refactor(protocol): swap S-expression grammar for strict JSON Schema

Sostituisce la grammatica S-expression con uno schema JSON stretto. La
grammatica S-expression falliva il parsing nel 64% delle generazioni del
modello Qwen3-235B sul run reale; JSON e' nativo per gli LLM moderni e
si parsa con json.loads.

Cambiamenti principali:
- grammar.py: costanti rinominate LOGICAL_OPS / COMPARATOR_OPS /
  CROSSOVER_OPS / ACTION_VALUES / KIND_VALUES.
- parser.py: nuovo AST a dataclass tipizzato (OpNode, IndicatorNode,
  FeatureNode, LiteralNode, Rule, Strategy); parse_strategy ora consuma
  JSON tramite json.loads.
- validator.py: walk dispatchato per tipo (isinstance) invece di
  pattern-matching su 'kind'; arity check su operatori e indicator.
- compiler.py: traversal del nuovo AST tipizzato, dispatch per
  isinstance; logica indicator/feature/literal invariata.
- hypothesis.py: prompt SYSTEM riscritto con esempi JSON e vincoli
  espliciti su no-nesting; estrazione via fence ```json``` + fallback
  brace-balanced.
- __init__.py: re-export pubblico delle entita' del protocollo.
- Tutti i test (parser, validator, compiler, hypothesis_agent,
  falsification, adversarial, e2e, smoke_run) migrati a JSON.
- Rimossa dipendenza sexpdata da pyproject.toml + uv.lock.

Test: 135 passed (era 122; aggiunti casi parser/validator).
ruff + mypy strict clean. Smoke run end-to-end OK.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-10 21:17:26 +02:00
parent df76906505
commit 44eb6436c1
16 changed files with 1082 additions and 392 deletions
+60 -7
View File
@@ -1,5 +1,7 @@
from __future__ import annotations
import json
import numpy as np
import pandas as pd
import pytest
@@ -26,7 +28,22 @@ def ohlcv() -> pd.DataFrame:
def test_compile_simple_long(ohlcv: pd.DataFrame) -> None:
src = "(strategy (when (lt (indicator rsi 14) 100.0) (entry-long)))"
src = json.dumps(
{
"rules": [
{
"condition": {
"op": "lt",
"args": [
{"kind": "indicator", "name": "rsi", "params": [14]},
{"kind": "literal", "value": 100.0},
],
},
"action": "entry-long",
}
]
}
)
ast = parse_strategy(src)
fn = compile_strategy(ast)
signals = fn(ohlcv)
@@ -35,7 +52,22 @@ def test_compile_simple_long(ohlcv: pd.DataFrame) -> None:
def test_compile_no_match_is_flat(ohlcv: pd.DataFrame) -> None:
src = "(strategy (when (gt (indicator rsi 14) 1000.0) (entry-long)))"
src = json.dumps(
{
"rules": [
{
"condition": {
"op": "gt",
"args": [
{"kind": "indicator", "name": "rsi", "params": [14]},
{"kind": "literal", "value": 1000.0},
],
},
"action": "entry-long",
}
]
}
)
ast = parse_strategy(src)
fn = compile_strategy(ast)
signals = fn(ohlcv)
@@ -43,11 +75,32 @@ def test_compile_no_match_is_flat(ohlcv: pd.DataFrame) -> None:
def test_compile_two_rules_priority(ohlcv: pd.DataFrame) -> None:
src = """
(strategy
(when (gt (feature close) 110.0) (entry-long))
(when (lt (feature close) 105.0) (entry-short)))
"""
src = json.dumps(
{
"rules": [
{
"condition": {
"op": "gt",
"args": [
{"kind": "feature", "name": "close"},
{"kind": "literal", "value": 110.0},
],
},
"action": "entry-long",
},
{
"condition": {
"op": "lt",
"args": [
{"kind": "feature", "name": "close"},
{"kind": "literal", "value": 105.0},
],
},
"action": "entry-short",
},
]
}
)
ast = parse_strategy(src)
fn = compile_strategy(ast)
signals = fn(ohlcv)