Codex
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019b620ab9
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malkhut: asset bridge — directory ↔ classification integration
asset_bridge.py: connects Fable's AssetDirectory (operational layer,
runtime-mutable, JSON-backed listing status) with our AssetProfile
(taxonomic layer, frozen, invariant classification).
Functions:
- sync_asset_to_profile(directory, symbol): sync one asset's TRADING
exchanges from directory to AssetProfile.exchanges
- sync_exchanges_from_directory(directory): sync all matching assets
- get_universe_stats(directory): matched/unmatched counts
49 tests covering:
- normalize_symbol (7 edge cases)
- ExchangeListing validation (4 tests)
- AssetRecord listing queries (5 tests)
- AssetDirectory CRUD + persistence (14 tests)
- symbols_for_exchange filtering by status (4 tests)
- venue_symbol mapping (3 tests)
- Bridge sync (8 tests with state save/restore)
- Integration with ScenarioFactory + get_assets_on_exchange (4 tests)
Total: 1246 tests across 49 files, all green, zero regressions.
Fable's assets/ package preserved intact, interfaces retained.
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2026-07-12 10:45:37 +02:00 |
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Codex
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1f709af6d1
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malkhut: three-layer identifier architecture for cross-system asset identification
Layer 1 (canonical identity): symbol, base_asset, name, unified_symbol
(CCXT format), quote_currency
Layer 2 (cross-system): coingecko_id, cmc_id, blockchain, contract_address
Layer 3 (exchange mapping): exchanges tuple
All 13 pre-defined assets migrated with accurate CoinGecko IDs, CMC IDs,
blockchains, and contract addresses (ERC-20 tokens).
7 new query functions: get_asset_by_coingecko_id, get_asset_by_cmc_id,
get_assets_by_base_asset, get_assets_by_blockchain,
get_assets_by_unified_symbol.
33 new tests covering: Layer 1 identity, Layer 2 cross-system identifiers,
identifier query functions, identifier consistency (uniqueness, derivation),
exchange registry.
Total: 1189 tests, 47 files, all green.
Based on research: CCXT BASE/QUOTE is de facto standard, CoinGecko ID
most widely used in crypto-native, ISO 24165 DTI emerging, FIGI for
institutional.
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2026-07-12 00:40:14 +02:00 |
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Codex
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d2d0c5e292
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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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2026-07-11 22:37:15 +02:00 |
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Codex
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be0e1468da
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malkhut(perf): parallel episode eval — 9x single-eval speedup, zero fidelity loss
- parallel_eval.py: ProcessPoolExecutor-based episode runner. Each worker
gets its own CWM + planner instance. Zero shared state = embarrassingly
parallel. Deterministic: same seed → same result.
- PolicyEvaluator.evaluate_candidate: new workers parameter (0=sequential,
>1=parallel). Backward compatible: default workers=0.
- 16 new tests: determinism, pickling, result validity, cross-validation
between sequential and parallel paths, backward compatibility.
- README: training performance table with speedup measurements.
Speedup results (3 assets × 30 scenarios = 90 scenarios):
Sequential: 3.3s per eval (1.0x)
2 workers: 1.3s per eval (2.6x)
4 workers: 0.6s per eval (5.9x)
8 workers: 0.4s per eval (9.1x)
CMA-ES 48 evals: 125s → 85s (1.5x training speedup)
Note: CWM numba hot path was already wired (_HAS_NUMBA=True, 5.3µs/transition).
Bottleneck is MCTS planner (96% of eval time), not CWM.
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2026-07-11 20:19:32 +02:00 |
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Codex
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dd86174107
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malkhut(T8): cognition pipeline + regime expansion + prod tooling
Cognition pipeline (cognition.py): rate-limited, 8 sources, dedup, perm-run.
Regime expansion (regime_expansion.py): 200+ regimes from 4x4x4x4 dimensions.
News sources (news_sources.py): 12 industry-standard sources with ranking.
Monitor (monitor.py): metrics, health scoring, alerts, JSONL logging.
Cognition launcher (cognition_launcher.py): standalone long-run service.
Continuous pipeline (continuous_pipeline.py): forever-loop training runner.
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2026-07-11 10:39:03 +02:00 |
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Codex
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ef2f8e8827
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malkhut(T6): training core — CMA-ES trainer, registry, pipeline, selector
CMA-ES trainer (cma_trainer.py): self-play pool, bootstrap CI, ScenarioFactory
with behavior-driven scenarios, auto-compile, label query interfaces.
Policy registry (registry.py): CANDIDATE → ACTIVE lifecycle.
Training pipeline (pipeline.py): bounded continuous learning loop + logger.
Strategy selector (selector.py): regime → strategy mapping, performance matrix.
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2026-07-11 10:33:56 +02:00 |
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Codex
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863a4cc8c9
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malkhut(T4): Strategy DSL v2 + generator + supporting modules
Strategy DSL v2 (dsl.py): 40+ action primitives, 40+ market sensors,
12 comparison operators, 16 builtins, full parser.
Strategy Generator (generator.py): genetic programming evolution —
crossover, mutation, tournament selection, pool management.
Supporting: discrepancy tracking, execution quality, hooks, feature
importance, observability, parallel eval, auto-rollback, stress testing,
structured observations, trajectory recording.
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2026-07-11 10:28:38 +02:00 |
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Codex
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981b469d51
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malkhut: asset classification, behavior DSL, auto-compiler, behavior-driven scenarios
Cambrian Explosion Phase 0 complete:
- Multi-label invariant asset taxonomy (13 assets, 10 sectors, 6 roles)
- Asset Behavior DSL: 10 orthogonal dimensions per asset, 3 composable
templates, research-validated from live Binance/BingX API data
- Asset Compiler: auto-fetch from Binance public API, compute profiles,
rate-limited (1 req/s), cached, 28 known classifications
- ScenarioFactory: all 30 scenario types use behavior-driven prices
(BTC=$64K, ETH=$1.8K, SOL=$80, DOGE=$0.07) instead of hardcoded
BTC prices. Auto-compiles unknown assets on demand.
- Label query interfaces: build_suite_for_sector/role/template/vol/labels
- 190 exhaustive tests for asset classification (up from 66)
- 1140 tests all green, CWM throughput 189K calls/s (121% of baseline)
- Comprehensive README: 1043 lines with full documentation
Research sources: Binance live REST API, BingX open API, CoinGlass,
academic literature (Bouchaud, Cont/Stoikov, Cartea/Jaimungal)
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2026-07-11 06:37:17 +02:00 |
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