malkhut: multi-exchange asset universe + schema docs
ExchangeProfile: standardized exchange metadata (fees, latency, capabilities). 3 pre-defined exchanges: Binance, BingX, Bybit. AssetProfile.exchanges: tuple[str] — which venues trade each asset. New query functions: get_assets_on_exchange, get_common_assets, get_exchange_for_asset, get_exchange, list_exchanges. _DATA_STORAGE_SCHEMA_FORMATS.md: comprehensive reference for agent consumption — data model, storage format, query interfaces, data flow diagram, enum reference, import patterns for BLUE/VIOLET/UV integration. README updated: exchange registry section, package structure, subsystems table.
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@@ -136,7 +136,7 @@ MALKHUT/
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│ │ ├── dsl.py # Strategy DSL v2 (40+ primitives, 40+ sensors)
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│ │ ├── generator.py # Genetic programming strategy evolution
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│ │ ├── selector.py # Regime → strategy mapping + performance matrix
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│ │ ├── asset_classification.py # Multi-label invariant asset taxonomy
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│ │ ├── asset_classification.py # Multi-label taxonomy + exchange registry (system-wide)
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│ │ ├── asset_behavior.py # 10-dimension behavior DSL, research-validated
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│ │ ├── asset_compiler.py # Auto-fetch from Binance/BingX, compile profiles
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│ │ ├── parallel_eval.py # ProcessPoolExecutor episode runner, 9x speedup
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@@ -422,7 +422,7 @@ simple doctrinal tick-exits (C11) ship first via T19 step 3; MALKHUT supersedes
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| **Strategy DSL v2** | `training/dsl.py` | 69 | 40+ primitives, 40+ sensors, 16 builtins |
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| **Strategy Generator** | `training/generator.py` | 20 | Genetic programming: crossover, mutation, tournament |
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| **Strategy Selector** | `training/selector.py` | 24 | Regime → strategy mapping, performance matrix |
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| **Asset Classification** | `training/asset_classification.py` | 190 | Multi-label invariant taxonomy, 13 assets, cross-dimensional consistency |
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| **Asset Classification** | `training/asset_classification.py` | 190 | Multi-label taxonomy + exchange registry, 13 assets, system-wide store |
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| **Asset Behavior DSL** | `training/asset_behavior.py` | (in classification) | 10 orthogonal dimensions, 3 templates, 13 behaviors, research-validated |
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| **Asset Compiler** | `training/asset_compiler.py` | (new) | Auto-fetch from Binance/BingX API, compile profiles, rate-limited |
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| **Cognition Pipeline** | `training/cognition.py` | 29 | Rate-limited, 8 sources, dedup, perm-run |
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@@ -690,6 +690,63 @@ btc.sector # Sector.CURRENCY
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btc.token_role # TokenRole.STORE_OF_VALUE
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```
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### Exchange Registry (Multi-Exchange Asset Universe)
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MALKHUT serves as the **system-wide asset universe store** for BLUE, VIOLET, UV, and all
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downstream systems. Each asset knows which exchanges trade it; each exchange has a
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standardized profile.
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#### ExchangeProfile
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| Field | Type | Purpose |
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|-------|------|---------|
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| `exchange_id` | str | Canonical key: `"binance"`, `"bingx"`, `"bybit"` |
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| `display_name` | str | Human-readable name |
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| `has_spot` | bool | Spot trading available |
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| `has_perps` | bool | Perpetual futures available |
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| `has_options` | bool | Options available |
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| `api_base_url` | str | REST API root URL |
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| `ws_base_url` | str | WebSocket root URL |
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| `default_taker_fee_bps` | float | Default taker fee |
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| `default_maker_fee_bps` | float | Default maker fee |
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| `typical_latency_ms` | float | Typical API latency |
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#### Pre-defined Exchanges
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| Exchange | Spot | Perps | Options | Taker Fee | Latency |
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|----------|------|-------|---------|-----------|---------|
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| **Binance** | ✓ | ✓ | ✓ | 0.4 bps | 40 ms |
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| **BingX** | ✓ | ✓ | ✗ | 0.5 bps | 100 ms |
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| **Bybit** | ✓ | ✓ | ✓ | 0.06 bps | 50 ms |
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#### Exchange-Asset Mapping
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Each `AssetProfile` carries an `exchanges: tuple[str, ...]` field listing which venues
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trade the asset. Default: `("binance",)`. Other systems (BLUE/VIOLET/UV) import their
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asset universes into this store.
