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from __future__ import annotations
import ast
import builtins
import contextlib
import importlib
import importlib.util
import io
import json
import math
import statistics
import sys
import time
import traceback
from typing import Any
BANNED_CALLS = {"breakpoint", "compile", "eval", "exec", "input", "open", "__import__"}
def main() -> int:
payload = json.loads(sys.stdin.read())
result = run_payload(payload)
sys.stdout.write(json.dumps(result))
return 0
def run_payload(payload: dict[str, Any]) -> dict[str, Any]:
started = time.perf_counter()
stdout = io.StringIO()
try:
raw = payload["theory_module"]
# Transparently render DSL JSON into a Theory class before execution
try:
from theory_dsl import render_theory_module
code = render_theory_module(raw)
except Exception:
code = raw
allowed_imports = tuple(payload.get("allowed_imports", ()))
_preload_modules(allowed_imports)
_validate_ast(code, allowed_imports)
namespace = {
"__builtins__": _safe_builtins(allowed_imports),
"__name__": "submitted_theory",
"__package__": None,
"math": math,
"statistics": statistics,
}
compiled = compile(code, "<submitted_theory>", "exec")
with contextlib.redirect_stdout(stdout):
exec(compiled, namespace, namespace)
theory_cls = namespace.get("Theory")
if theory_cls is None:
raise ValueError("Submitted module must define class Theory")
theory = theory_cls()
history = payload.get("history", [])
future = payload.get("future", [])
window = {
"history": history,
"steps": len(future),
"sensor_names": payload.get("sensor_names", []),
}
if not hasattr(theory, "fit"):
raise ValueError("Theory must implement fit(history)")
if not hasattr(theory, "predict"):
raise ValueError("Theory must implement predict(window)")
if not hasattr(theory, "log_prob"):
raise ValueError("Theory must implement log_prob(observations)")
fit_result = theory.fit(history)
predictions = theory.predict(window)
reported_log_prob = theory.log_prob(future)
drift_detected = bool(theory.detect_drift(history)) if hasattr(theory, "detect_drift") else False
description = str(theory.describe()) if hasattr(theory, "describe") else ""
return {
"ok": True,
"error": "",
"stdout": stdout.getvalue()[-4000:],
"predictions": _jsonable(predictions),
"reported_log_prob": float(reported_log_prob),
"fit_result": _jsonable(fit_result),
"description": description[:2000],
"drift_detected": drift_detected,
"runtime_ms": round((time.perf_counter() - started) * 1000, 3),
}
except Exception as exc: # pragma: no cover - details are asserted by parent tests.
return {
"ok": False,
"error": f"{type(exc).__name__}: {exc}",
"stdout": stdout.getvalue()[-4000:],
"traceback": traceback.format_exc(limit=4)[-4000:],
"predictions": [],
"reported_log_prob": float("-inf"),
"description": "",
"drift_detected": False,
"runtime_ms": round((time.perf_counter() - started) * 1000, 3),
}
def _preload_modules(allowed_imports: tuple[str, ...]) -> None:
for name in ("numpy", "scipy"):
if name in allowed_imports:
try:
importlib.import_module(name)
except Exception:
pass
def _validate_ast(code: str, allowed_imports: tuple[str, ...]) -> None:
tree = ast.parse(code)
module_aliases: dict[str, str] = {}
for node in ast.walk(tree):
if isinstance(node, ast.Import):
for alias in node.names:
_require_allowed_import(alias.name, allowed_imports)
module_aliases[alias.asname or alias.name.split(".", 1)[0]] = alias.name
elif isinstance(node, ast.ImportFrom):
if node.module is None:
raise ImportError("Relative imports are not allowed")
_require_allowed_import(node.module, allowed_imports)
_require_allowed_fromlist(node.module, [alias.name for alias in node.names], allowed_imports)
for alias in node.names:
imported_name = f"{node.module}.{alias.name}"
if imported_name in allowed_imports:
module_aliases[alias.asname or alias.name] = imported_name
elif isinstance(node, ast.Call) and isinstance(node.func, ast.Name):
if node.func.id in BANNED_CALLS:
