peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pyarrow
/src
/arrow
/python
/decimal.cc
// Licensed to the Apache Software Foundation (ASF) under one | |
// or more contributor license agreements. See the NOTICE file | |
// distributed with this work for additional information | |
// regarding copyright ownership. The ASF licenses this file | |
// to you under the Apache License, Version 2.0 (the | |
// "License"); you may not use this file except in compliance | |
// with the License. You may obtain a copy of the License at | |
// | |
// http://www.apache.org/licenses/LICENSE-2.0 | |
// | |
// Unless required by applicable law or agreed to in writing, | |
// software distributed under the License is distributed on an | |
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | |
// KIND, either express or implied. See the License for the | |
// specific language governing permissions and limitations | |
// under the License. | |
namespace arrow { | |
namespace py { | |
namespace internal { | |
Status ImportDecimalType(OwnedRef* decimal_type) { | |
OwnedRef decimal_module; | |
RETURN_NOT_OK(ImportModule("decimal", &decimal_module)); | |
RETURN_NOT_OK(ImportFromModule(decimal_module.obj(), "Decimal", decimal_type)); | |
return Status::OK(); | |
} | |
Status PythonDecimalToString(PyObject* python_decimal, std::string* out) { | |
// Call Python's str(decimal_object) | |
return PyObject_StdStringStr(python_decimal, out); | |
} | |
// \brief Infer the precision and scale of a Python decimal.Decimal instance | |
// \param python_decimal[in] An instance of decimal.Decimal | |
// \param precision[out] The value of the inferred precision | |
// \param scale[out] The value of the inferred scale | |
// \return The status of the operation | |
static Status InferDecimalPrecisionAndScale(PyObject* python_decimal, int32_t* precision, | |
int32_t* scale) { | |
DCHECK_NE(python_decimal, NULLPTR); | |
DCHECK_NE(precision, NULLPTR); | |
DCHECK_NE(scale, NULLPTR); | |
// TODO(phillipc): Make sure we perform PyDecimal_Check(python_decimal) as a DCHECK | |
OwnedRef as_tuple(PyObject_CallMethod(python_decimal, const_cast<char*>("as_tuple"), | |
const_cast<char*>(""))); | |
RETURN_IF_PYERROR(); | |
DCHECK(PyTuple_Check(as_tuple.obj())); | |
OwnedRef digits(PyObject_GetAttrString(as_tuple.obj(), "digits")); | |
RETURN_IF_PYERROR(); | |
DCHECK(PyTuple_Check(digits.obj())); | |
const auto num_digits = static_cast<int32_t>(PyTuple_Size(digits.obj())); | |
RETURN_IF_PYERROR(); | |
OwnedRef py_exponent(PyObject_GetAttrString(as_tuple.obj(), "exponent")); | |
RETURN_IF_PYERROR(); | |
DCHECK(IsPyInteger(py_exponent.obj())); | |
const auto exponent = static_cast<int32_t>(PyLong_AsLong(py_exponent.obj())); | |
RETURN_IF_PYERROR(); | |
if (exponent < 0) { | |
// If exponent > num_digits, we have a number with leading zeros | |
// such as 0.01234. Ensure we have enough precision for leading zeros | |
// (which are not included in num_digits). | |
*precision = std::max(num_digits, -exponent); | |
*scale = -exponent; | |
} else { | |
// Trailing zeros are not included in num_digits, need to add to precision. | |
// Note we don't generate negative scales as they are poorly supported | |
// in non-Arrow systems. | |
*precision = num_digits + exponent; | |
*scale = 0; | |
} | |
return Status::OK(); | |
} | |
PyObject* DecimalFromString(PyObject* decimal_constructor, | |
const std::string& decimal_string) { | |
DCHECK_NE(decimal_constructor, nullptr); | |
auto string_size = decimal_string.size(); | |
DCHECK_GT(string_size, 0); | |
auto string_bytes = decimal_string.c_str(); | |
DCHECK_NE(string_bytes, nullptr); | |
return PyObject_CallFunction(decimal_constructor, const_cast<char*>("s#"), string_bytes, | |
static_cast<Py_ssize_t>(string_size)); | |
} | |
namespace { | |
template <typename ArrowDecimal> | |
Status DecimalFromStdString(const std::string& decimal_string, | |
const DecimalType& arrow_type, ArrowDecimal* out) { | |
int32_t inferred_precision; | |
int32_t inferred_scale; | |
RETURN_NOT_OK(ArrowDecimal::FromString(decimal_string, out, &inferred_precision, | |
&inferred_scale)); | |
const int32_t precision = arrow_type.precision(); | |
const int32_t scale = arrow_type.scale(); | |
if (scale != inferred_scale) { | |
DCHECK_NE(out, NULLPTR); | |
