deepalgo-sovereign 0.2.3

Python SDK for the DeepAlgo Sovereign AI Regime API

DeepAlgo Sovereign SDK

Python client for the DeepAlgo Sovereign AI Regime API — institutional-grade regime classification, entry signal quality, session-stratified causal signal quality, and order-flow intelligence across FX, metals, indices, and commodities.

Installation

pip install deepalgo-sovereign

Quick Start

Get your key in 30 seconds — no GitHub account or card required.

Run the one-liner below in Python and check your inbox. That's it.

1. Get a free API key

from deepalgo_sovereign import DeepAlgoClient

DeepAlgoClient.enroll("[e-mail]")
# ✓ Prints: "Done — check your inbox for your free API key and quick-start instructions."
# Your key (e.g. da_free_xxxxxxxxxxxx) arrives by email within ~5 seconds.
# Check spam if you don't see it within 30 seconds.

No account creation, no GitHub, no card. If you already enrolled, calling enroll() again with the same address resends your existing key.

2. Check a regime

client = DeepAlgoClient(api_key="your_key_here")

regime = client.verify_regime("EUR_USD")
print(regime["is_favorable"])                        # True
print(regime["veto_reason"])                         # None  (or a veto code)
print(regime["metrics"]["regime"])                   # "MEAN_REVERTING"
print(regime["metrics"]["composite_confidence"])     # 0.7843
print(regime["metrics"]["vpin_at_time"])             # 0.31
print(regime["stability_score"])                     # "82.4%"

3. Check session signal quality

sq = client.get_session_signal_quality("EUR_USD")
print(sq["current_session"])     # "Asian"
print(sq["current_quality"])     # "SPURIOUS"
print(sq["current_multiplier"])  # 1.3

# EUR/USD in Asian hours: 99.6% of raw OFI signal is macro noise — not structural.
# USD/JPY in Asian hours: only 2.7% spurious — Tokyo institutional flow is genuine.

# All three sessions at a glance:
for session, data in sq["sessions"].items():
    print(f"{session}: {data['quality']} ({data['ic_reduction_pct']:+.1f}% IC change)")

4. Check entry signal quality

signal = client.get_entry_signal("EUR_USD")
print(signal)
# {
#   "entry_quality": "HIGH",
#   "current_ou_z": 1.42,
#   "ou_z_threshold": 0.75,
#   "recommended_delay_candles": 3,
#   "best_confirmation_signal": "rsi_divergence",
#   "calibrated": True
# }

if signal["entry_quality"] in ("HIGH", "MEDIUM"):
    regime = client.verify_regime("EUR_USD")
    if regime["is_favorable"]:
        # statistically sound entry — proceed
        pass

API Reference

DeepAlgoClient.enroll(email)

Class method. Registers for a free API key — no account creation required. Key is emailed within seconds.

DeepAlgoClient.enroll("[e-mail]")

client.verify_regime(asset, use_tlock=True)

Returns the full AI regime verdict for an instrument. Makes a live data fetch and runs the complete three-lock gauntlet — typically 2–8 seconds.

Production use: call check_lock() instead. It reads from a pre-computed Redis cache (updated every 60 s) and responds in under 100 ms. Use verify_regime() for strategy development, instrument evaluation, and anywhere you want full regime metadata.

Parameter	Type	Description
asset	str	OANDA instrument name, e.g. "EUR_USD", "XAU_USD"
use_tlock	bool	Enable/disable the third validation layer (default: True)

Response fields:

Field	Type	Description
is_favorable	bool	True if all three locks pass
veto_reason	str | None	Gate that blocked — REGIME_VETO, AI_PROXY_VETO, TRANSFORMER_VETO, ENTROPY_VETO, or None
stability_score	str	Lock 2 neural stability as a percentile, e.g. "82.4%"
divergence	str	Divergence label — "NONE" when regime is clean
metrics.regime	str	HMM state — "MEAN_REVERTING", "TRENDING", "HIGH_VOL"
metrics.composite_confidence	float	Combined confidence after all scalars applied
metrics.entropy	float	Shannon entropy of return distribution (0–1)
metrics.vpin_at_time	float	VPIN at scan time — > 0.80 = predatory flow
metrics.entropy_scalar	float	Confidence multiplier from entropy (1.0 = no reduction)
metrics.vpin_scalar	float	Confidence multiplier from order-flow toxicity
metrics.macro_z_score	float	Z-score vs macro driver spread
metrics.lock3_score	float	Transformer sequence validation score

client.check_lock(instrument, injected_data=None)

Binary EXECUTE / VETO decision. Use this in your order router immediately before placing a trade — reads pre-computed state from Redis so response is sub-millisecond on the server side.

decision = client.check_lock("EUR_USD")
if decision["authorized"]:
    place_order()

