--- title: Compute on Your Own Data — Compute API description: POST your own OHLCV klines to the engine and get back RSI / MACD / SMC and 60+ other indicators. For backtest, CSV uploads, and custom data sources. --- # Compute on Your Own Data `POST /api/indicators/compute` lets you run the engine's 60+ indicator pipelines **against klines you supply yourself** — independent of the engine's in-memory cache, not bound to any venue or symbol. Good for: - **Backtest**: run indicators over OHLCV history pulled from your DB / CSV - **Custom data sources**: counterparty exchange, aggregated contracts, your own tick resamples - **Offline analysis**: validate indicator values for a specific window without being constrained by what the engine has cached Not for: - **Live data** — use [`POST /api/indicators`](#related) for lower latency, it reads from in-memory store - **Multi-timeframe (MTF) indicators** like SMC's `fvg_timeframe` — those need server-side prefetch of multiple timeframes; only the store-backed path supports them --- ## 30-second quickstart ```bash curl -X POST 'https://api.mobiusquant.ai/api/indicators/compute' \ -H 'authorization: Bearer mq_xxx' \ -H 'content-type: application/json' \ -d '{ "klines": [ [1735689600000, 95000.0, 95500.0, 94800.0, 95200.0, 1234.5], [1735693200000, 95200.0, 95800.0, 95100.0, 95650.0, 1500.2] ], "interval": "1h", "calc": [{"name": "rsi", "params": {"period": 14}}] }' ``` Returns: ```jsonc { "count": 2, "interval": "1h", "klines": [[1735689600000, 95000.0, ...], ...], // echoed "indicators": { "rsi:period=14": { "columns": ["open_time", "rsi"], "data": [[1735689600000, null], [1735693200000, null]], "explain": { /* knowledge: summary_focus / signals / caveats */ } } } } ``` > RSI returns `null` for the first 14 bars — this is **normal**. All cumulative indicators need warmup. See [Limits](#limits) below. --- ## Python example ```python import requests import pandas as pd # Load historical OHLCV from your own data source df = pd.read_csv('btc_1h_history.csv') # columns: open_time(ms), open, high, low, close, volume klines = df[['open_time', 'open', 'high', 'low', 'close', 'volume']].values.tolist() resp = requests.post( 'https://api.mobiusquant.ai/api/indicators/compute', headers={'Authorization': 'Bearer mq_xxx'}, json={ 'klines': klines, 'interval': '1h', 'calc': [ {'name': 'ema', 'params': {'period': 20}, 'id': 'ema20'}, {'name': 'ema', 'params': {'period': 200}, 'id': 'ema200'}, {'name': 'rsi', 'params': {'period': 14}}, ], }, ) result = resp.json() print(result['indicators']['ema20']['data'][-1]) # latest EMA20 value print(result['indicators']['rsi:period=14']['data'][-1]) ``` --- ## SMC and other "composite" indicators work too Indicators like SMC (Smart Money Concepts) that produce non-numeric output also return per-bar columns + an `objects` sidecar: ```bash curl -X POST 'https://api.mobiusquant.ai/api/indicators/compute?explain=false' \ -H 'content-type: application/json' \ -d '{ "klines": [/* ≥500 historical bars */], "calc": [{"id": "smc", "name": "smc", "params": {"show_swing_points": true, "show_premium_discount_zones": true}}] }' ``` The response includes `indicators.smc.objects` with structured shapes — `swing_structures`, `order_blocks_swing`, `fair_value_gaps`, `premium_zone`, etc. Feed them straight into a chart renderer or an LLM. See [SMC indicator page](/indicators/smc). --- ## Request schema | Field | Type | Required | Description | |---|---|---|---| | `klines` | array | ✓ | OHLCV bars; each row auto-detected as either list or object (see below) | | `calc` | array | ✓ | Indicators to compute, each `{name, params, id?