def eval(self, env: Env.Values) -> V.String:
""
v = self.expr.eval(env)
if isinstance(v, V.Null):
if "default" in self.options:
return V.String(self.options["default"])
return V.String("")
if isinstance(v, V.String):
return v
if isinstance(v, V.Array):
return V.String(self.options["sep"].join(
str(item.value) for item in v.value))
if v == V.Boolean(True) and "true" in self.options:
return V.String(self.options["true"])
if v == V.Boolean(False) and "false" in self.options:
return V.String(self.options["false"])
return V.String(str(v))
def eval(self, env: Env.Values) -> V.Boolean:
""
return V.Boolean(self.value)
def __call__(self, expr: E.Apply, env: Env.Values, stdlib: Base) -> V.Base:
lhs = expr.arguments[0].eval(env, stdlib=stdlib).expect(T.Boolean()).value
if lhs:
return V.Boolean(True)
return expr.arguments[1].eval(env, stdlib=stdlib).expect(T.Boolean())
def _call_eager(self, expr: E.Apply, arguments: List[V.Base]) -> V.Base:
assert len(arguments) == 2
return V.Boolean(self.op(arguments[0].value, arguments[1].value))
def __init__(self):
# language built-ins
self._at = _At()
self._land = _And()
self._lor = _Or()
self._negate = StaticFunction(
"_negate", [T.Boolean()], T.Boolean(), lambda x: V.Boolean(not x.value)
)
self._add = _AddOperator()
self._sub = _ArithmeticOperator("-", lambda l, r: l - r)
self._mul = _ArithmeticOperator("*", lambda l, r: l * r)
self._div = _ArithmeticOperator("/", lambda l, r: l // r)
self._rem = StaticFunction(
"_rem", [T.Int(), T.Int()], T.Int(), lambda l, r: V.Int(l.value % r.value)
)
self._eqeq = _ComparisonOperator("==", lambda l, r: l == r)
self._neq = _ComparisonOperator("!=", lambda l, r: l != r)
self._lt = _ComparisonOperator("<", lambda l, r: l < r)
self._lte = _ComparisonOperator("<=", lambda l, r: l <= r)
self._gt = _ComparisonOperator(">", lambda l, r: l > r)
self._gte = _ComparisonOperator(">=", lambda l, r: l >= r)
# static stdlib functions
for (name, argument_types, return_type, F) in [
("floor", [T.Float()], T.Int(), lambda v: V.Int(math.floor(v.value))),
("ceil", [T.Float()], T.Int(), lambda v: V.Int(math.ceil(v.value))),
("round", [T.Float()], T.Int(), lambda v: V.Int(round(v.value))),
("length", [T.Array(T.Any())], T.Int(), lambda v: V.Int(len(v.value))),
("sub", [T.String(), T.String(), T.String()], T.String(), _sub),
("basename", [T.String(), T.String(optional=True)], T.String(), _basename),
(
"defined",
[T.Any(optional=True)],
T.Boolean(),
lambda v: V.Boolean(not isinstance(v, V.Null)),
),
# context-dependent:
("write_lines", [T.Array(T.String())], T.File(), _notimpl),
("write_tsv", [T.Array(T.Array(T.String()))], T.File(), _notimpl),
("write_map", [T.Map((T.Any(), T.Any()))], T.File(), _notimpl),
("write_json", [T.Any()], T.File(), _notimpl),
("stdout", [], T.File(), _notimpl),
("stderr", [], T.File(), _notimpl),
("glob", [T.String()], T.Array(T.File()), _notimpl),
("read_int", [T.File()], T.Int(), _notimpl),
("read_boolean", [T.File()], T.Boolean(), _notimpl),
("read_string", [T.File()], T.String(), _notimpl),
("read_float", [T.File()], T.Float(), _notimpl),
("read_array", [T.File()], T.Array(T.Any()), _notimpl),
("read_map", [T.File()], T.Map((T.Any(), T.Any())), _notimpl),
("read_lines", [T.File()], T.Array(T.Any()), _notimpl),
("read_tsv", [T.File()], T.Array(T.Array(T.String())), _notimpl),
("read_json", [T.File()], T.Any(), _notimpl),
]:
setattr(self, name, StaticFunction(name, argument_types, return_type, F))
# polymorphically typed stdlib functions which require specialized
# infer_type logic
self.range = _Range()
self.prefix = _Prefix()
self.size = _Size()
self.select_first = _SelectFirst()
self.select_all = _SelectAll()
self.zip = _Zip()
self.cross = _Zip() # FIXME
self.flatten = _Flatten()
self.transpose = _Transpose()
def __call__(self, expr: E.Apply, env: Env.Values) -> V.Base:
if isinstance(expr.arguments[0].eval(env), V.Null):
return V.Boolean(False)
return V.Boolean(True)
def __call__(self, expr: E.Apply, env: E.Env) -> V.Base:
assert len(expr.arguments) == 2
return V.Boolean(
# pyre-fixme
self.op(expr.arguments[0].eval(env).value,
expr.arguments[1].eval(env).value))
def __call__(self, expr: E.Apply, env: E.Env) -> V.Base:
lhs = expr.arguments[0].eval(env).expect(T.Boolean()).value
if lhs:
return V.Boolean(True)
return expr.arguments[1].eval(env).expect(T.Boolean())
assert len(expr.arguments) == len(self.argument_types)
argument_values = [
arg.eval(env).coerce(ty)
for arg, ty in zip(expr.arguments, self.argument_types)
]
ans: V.Base = self.F(*argument_values)
return ans.coerce(self.return_type)
def _notimpl(one: Any = None, two: Any = None) -> None:
exec("raise NotImplementedError()")
_static_functions: List[Tuple[str, List[T.Base], T.Base, Any]] = [
("_negate", [T.Boolean()], T.Boolean(),
lambda x: V.Boolean(not x.value)), # pyre-fixme
("_rem", [T.Int(), T.Int()], T.Int(),
lambda l, r: V.Int(l.value % r.value)), # pyre-fixme
("stdout", [], T.File(), _notimpl),
("basename", [T.String(), T.String(optional=True)], T.String(), _notimpl),
# note: size() can take an empty value and probably returns 0 in that case.
# e.g. https://github.com/DataBiosphere/topmed-workflows/blob/31ba8a714b36ada929044f2ba3d130936e6c740e/CRAM-no-header-md5sum/md5sum/CRAM_md5sum.wdl#L39
("size", [T.File(optional=True),
T.String(optional=True)], T.Float(), _notimpl),
("ceil", [T.Float()], T.Int(), _notimpl),
("round", [T.Float()], T.Int(), _notimpl),
("glob", [T.String()], T.Array(T.File()), _notimpl),
("read_int", [T.String()], T.Int(), _notimpl),
("read_boolean", [T.String()], T.Boolean(), _notimpl),
("read_string", [T.String()], T.String(), _notimpl),
("read_float", [T.String()], T.Float(), _notimpl),