# Copyright 2018 The Feast Authors

#

# Licensed 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

#

# https://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.

from feast.sdk.resources.feature import ValueType

import numpy as np

# mapping of pandas dtypes to feast value type strings

DTYPE_TO_VALUE_TYPE_MAPPING = {

"float64": ValueType.DOUBLE,

"float32": ValueType.FLOAT,

"int64": ValueType.INT64,

"uint64": ValueType.INT64,

"int32": ValueType.INT32,

"uint32": ValueType.INT32,

"uint8": ValueType.INT32,

"int8": ValueType.INT32,

"bool": ValueType.BOOL,

"timedelta": ValueType.INT64,

"datetime64[ns]": ValueType.TIMESTAMP,

"datetime64[ns, tz]": ValueType.TIMESTAMP,

"category": ValueType.STRING,

"object": ValueType.STRING

}

# Mapping of feast value type to Pandas DataFrame dtypes

# Integer and floating values are all 64-bit for better integration

# with BigQuery data types

FEAST_VALUETYPE_TO_DTYPE = {

"bytesVal": np.byte,

"stringVal": np.object,

"int32Val": "Int32", # Use pandas nullable int type

"int64Val": "Int64", # Use pandas nullable int type

"doubleVal": np.float64,

"floatVal": np.float64,

"boolVal": np.bool,

"timestampVal": np.datetime64,

}

def dtype_to_value_type(dtype):

"""Returns the equivalent feast valueType for the given dtype

Args:

dtype (pandas.dtype): pandas dtype

Returns:

feast.types.ValueType2.ValueType: equivalent feast valuetype

"""

return DTYPE_TO_VALUE_TYPE_MAPPING[dtype.__str__()]