}` — same shape as [`/api/indicators`](https://api.mobiusquant.ai/docs#/indicators/post_indicators_api_indicators_post) | | `interval` | string | ✗ | Metadata only, echoed back; some MTF indicators ignore it | | `echo_klines` | bool | ✗ | Default `true` — echoes input klines; set `false` to shrink the response | Two `klines` row formats (auto-detected): ```jsonc // Compact (Binance nested-list style): [open_time_ms, open, high, low, close, volume, quote_volume?] [1735689600000, 95000.0, 95500.0, 94800.0, 95200.0, 1234.5, 117526200.0] // Object (more explicit) { "open_time": 1735689600000, "open": 95000.0, "high": 95500.0, "low": 94800.0, "close": 95200.0, "volume": 1234.5, "quote_volume": 117526200.0 // optional, used by some indicators (VWAP / CVD); defaults to 0 } ``` --- ## Response schema | Field | Type | Description | |---|---|---| | `count` | int | Number of klines processed | | `interval` | string | Echoes request's `interval` (only when provided) | | `klines` | array | Echo of input klines (omitted when `echo_klines=false`) | | `indicators` | object | key = `id` or auto-generated `name:p1=v1,...`, value = single indicator's columns/data/objects/explain | Each `indicators.` has the same shape as in [`POST /api/indicators`](https://api.mobiusquant.ai/agents.md): ```jsonc { "columns": ["open_time", "rsi"], "data": [[1735689600000, null], [1735693200000, 67.4], ...], "objects": { /* present only for SMC and other non-numeric indicators */ }, "explain": { /* knowledge: only when ?explain=true */ } } ``` --- ## Limits | Limit | Value | On violation | |---|---|---| | Kline count | ≤ **2000** | `413` | | `open_time` | strictly **monotonically increasing in ms** | `400` | | OHLCV | must be finite (no NaN / inf) | `400` | | `calc` list | non-empty, all `name` in [registry](https://api.mobiusquant.ai/api/indicators/registry) | `400` | | `calc` invalid params | Pydantic / signature mismatch | `422` | ### Important: no warmup buffer `/api/indicators` internally adds 1000 bars of warmup to feed accumulating indicators (EMA / RSI / ATR). **`/api/indicators/compute` does not** — it uses exactly the klines you supply. So make sure you include enough history: | Indicator / usage | Minimum bars | |---|---| | RSI(14) to stabilize | ≥ 50 | | EMA(200) / ATR(200) to stabilize | ≥ 200 | | Bollinger / Keltner / Donchian (default params) | ≥ 30 | | SMC internal structure + FVG | ≥ 50 | | SMC swing structure / OB / Strong-Weak / P/D zones | ≥ 100 (default swing_size=50, plus buffer) | | SMC complete + EQH/EQL stable | ≥ 200 (ATR threshold converges) | | **Production-grade analysis** | **500+** | The first N bars returning `null` is normal — discard them and use the stable tail. --- ## Auth & rate limits Same as `/api/indicators`: - No `Authorization` header → anonymous IP bucket (low quota) - Valid `Bearer mq_xxx` → token bucket (higher quota) - Don't have a token yet? [Apply for one](https://www.mobiusquant.ai/zh/apply-token) — it's free. --- ## Error codes | Code | Meaning | What to do | |---|---|---| | `400` | Validation failed (non-monotonic, NaN, unknown indicator, too few columns) | Read `detail`, fix the request | | `401` | Authorization header present but token invalid | [Re-apply](https://www.mobiusquant.ai/zh/apply-token) | | `413` | `klines` exceeds 2000 | Batch, or shorten the window | | `422` | Pydantic validation (missing field, wrong type, unknown field) | Check `detail.loc` | | `429` | Rate limited | Honor `Retry-After`; token bucket has higher quota | | `500` | Indicator computation crashed (indicator bug) | Report with the indicator name in `detail` | --- ## Related - [`POST /api/indicators`](https://api.mobiusquant.ai/docs#/indicators/post_indicators_api_indicators_post) — Reads klines from engine cache and computes indicators (faster, but limited to subscribed venues/symbols) - [`GET /api/indicators/registry`](https://api.mobiusquant.ai/api/indicators/registry) — All 60+ indicators with parameter signatures - [SMC indicator page](/indicators/smc) — Details of the SMC `objects` sidecar - [AI Agent Manual](/agents) — Engine integration guide for LLMs - [Skill Runtime Lookup](/lookup-guide) — Endpoint decision tree for Skill integration