the customer wants a feed that mirrors what their own app session sees — sometimes broader than the public surface — the studio runs a documented protocol analysis on a consenting account. That means an authorized capture of traffic between the customer's instance of the app and the Doex Pro backend, written up as an OpenAPI-shaped report covering hosts, auth chain, request envelopes, and pagination. Reachable: a richer set of surfaces than key-scoped REST sometimes permits. Effort: medium; the work is the auth chain and replay-resistance, not the endpoints themselves. Durability: medium — app releases can change envelope shapes, so the captured surfaces get re-checked on a cadence rather than once. Used only with written consent from the account holder, on accounts the customer controls.

Route 3 — Native export plus reconciliation

For history-only needs (taxes, year-end audit), the in-app export plus statement download is sometimes enough. Effort: lowest. Reachable: only what the operator chooses to expose — usually a CSV of fills and statements; no live state, no positions stream. Durability: high but coarse. Useful as a reconciliation source against the other two routes, less often the spine of a live integration.

The studio's call for most Doex Pro integrations is route 1 as the working surface, route 3 as a checksum against history, and route 2 reserved for the cases where the app session genuinely sees something the key-scoped surface does not.

What the build hands over

The deliverable is biased toward code that runs, not paperwork. In order:

• Runnable SDK source — a Python package (Node.js and Go on request) covering the signed REST client, the WebSocket client with heartbeat and reconnect, request-budget management, and normalized models for balances, positions, orders, and fills.
• Stateful ingestion worker — long-running process that owns the WebSocket connection, persists ticks and depth events with idempotency, resyncs on sequence gaps, and exposes its own health endpoint to your monitoring.
• Webhook adapter — for downstream systems that want push instead of pull, a thin service that fans out trade and position events into your own webhook contract (signed payloads, retry, deduplication).
• Automated test harness — replayable VCR-style fixtures plus a small live-smoke suite that exercises the signed-request loop end-to-end against a customer's account.
• Batch-vs-realtime sync design — a one-page operational guide picking which surfaces stream and which are pulled, with cadences chosen to fit the downstream consumer.
• OpenAPI specification and auth-flow report — written up as part of the engagement, useful for handing the build to another team. Secondary to the running code.
• Compliance and retention notes — short, specific to the customer's deployment and jurisdiction. NDA is standard.

A signed-request walkthrough

Illustrative Python sketch for the two most common surfaces on a Doex-shaped backend: a signed REST balance read and a WebSocket subscription for trades. The exact host, parameter names, and signing chain are pinned during the build against the customer's authorized account.

import hmac, hashlib, json, os, time, requests, websocket

BASE   = "https://api.doex.com"          # confirmed against the running app
KEY    = os.environ["DOEX_KEY"]
SECRET = os.environ["DOEX_SECRET"].encode()

def signed_get(path, params=None):
    params = dict(params or {})
    params["timestamp"] = int(time.time() * 1000)
    qs  = "&".join(f"{k}={v}" for k, v in sorted(params.items()))
    sig = hmac.new(SECRET, qs.encode(), hashlib.sha256).hexdigest()
    r = requests.get(
        f"{BASE}{path}?{qs}&signature={sig}",
        headers={"X-DOEX-APIKEY": KEY},
        timeout=8,
    )
    r.raise_for_status()
    return r.json()

# spot wallet balances, normalized into one shape
balances = [
    {"asset": b["asset"], "free": float(b["free"]), "locked": float(b["locked"])}
    for b in signed_get("/v1/account/balances")["assets"]
    if float(b["free"]) + float(b["locked"]) > 0
]

# open futures positions
positions = signed_get("/v1/futures/positions")

# live trade stream for BTC/USDT
def on_message(ws, raw):
    ev = json.loads(raw)
    if ev.get("e") == "trade":
        record_tick(ev["s"], ev["p"], ev["q"], ev["T"])

ws = websocket.WebSocketApp(
    "wss://stream.doex.com/ws/btcusdt@trade",
    on_message=on_message,
)
ws.run_forever(ping_interval=20, ping_timeout=10)

Notes from the walkthrough that matter at integration time: timestamp skew is the most common cause of a 400 on signed routes (the build keeps a clock-drift check in the client); the WebSocket should be on its own connection from the REST client so a 429 on REST does not pull the streaming socket down with it; and the trade-message shape is the place where exchange-specific quirks tend to live, so the normalized models are kept thin and explicit.

Engineering notes from doing this work

Three things the studio plans for when the target is a crypto exchange of this shape — none of them are blockers, all of them are things the build handles so the customer does not have to.

• Wallet partition is explicit, not implicit. Spot, margin, and futures live in separate ledgers on a Doex-shaped backend. The SDK keeps them addressable as three wallets or one aggregate, with a clear projection function — never a silent merge that hides where the funds actually sit.
• Order books need sequence-number discipline. Streaming depth comes as diffs; without a snapshot+resync protocol, a missed message corrupts the local book and you only find out when an aggressive order surprises you. The client tracks the last update id, requests a snapshot on reconnect, and replays buffered diffs forward.
• Precision is per-pair, not per-exchange. Tick size and step size differ across symbols; the spec captures those constants so quote rounding and order quantization happen at the client edge and the wire-format is never the place where rounding error gets introduced.
• Time and key rotation are operational, not architectural. Signed-request systems live or die on clock skew and key hygiene. The deliverable comes with a small ops runbook covering NTP expectations, key rotation steps, and the alerting we recommend for both.