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```python
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from malkhut.training.asset_classification import *
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# Which exchanges trade BTC?
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btc = get_asset_profile("BTCUSDT")
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print(btc.exchanges) # ('binance',)
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# All assets on Binance
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binance_assets = get_assets_on_exchange("binance")
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# Assets traded on BOTH Binance and BingX
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common = get_common_assets("binance", "bingx")
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# Which exchanges trade a given asset?
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venues = get_exchange_for_asset("ETHUSDT")
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# Exchange metadata
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ex = get_exchange("binance")
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print(ex.default_taker_fee_bps) # 0.4
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print(ex.typical_latency_ms) # 40
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```
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### Asset Behavior DSL (10-Dimension Research-Validated Model)
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The Asset Behavior DSL decomposes each asset's **trading behavior** into 10 orthogonal
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300
MALKHUT/malkhut/training/_DATA_STORAGE_SCHEMA_FORMATS.md
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300
MALKHUT/malkhut/training/_DATA_STORAGE_SCHEMA_FORMATS.md
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# MALKHUT Asset Store — Data Storage Schema & Formats
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**System-wide asset universe.** Used by BLUE, VIOLET, UV, and all downstream systems.
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This document defines the data model, storage formats, and query interfaces for the
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MALKHUT asset classification and exchange registry. Other agents use this to:
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- Understand what data is stored and where
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- Import assets from other systems (e.g., BLUE's Binance universe)
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- Query the asset universe by any dimension
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- Extend the store with new exchanges or assets
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## Quick Reference
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```
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asset_classification.py → AssetProfile, ExchangeProfile, query functions
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asset_behavior.py → AssetBehavior (10-dimension behavior model)
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asset_compiler.py → Auto-fetch from Binance/BingX API
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parallel_eval.py → Parallel episode evaluation
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cma_trainer.py → ScenarioFactory (uses both stores)
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```
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---
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## 1. ExchangeProfile — Exchange Metadata
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**Frozen dataclass. One entry per exchange.**
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```python
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@dataclass(frozen=True, slots=True)
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class ExchangeProfile:
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exchange_id: str # "binance", "bingx", "bybit"
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display_name: str # "Binance"
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has_spot: bool
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has_perps: bool
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has_options: bool
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api_base_url: str # REST root
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ws_base_url: str # WebSocket root ("" if N/A)
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default_taker_fee_bps: float
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default_maker_fee_bps: float
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typical_latency_ms: float
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```
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**Storage:** `EXCHANGE_PROFILES: Dict[str, ExchangeProfile]` in `asset_classification.py`.
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**Pre-defined:** `binance`, `bingx`, `bybit`.
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**How to add a new exchange:**
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```python
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from malkhut.training.asset_classification import EXCHANGE_PROFILES, ExchangeProfile
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EXCHANGE_PROFILES["okx"] = ExchangeProfile(
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exchange_id="okx", display_name="OKX",
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has_spot=True, has_perps=True, has_options=True,
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api_base_url="https://www.okx.com",
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ws_base_url="wss://ws.okx.com:8443/ws/v5/public",
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default_taker_fee_bps=0.1, default_maker_fee_bps=-0.02,
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typical_latency_ms=60,
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)
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```
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---
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## 2. AssetProfile — Per-Asset Classification
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**Frozen dataclass. One entry per symbol. Multi-label on Sector and TokenRole.**
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```python
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@dataclass(frozen=True, slots=True)
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class AssetProfile:
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# Identity
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symbol: str # "BTCUSDT"
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# Fundamental (intrinsic, never change)
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sectors: tuple[Sector, ...] # ("CURRENCY",)
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token_roles: tuple[TokenRole, ...] # ("STORE_OF_VALUE",)
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supply_model: SupplyModel # FIXED_CAP | DISINFLATIONARY | INFLATIONARY | BURN_MECHANISM
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consensus: ConsensusFamily # POW | POS | DPOS
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smart_contracts: SmartContractCapability # FULL | PARTIAL | NONE
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# Technical (invariant market-structure)
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market_cap_tier: MarketCapTier # MEGA | LARGE | MID | SMALL | MICRO
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volatility_profile: VolatilityProfile # LOW | MEDIUM | HIGH | EXTREME
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liquidity_profile: LiquidityProfile # DEEP | NORMAL | THIN | ILLIQUID
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derivative_access: DerivativeAccess # PERPS_AND_OPTIONS | PERPS_ONLY | NONE
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# Execution parameters (exchange-set)
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tick_size: float
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lot_size: float
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price_decimals: int
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maker_fee_bps: float
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taker_fee_bps: float
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# Order-book fingerprint (long-run averages)
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typical_spread_bps: float
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typical_depth_usd: float
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typical_daily_volume_usd: float
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# Structural flags
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has_funding: bool = False
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has_options: bool = False
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# Exchange membership
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exchanges: tuple[str, ...] = ("binance",) # which venues trade this
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```
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**Storage:** `ASSET_PROFILES: Dict[str, AssetProfile]` in `asset_classification.py`.