raise PermissionError(f"Call to {node.func.id} is not allowed")
if node.func.id == "getattr":
_require_allowed_getattr(node, module_aliases, allowed_imports)
elif isinstance(node, ast.Attribute) and node.attr.startswith("__"):
raise PermissionError("Dunder attribute access is not allowed")
elif isinstance(node, ast.Attribute):
_require_allowed_attribute(node, module_aliases, allowed_imports)
def _require_allowed_import(module_name: str, allowed_imports: tuple[str, ...]) -> None:
if module_name not in allowed_imports:
raise ImportError(f"Import '{module_name}' is not allowed")
def _require_allowed_fromlist(module_name: str, fromlist: list[str] | tuple[str, ...], allowed_imports: tuple[str, ...]) -> None:
for item in fromlist:
if item == "*":
raise ImportError("Wildcard imports are not allowed")
submodule_name = f"{module_name}.{item}"
if _looks_like_submodule(submodule_name) and submodule_name not in allowed_imports:
raise ImportError(f"Import '{submodule_name}' is not allowed")
def _looks_like_submodule(module_name: str) -> bool:
try:
return importlib.util.find_spec(module_name) is not None
except (ImportError, AttributeError, ModuleNotFoundError, ValueError):
return False
def _require_allowed_attribute(
node: ast.Attribute,
module_aliases: dict[str, str],
allowed_imports: tuple[str, ...],
) -> None:
if not isinstance(node.value, ast.Name):
return
module_name = module_aliases.get(node.value.id)
if not module_name:
return
submodule_name = f"{module_name}.{node.attr}"
if _looks_like_submodule(submodule_name) and submodule_name not in allowed_imports:
raise ImportError(f"Import '{submodule_name}' is not allowed")
def _require_allowed_getattr(
node: ast.Call,
module_aliases: dict[str, str],
allowed_imports: tuple[str, ...],
) -> None:
if len(node.args) < 2 or not isinstance(node.args[1], ast.Constant) or not isinstance(node.args[1].value, str):
return
attr = node.args[1].value
if attr.startswith("__"):
raise PermissionError("Dunder attribute access is not allowed")
if not isinstance(node.args[0], ast.Name):
return
module_name = module_aliases.get(node.args[0].id)
if not module_name:
return
submodule_name = f"{module_name}.{attr}"
if _looks_like_submodule(submodule_name) and submodule_name not in allowed_imports:
raise ImportError(f"Import '{submodule_name}' is not allowed")
def _safe_builtins(allowed_imports: tuple[str, ...]) -> dict[str, Any]:
safe_names = [
"abs",
"all",
"any",
"ArithmeticError",
"AssertionError",
"BaseException",
"bool",
"dict",
"enumerate",
"Exception",
"filter",
"float",
"getattr",
"hasattr",
"int",
"isinstance",
"issubclass",
"len",
"list",
"map",
"max",
"min",
"object",
"pow",
"print",
"property",
"range",
"repr",
"round",
"set",
"slice",
"sorted",
"staticmethod",
"str",
"sum",
"super",
"tuple",
"type",
"ValueError",
"zip",
]
safe = {name: getattr(builtins, name) for name in safe_names}
safe["__build_class__"] = builtins.__build_class__
safe["__import__"] = _limited_import(allowed_imports)
return safe
def _limited_import(allowed_imports: tuple[str, ...]):
def import_hook(name, globals=None, locals=None, fromlist=(), level=0):
if level != 0:
raise ImportError("Relative imports are not allowed")
_require_allowed_import(name, allowed_imports)
_require_allowed_fromlist(name, fromlist or (), allowed_imports)
return builtins.__import__(name, globals, locals, fromlist, level)
return import_hook
def _jsonable(value: Any) -> Any:
if isinstance(value, dict):
return {str(key): _jsonable(item) for key, item in value.items()}
if isinstance(value, (list, tuple)):
return [_jsonable(item) for item in value]
if hasattr(value, "item"):
try:
return value.item()
except Exception:
pass
if hasattr(value, "tolist"):
try:
return _jsonable(value.tolist())
except Exception:
pass
try:
json.dumps(value)
return value
except TypeError:
return repr(value)
if __name__ == "__main__":
raise SystemExit(main())
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