ARROW_ASSIGN_OR_RAISE(*out, out->Rescale(inferred_scale, scale)); | |
} | |
auto inferred_scale_delta = inferred_scale - scale; | |
if (ARROW_PREDICT_FALSE((inferred_precision - inferred_scale_delta) > precision)) { | |
return Status::Invalid( | |
"Decimal type with precision ", inferred_precision, | |
" does not fit into precision inferred from first array element: ", precision); | |
} | |
return Status::OK(); | |
} | |
template <typename ArrowDecimal> | |
Status InternalDecimalFromPythonDecimal(PyObject* python_decimal, | |
const DecimalType& arrow_type, | |
ArrowDecimal* out) { | |
DCHECK_NE(python_decimal, NULLPTR); | |
DCHECK_NE(out, NULLPTR); | |
std::string string; | |
RETURN_NOT_OK(PythonDecimalToString(python_decimal, &string)); | |
return DecimalFromStdString(string, arrow_type, out); | |
} | |
template <typename ArrowDecimal> | |
Status InternalDecimalFromPyObject(PyObject* obj, const DecimalType& arrow_type, | |
ArrowDecimal* out) { | |
DCHECK_NE(obj, NULLPTR); | |
DCHECK_NE(out, NULLPTR); | |
if (IsPyInteger(obj)) { | |
// TODO: add a fast path for small-ish ints | |
std::string string; | |
RETURN_NOT_OK(PyObject_StdStringStr(obj, &string)); | |
return DecimalFromStdString(string, arrow_type, out); | |
} else if (PyDecimal_Check(obj)) { | |
return InternalDecimalFromPythonDecimal<ArrowDecimal>(obj, arrow_type, out); | |
} else { | |
return Status::TypeError("int or Decimal object expected, got ", | |
Py_TYPE(obj)->tp_name); | |
} | |
} | |
} // namespace | |
Status DecimalFromPythonDecimal(PyObject* python_decimal, const DecimalType& arrow_type, | |
Decimal128* out) { | |
return InternalDecimalFromPythonDecimal(python_decimal, arrow_type, out); | |
} | |
Status DecimalFromPyObject(PyObject* obj, const DecimalType& arrow_type, | |
Decimal128* out) { | |
return InternalDecimalFromPyObject(obj, arrow_type, out); | |
} | |
Status DecimalFromPythonDecimal(PyObject* python_decimal, const DecimalType& arrow_type, | |
Decimal256* out) { | |
return InternalDecimalFromPythonDecimal(python_decimal, arrow_type, out); | |
} | |
Status DecimalFromPyObject(PyObject* obj, const DecimalType& arrow_type, | |
Decimal256* out) { | |
return InternalDecimalFromPyObject(obj, arrow_type, out); | |
} | |
bool PyDecimal_Check(PyObject* obj) { | |
static OwnedRef decimal_type; | |
if (!decimal_type.obj()) { | |
ARROW_CHECK_OK(ImportDecimalType(&decimal_type)); | |
DCHECK(PyType_Check(decimal_type.obj())); | |
} | |
// PyObject_IsInstance() is slower as it has to check for virtual subclasses | |
const int result = | |
PyType_IsSubtype(Py_TYPE(obj), reinterpret_cast<PyTypeObject*>(decimal_type.obj())); | |
ARROW_CHECK_NE(result, -1) << " error during PyType_IsSubtype check"; | |
return result == 1; | |
} | |
bool PyDecimal_ISNAN(PyObject* obj) { | |
DCHECK(PyDecimal_Check(obj)) << "obj is not an instance of decimal.Decimal"; | |
OwnedRef is_nan( | |
PyObject_CallMethod(obj, const_cast<char*>("is_nan"), const_cast<char*>(""))); | |
return PyObject_IsTrue(is_nan.obj()) == 1; | |
} | |
DecimalMetadata::DecimalMetadata() | |
: DecimalMetadata(std::numeric_limits<int32_t>::min(), | |
std::numeric_limits<int32_t>::min()) {} | |
DecimalMetadata::DecimalMetadata(int32_t precision, int32_t scale) | |
: precision_(precision), scale_(scale) {} | |
Status DecimalMetadata::Update(int32_t suggested_precision, int32_t suggested_scale) { | |
const int32_t current_scale = scale_; | |
scale_ = std::max(current_scale, suggested_scale); | |
const int32_t current_precision = precision_; | |
if (current_precision == std::numeric_limits<int32_t>::min()) { | |
precision_ = suggested_precision; | |
} else { | |
auto num_digits = std::max(current_precision - current_scale, | |
suggested_precision - suggested_scale); | |
precision_ = std::max(num_digits + scale_, current_precision); | |
} | |
return Status::OK(); | |
} | |
Status DecimalMetadata::Update(PyObject* object) { | |
bool is_decimal = PyDecimal_Check(object); | |
if (ARROW_PREDICT_FALSE(!is_decimal || PyDecimal_ISNAN(object))) { | |
return Status::OK(); | |
} | |
int32_t precision = 0; | |
int32_t scale = 0; | |
RETURN_NOT_OK(InferDecimalPrecisionAndScale(object, &precision, &scale)); | |
return Update(precision, scale); | |
} | |
} // namespace internal | |
} // namespace py | |
} // namespace arrow | |