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**Multi-label rules:**
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- `sectors` and `token_roles` are **tuples** (ordered). First element = primary label.
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- `supply_model`, `consensus`, `smart_contracts` = **single enum** (inherently singular).
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- `exchanges` = **tuple of strings** (which venues list the asset).
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**Query functions:**
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| Function | Returns |
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|----------|---------|
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| `get_asset_profile(symbol)` | Single profile or None |
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| `list_assets()` | All symbols |
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| `get_assets_by_sector(sector)` | Assets in ANY of the queried sector |
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| `get_assets_by_token_role(role)` | Assets with ANY of the queried role |
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| `get_assets_by_supply(model)` | Assets with given supply model |
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| `get_assets_by_consensus(family)` | Assets with given consensus |
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| `get_assets_by_market_cap(tier)` | Assets in market cap band |
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| `get_assets_by_volatility(vol)` | Assets in vol band |
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| `get_assets_by_liquidity(liq)` | Assets in liquidity band |
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| `get_assets_by_derivatives(access)` | Assets with given derivative access |
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| `get_gas_tokens()` | All gas tokens |
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| `get_pov_assets()` | PoW assets (forced selling) |
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| `get_shortable_assets()` | All shortable assets |
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| `get_multi_sector_assets()` | Assets in >1 sector |
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| `get_multi_role_assets()` | Assets with >1 role |
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| `get_assets_on_exchange(exchange_id)` | Assets traded on given exchange |
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| `get_common_assets(ex_a, ex_b)` | Assets on BOTH exchanges |
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| `get_exchange_for_asset(symbol)` | Which exchanges trade this asset |
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---
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## 3. AssetBehavior — Per-Asset Behavior Model
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**Frozen dataclass. 10 orthogonal dimensions. Research-validated.**
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```python
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@dataclass(frozen=True, slots=True)
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class AssetBehavior:
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symbol: str
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depth: DepthProfile # book shape: amplitude, alpha, fragility
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spread: SpreadProfile # normal spread, stress multiplier
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flow: FlowProfile # order rate, sizes, cancel ratio
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vol: VolatilityProfile # ann vol, GARCH params, half-life
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intraday: IntradayProfile # peak/trough hours, ratio
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weekend: WeekendProfile # vol/volume/spread multipliers
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correlation: CorrelationProfile # ETH beta, BTC corr (normal vs crash)
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market_maker: MarketMakerProfile # inventory, pull speed, margins
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liquidation: LiquidationProfile # OI/MCap, trigger %, cascade
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funding: FundingProfile # mean/std, positive %, basis
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retail: RetailProfile # retail ratio, inst gap
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bingx: BingxProfile # BingX-specific multiplier, latency
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template_name: str = "" # which template this came from
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reference_price: float = 0.0 # last known mid-price
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```
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**Storage:** `ASSET_BEHAVIORS: Dict[str, AssetBehavior]` in `asset_behavior.py`.
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**3 templates:** `institutional_blue_chip`, `mid_cap_l1`, `retail_meme`.