Keeping the feed honest

Once a feed is live, the failure modes shift. The studio designs for them up front rather than chasing them after the fact:

• Heartbeat tracking on the WebSocket with a hard reconnect threshold — silent socket death is a known failure mode on retail-facing exchange streams.
• Idempotent writes downstream — every tick and fill carries a stable id, so a replay during reconnect cannot double-count.
• Rate-limit budgeting on REST — the client knows its share of the per-minute and per-route budget and queues opportunistic polls behind the must-have ones.
• Drift detection between the streaming view and a periodic REST snapshot — when the two diverge by more than a tolerance, the ingestion worker raises and resyncs rather than letting the mismatch coast.

Custody and rules of the road

Doex Pro is a centralized crypto exchange, not a regulated AIS or open-banking participant — the dependable basis for integration is the customer's own authorization over their account, not a regulator-defined consent flow. In practice that means the integration is run on accounts the customer holds and operates, with API keys the customer issues at scopes the customer chooses, under an NDA where the data is sensitive.

Anti-money-laundering posture sits with the operator. DOEX INC describes itself on its product pages as carrying MSB filings with US FinCEN and Canadian FinTRAC; the studio does not assert specific registration numbers here, and the build does not depend on regulator-defined data-portability rules that apply to banks and card issuers. Where the customer's own jurisdiction adds obligations — GDPR for an EU operator, state-level privacy law in the US, sector rules for a regulated investment manager — those are reflected in retention windows and access logs in the deliverable, not assumed away.

Sample integration scenarios

• Multi-exchange portfolio dashboard. Pull Doex Pro spot and futures into a unified balance view, refresh on a 5-second cadence, drive a single PnL number across exchanges.
• Tax and trade-journal export. Paginate full order and fill history into a normalized schema, cross-check against the in-app CSV export, hand off to an accounting tool.
• Risk monitor with margin alerts. Subscribe to futures position updates, run a liquidation-distance calculation client-side, fire a webhook to an on-call channel when distance drops below a threshold.
• Programmatic order routing. Place and cancel orders under a key-scoped trading permission, with a kill-switch hook that the operations team can trip without touching the SDK.

Sources behind this brief

The brief was built from the app's public listings, the operator's own product and help-centre pages, and a market scan of comparable exchange-mobile pairs. Specific endpoint names, host, and signing chain are confirmed against the customer's authorized account during the build, not asserted as fact here.

Citations:

• Doex Pro on Google Play (package com.doexinc.crypto)
• Doex Pro on the App Store
• DOEX exchange product page (operator)
• FinCEN MSB Registrant Search

OpenFinance Lab · integration desk review, May 2026.

Other exchange apps in the same shape

Real comparators a buyer evaluating Doex Pro tends to also have on the integration list. Plain context, not ranking.

• Coinbase — large US-regulated exchange; holds balances, orders, transfers, staking positions. Comparable normalization target for a unified account view.
• Kraken — spot plus futures with mature streaming surfaces; useful when an integration needs to span both retail and pro-tier shapes.
• MEXC — broad listing depth across spot and futures; the long tail of pairs makes symbol-precision handling especially load-bearing.
• Bitget — copy-trading-first surface; relevant when the integration needs lead-trader attribution and mirror ratios alongside raw positions.
• PrimeXBT — fast-market focus with crypto and traditional pairs; integration tends to lean on the streaming side for both.
• Crypto.com — exchange plus app-of-record for staking and savings; the integration question is usually which wallet surface counts.
• Bybit — derivatives-leaning with active WebSocket products; sequence-number discipline carries over almost line for line.
• Binance — the reference shape most other exchange APIs cross-pollinate from; familiar conventions help when normalizing across several venues.

Questions an integrator usually asks

Do you push trade and order-book updates over WebSocket, or poll REST for portfolio state?

Both, where each surface earns its place. Tick data, depth updates, and execution callbacks come over the streaming socket. Wallet balances, fee tiers, and historical fills are pulled with signed REST calls on a cadence that fits the downstream consumer. The build keeps the two transports on separate connections so a REST budget never starves the trading stream.

How do you keep an order book in sync after a WebSocket reconnect?

We treat sequence numbers as load-bearing. The client tracks the last update id, requests a fresh REST snapshot on reconnect, and replays buffered diffs from the snapshot's sequence forward. If a gap is detected mid-session, the book is invalidated and resynced rather than silently corrupted.

Can spot, margin, and futures positions land in one normalized account view?

Yes. The app exposes the three wallet partitions separately on the backend, which is how the exchange tracks them internally. The deliverable projects them into a single account aggregate with consistent symbol codes, precision per pair, and a position-vs-balance distinction so downstream PnL math is unambiguous.

What does the build look like when we want a continuous feed instead of a one-shot export?

A continuous feed gets the SDK plus a stateful ingestion worker: WebSocket client with heartbeat and back-off, REST poller for the surfaces that aren't streamed, idempotent writes into your store, and a small ops runbook covering key rotation and rate-limit alarms. A one-shot export drops the worker and ships a CLI that pages through history once.

A Doex Pro client of the shape described here ships from $300 as runnable source — the SDK, the ingestion worker, the tests, and the spec — paid only after the build lands and you are satisfied with what you receive. If you would rather not host it yourself, the same surfaces are available as hosted endpoints with no upfront fee, billed per call. A first build runs one to two weeks from kickoff. Send us the account scope you want covered and the cadence you want it at: Start a Doex Pro build.