Field	Type	Description
authorized	bool	True = EXECUTE, False = BLOCK
decision	str	"EXECUTE" or "BLOCK"
forensics.failed_lock	str	Which lock blocked, or "NONE"
forensics.vpin_toxicity	float	Current VPIN — > 0.75 = toxic
forensics.pip_multiplier	int	Correct pip factor for this instrument
forensics.execution_intelligence.execution_benchmarks.vwap_deviation_bps	float	Distance from VWAP in basis points
forensics.execution_intelligence.capacity_metrics.suggested_max_clip_usd	float	Max recommended trade size

client.get_session_signal_quality(instrument)

Returns the DML-calibrated session signal quality for an instrument. Based on a Double Machine Learning study across 32 G10 FX, metals, and bond instruments — identifies whether order flow imbalance carries structural predictive content in the current session, or whether it is predominantly spurious macro co-movement.

Field	Type	Description
current_session	str	"Asian", "London", or "NewYork"
current_quality	str	"STRUCTURAL", "MIXED", "SPURIOUS", or "UNKNOWN"
current_multiplier	float	Lock 3 threshold multiplier currently active (1.0, 1.1, or 1.3)
sessions	dict	Per-session breakdown: quality, multiplier, ic_reduction_pct, structural_ic
last_calibrated	str	Date of most recent DML calibration run

Multiplier guide:

Quality	Multiplier	Meaning
STRUCTURAL	1.0×	OFI signal is genuine — standard threshold
MIXED	1.1×	Partial spurious component — threshold raised 10%
SPURIOUS	1.3×	Predominantly macro noise — threshold raised 30%

Research note: The Asian session finding is the sharpest result. EUR/USD in Asian hours (00–08 UTC) loses 99.6% of its apparent OFI signal to confounder exposure — it is almost entirely spurious. USD/JPY in the same session loses only 2.7% — Tokyo institutional participation is genuine. The difference is not in the signal. It is in who is trading. Source: DeepAlgo Sovereign Research, Bletchley Intelligence Ltd.

client.get_entry_signal(instrument)

Returns OU-calibrated entry timing quality. Derived from 60-day IC analysis across 76 instruments — identifies whether the current moment is a statistically optimal entry point, not just whether the regime is right.

Field	Type	Description
entry_quality	str	HIGH, MEDIUM, LOW, or NO_DATA
current_ou_z	float	Live OU z-score — deviation from equilibrium in σ
ou_z_threshold	float	Calibrated threshold from IC analysis
recommended_delay_candles	int	Optimal M5 candle wait after signal touch
best_confirmation_signal	str	Highest-IC confirmation signal at optimal lag
calibrated	bool	False if instrument has no calibration data yet

client.validate_sequence(asset, candles)

Runs the full validation stack using 60 M5 candles of OHLCV data.

result = client.validate_sequence("EUR_USD", candles=[...])  # list of 60 OHLCV dicts
# {"is_authorized": True, "verdict": "AUTHORIZED"}

Supported Instruments

The API covers 76+ instruments across four asset classes:

• FX: EUR_USD, GBP_USD, USD_JPY, EUR_JPY, GBP_JPY, AUD_USD, and 30+ major/minor/exotic pairs
• Metals: XAU_USD, XAG_USD, XAU_EUR, XAU_JPY, XAU_AUD
• Indices: SPX500_USD, NAS100_USD, US30_USD, EU50_EUR, DE30_EUR, JP225_USD
• Commodities: NATGAS_USD, SUGAR_USD, WHEAT_USD, SOYBN_USD, CORN_USD

Tier Access

Feature	Free	Professional	Institutional
Instruments	4	15	All 76+
API calls / day	50	Unlimited	Unlimited
verify_regime()	✓	✓	✓
get_entry_signal()	—	✓	✓
get_session_signal_quality()	—	✓	✓
OU-calibrated entry timing	—	✓	✓
DML session quality (32 instruments)	—	✓	✓
Institutional order-flow VPIN	—	—	✓
Cross-client Network Intelligence	—	—	✓

Upgrade at gateway.deepalgo.co.uk

Health Check

import requests
r = requests.get("https://api.deepalgo.co.uk/health")
print(r.json())

Not using Python? MetaTrader (MQL5) EA

Trading on MetaTrader 5 instead of a Python stack? mql5/DeepAlgoSovereignGate.mq5 wraps this same API in a free, no-code Expert Advisor — drag it onto a chart, paste your API key, and it publishes the same APPROVE/VETO verdict (regime, veto reason, VPIN, confidence) on the chart and via a GlobalVariable/Common file that any other EA on your terminal can read.

Support

• Documentation: gateway.deepalgo.co.uk
• Email: [e-mail]

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DeepAlgo Sovereign SDK v0.2.2 — MIT License