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**Query functions:** same pattern as AssetProfile — `get_behavior()`, `get_behaviors_by_template()`, etc.
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---
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## 4. Auto-Compilation (AssetCompiler)
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**Auto-fetches from Binance/BingX public API, computes profiles.**
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```python
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compiler = AssetCompiler()
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result = compiler.compile("XRPUSDT") # ~6s, rate-limited
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compiler.register(result) # adds to ASSET_PROFILES + ASSET_BEHAVIORS
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```
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**What it auto-fetches:**
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| Endpoint | Computes |
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|----------|----------|
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| `/api/v3/ticker/24hr` | Price reference, daily volume |
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| `/api/v3/depth?limit=100` | Spread, depth amplitude, decay α |
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| `/api/v3/klines?interval=1h&limit=168` | Annualized vol, order flow stats |
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| `/api/v3/exchangeInfo` | Tick size, lot size, price decimals |
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| `/fapi/v1/fundingRate` | Funding rate mean/std |
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| `/fapi/v1/openInterest` | OI/MCap ratio |
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**Known classifications:** 28 pre-defined assets. Unknowns get heuristic defaults.
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---
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## 5. Exchange-Asset Mapping Pattern
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The mapping follows a many-to-many relationship:
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```
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Asset (BTCUSDT) ──exchanges──> (binance, bingx, bybit)
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Exchange (binance) ──assets──> (BTCUSDT, ETHUSDT, SOLUSDT, ...)
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```
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**In code:** `AssetProfile.exchanges` is a tuple of `exchange_id` strings.
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**For querying:** `get_assets_on_exchange(id)`, `get_common_assets(a, b)`.
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**When importing from BLUE/VIOLET/UV:**
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1. Get the full symbol list from the source system
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2. For each symbol, check if it already exists in `ASSET_PROFILES`
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- If yes: add the new exchange_id to the `exchanges` tuple
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- If no: create a minimal profile with the exchange's default fees
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3. The `_profile()` helper and `AssetProfile.from_template()` handle creation
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---
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## 6. Data Flow Diagram
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```
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┌──────────────────┐ ┌──────────────────┐
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│ Binance API │ │ BingX API │
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│ (public, R/O) │ │ (public, R/O) │
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└────────┬─────────┘ └────────┬─────────┘
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│ │
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▼ ▼
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┌────────────────────────────────────────────┐
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│ AssetCompiler │
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│ auto-fetch → compute → CompileResult │
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└────────────────────┬───────────────────────┘
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│
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▼
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┌────────────────────────────────────────────┐
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│ ASSET_PROFILES (Dict[str, AssetProfile])│
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│ ASSET_BEHAVIORS (Dict[str, AssetBehavior])│
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│ EXCHANGE_PROFILES (Dict[str, ExchangeProfile])│
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│ │
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│ System-wide store: │
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│ BLUE ──imports──→ this store │
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│ VIOLET ──imports──→ this store │
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│ UV ──imports──→ this store │
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│ MALKHUT ──uses──→ this store │
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│ ScenarioFactory ──reads──→ this store │
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└────────────────────┬───────────────────────┘
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│
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▼
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┌────────────────────────────────────────────┐
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│ ScenarioFactory │
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│ behavior-driven scenarios │
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│ auto-compile unknown assets │
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│ label queries (sector/role/template) │
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│ exchange-aware scenario generation │
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└────────────────────────────────────────────┘
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```
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---
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## 7. File Locations
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| File | Purpose | Lines |
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|------|---------|-------|
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| `malkhut/training/asset_classification.py` | Enums, AssetProfile, ExchangeProfile, queries | ~600 |
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| `malkhut/training/asset_behavior.py` | 10-dimension behavior model, templates | ~400 |
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| `malkhut/training/asset_compiler.py` | Binance/BingX auto-fetch, compile | ~520 |
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| `malkhut/training/parallel_eval.py` | Parallel episode evaluation | ~91 |
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| `malkhut/training/cma_trainer.py` | ScenarioFactory, CMA-ES trainer | ~1340 |
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| `malkhut/tests/test_asset_classification.py` | 190 classification tests | ~355 |
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| `malkhut/tests/test_parallel_eval.py` | 16 parallel eval tests | ~225 |
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---
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## 8. Constants and Enums Reference
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### Sector (multi-label)
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`CURRENCY`, `LAYER1`, `LAYER2`, `DEFI`, `ORACLE`, `EXCHANGE`, `MEME`, `PRIVACY`, `STORAGE`, `GAMING_NFT`
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### TokenRole (multi-label)
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`GAS`, `STORE_OF_VALUE`, `GOVERNANCE`, `UTILITY`, `MEME`, `EXCHANGE_FEE`
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### SupplyModel (single)
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`FIXED_CAP`, `DISINFLATIONARY`, `INFLATIONARY`, `BURN_MECHANISM`
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### ConsensusFamily (single)
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`POW`, `POS`, `DPOS`
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### SmartContractCapability (single)
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`FULL`, `PARTIAL`, `NONE`
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### MarketCapTier (single)
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`MEGA` (>$500B), `LARGE` ($50-500B), `MID` ($5-50B), `SMALL` ($500M-5B), `MICRO` (<$500M)
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### VolatilityProfile (single)
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`LOW` (<30%), `MEDIUM` (30-80%), `HIGH` (80-150%), `EXTREME` (>150%)
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### LiquidityProfile (single)
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`DEEP` (>$100M), `NORMAL` ($10-100M), `THIN` ($1-10M), `ILLIQUID` (<$1M)
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### DerivativeAccess (single)
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`PERPS_AND_OPTIONS`, `PERPS_ONLY`, `NONE`
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@@ -1,5 +1,5 @@
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"""
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Asset Classification — INVARIANT characteristics only.
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Asset Classification — INVARIANT characteristics only. System-wide asset universe.
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Split into two axes:
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FUNDAMENTAL — intrinsic to the token's design (never changes):
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@@ -8,6 +8,11 @@ Split into two axes:
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TECHNICAL — invariant market-structure properties (set at listing, rarely change):
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MarketCapTier, TypicalSpread/Depth, TickSize/LotSize, FeeStructure,
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Plus:
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EXCHANGE — multi-exchange support:
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ExchangeProfile (per-exchange metadata), exchange-asset mapping
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(which exchanges trade which assets, with exchange-specific parameters).
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DerivativeAccess, PriceDecimals, TypicalVolume
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Overlap handling (industry standard, per CoinGecko/CMC/Messari):
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||||
@@ -120,6 +125,66 @@ class LiquidityProfile(str, Enum):
|
||||
ILLIQUID = "illiquid" # <$1M
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# ExchangeProfile — multi-exchange support
|
||||
# ==============================================================================
|
||||
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class ExchangeProfile:
|
||||
"""Metadata for a trading venue. System-wide — used by BLUE/VIOLET/UV/MALKHUT."""
|
||||
exchange_id: str # canonical key: "binance", "bingx", "bybit", etc.
|
||||
display_name: str # human-readable: "Binance", "BingX"
|
||||
has_spot: bool
|
||||
has_perps: bool
|
||||
has_options: bool
|
||||
api_base_url: str # REST API root
|
||||
ws_base_url: str # WebSocket root ("" if not applicable)
|
||||
default_taker_fee_bps: float
|
||||
default_maker_fee_bps: float
|
||||
typical_latency_ms: float
|
||||
|
||||
|
||||
EXCHANGE_PROFILES: Dict[str, ExchangeProfile] = {}
|
||||
|
||||
BINANCE = ExchangeProfile(
|
||||
exchange_id="binance", display_name="Binance",
|
||||
has_spot=True, has_perps=True, has_options=True,
|
||||
api_base_url="https://api.binance.com",
|
||||
ws_base_url="wss://stream.binance.com:9443",
|
||||
default_taker_fee_bps=0.4, default_maker_fee_bps=0.2,
|
||||
typical_latency_ms=40,
|
||||
)
|
||||
EXCHANGE_PROFILES["binance"] = BINANCE
|
||||
|
||||
BINGX = ExchangeProfile(
|
||||
exchange_id="bingx", display_name="BingX",
|
||||
has_spot=True, has_perps=True, has_options=False,
|
||||
api_base_url="https://open-api.bingx.com",
|
||||
ws_base_url="wss://open-api.bingx.com/swapMarket",
|
||||
default_taker_fee_bps=0.5, default_maker_fee_bps=0.2,
|
||||
typical_latency_ms=100,
|
||||
)
|
||||
EXCHANGE_PROFILES["bingx"] = BINGX
|
||||
|
||||
BYBIT = ExchangeProfile(
|
||||
exchange_id="bybit", display_name="Bybit",
|
||||
has_spot=True, has_perps=True, has_options=True,
|
||||
api_base_url="https://api.bybit.com",
|
||||
ws_base_url="wss://stream.bybit.com/v5/public/linear",
|
||||
default_taker_fee_bps=0.06, default_maker_fee_bps=-0.01,
|
||||
typical_latency_ms=50,
|
||||
)
|
||||
EXCHANGE_PROFILES["bybit"] = BYBIT
|
||||
|
||||
|
||||
def get_exchange(exchange_id: str) -> Optional[ExchangeProfile]:
|
||||
return EXCHANGE_PROFILES.get(exchange_id)
|
||||
|
||||
|
||||
def list_exchanges() -> List[str]:
|
||||
return list(EXCHANGE_PROFILES.keys())
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# AssetProfile — frozen, all-invariant, multi-label where appropriate
|
||||
# ==============================================================================
|
||||
@@ -160,6 +225,9 @@ class AssetProfile:
|
||||
has_funding: bool = False
|
||||
has_options: bool = False
|
||||
|
||||
# --- Exchange membership (which venues trade this asset) ---
|
||||
exchanges: tuple[str, ...] = ("binance",) # tuple of exchange_ids
|
||||
|
||||
@property
|
||||
def sector(self) -> Sector:
|
||||
"""Primary sector (first in tuple). For single-label consumers."""
|
||||
@@ -224,6 +292,7 @@ def _profile(
|
||||
typical_daily_volume_usd: float,
|
||||
has_funding: bool = False,
|
||||
has_options: bool = False,
|
||||
exchanges: Sequence[str] = ("binance",),
|
||||
) -> AssetProfile:
|
||||
return AssetProfile(
|
||||
symbol=symbol,
|
||||
@@ -238,10 +307,10 @@ def _profile(
|
||||
derivative_access=derivative_access,
|
||||
tick_size=tick_size, lot_size=lot_size, price_decimals=price_decimals,
|
||||
maker_fee_bps=maker_fee_bps, taker_fee_bps=taker_fee_bps,
|
||||
typical_spread_bps=typical_spread_bps,
|
||||
typical_depth_usd=typical_depth_usd,
|
||||
typical_spread_bps=typical_spread_bps, typical_depth_usd=typical_depth_usd,
|
||||
typical_daily_volume_usd=typical_daily_volume_usd,
|
||||
has_funding=has_funding, has_options=has_options,
|
||||
exchanges=tuple(exchanges),
|
||||
)
|
||||
|
||||
|
||||
@@ -528,3 +597,20 @@ def get_multi_sector_assets() -> List[AssetProfile]:
|
||||
def get_multi_role_assets() -> List[AssetProfile]:
|
||||
"""Assets serving more than one token role."""
|
||||
return [p for p in ASSET_PROFILES.values() if len(p.token_roles) > 1]
|
||||
|
||||
|
||||
def get_assets_on_exchange(exchange_id: str) -> List[AssetProfile]:
|
||||
"""Assets traded on a given exchange."""
|
||||
return [p for p in ASSET_PROFILES.values() if exchange_id in p.exchanges]
|
||||
|
||||
|
||||
def get_common_assets(exchange_a: str, exchange_b: str) -> List[AssetProfile]:
|
||||
"""Assets traded on BOTH exchanges (intersection)."""
|
||||
return [p for p in ASSET_PROFILES.values()
|
||||
if exchange_a in p.exchanges and exchange_b in p.exchanges]
|
||||
|
||||
|
||||
def get_exchange_for_asset(symbol: str) -> tuple[str, ...]:
|
||||
"""Return which exchanges trade a given asset."""
|
||||
p = ASSET_PROFILES.get(symbol)
|
||||
return p.exchanges if p else ()
|
||||
|
||||
Reference in New Issue
Block a user