python-spanner-orm/spanner_orm/field.py at spanner-orm-upgrade · google/python-spanner-orm

334 lines (268 loc) · 9.56 KB
# Copyright 2019 Google LLC
# 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.
"""Helper to deal with field types in Spanner interactions."""
import base64
import binascii
import datetime
from typing import Any, Optional, Type, Union
import warnings
from google.cloud import spanner
from google.cloud import spanner_v1
from spanner_orm import error
class FieldType(abc.ABC):
  """Base class for column types for Spanner interactions."""
  @abc.abstractmethod
  def ddl(self) -> str:
    """Returns the DDL for this type."""
    raise NotImplementedError
  @abc.abstractmethod
  def grpc_type(self) -> spanner_v1.Type:
    """Returns the type as used in Cloud Spanner's gRPC API."""
    raise NotImplementedError
  @abc.abstractmethod
  def validate_type(self, value: Any) -> None:
    """Raises error.ValidationError if value doesn't match the type."""
    raise NotImplementedError
  def comparable_with(self, other: 'FieldType') -> bool:
    """Returns whether two types are comparable."""
    # https://cloud.google.com/spanner/docs/reference/standard-sql/data-types#comparable_data_types
    return type(self) == type(other)
class Field:
  """Represents a column in a table as a field in a model.
  Attributes:
    name: Name of the column, or None if this hasn't been bound to a column yet.
  name: Optional[str]
  def __init__(
      self,
      field_type: Union[FieldType, Type[FieldType]],
      nullable: bool = False,
      primary_key: bool = False,
    """Initializer.
      field_type: Type of the field. Passing a class instead of an instance of
        that class is deprecated.
      nullable: Whether the field can be NULL.
      primary_key: Whether the field is part of the table's primary key.
    self.name = None
    if isinstance(field_type, FieldType):
      self._type = field_type
      warnings.warn(
          DeprecationWarning(
              'Pass an instance of FieldType instead of a class.'))
      self._type = field_type()
    self._nullable = nullable
    self._primary_key = primary_key
  def ddl(self) -> str:
    """Returns DDL for the column."""
    if self._nullable:
      return self._type.ddl()
    return f'{self._type.ddl()} NOT NULL'
  def field_type(self) -> FieldType:
    """Returns the type of the field."""
    return self._type
  def grpc_type(self) -> spanner_v1.Type:
    """Returns the type as used in Cloud Spanner's gRPC API."""
    return self._type.grpc_type()
  def nullable(self) -> bool:
    """Returns whether the field can be NULL."""
    return self._nullable
  def primary_key(self) -> bool:
    """Returns whether the field is part of the table's primary key."""
    return self._primary_key
  def validate(self, value: Any) -> None:
    """Raises error.ValidationError if value isn't compatible with the field."""
    if value is None:
      if not self._nullable:
        raise error.ValidationError('None set for non-nullable field')
      self._type.validate_type(value)
class Boolean(FieldType):
  """Represents a boolean type."""
  def ddl(self) -> str:
    """See base class."""
    del self  # Unused.
    return 'BOOL'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.BOOL
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, bool):
      raise error.ValidationError(f'{value!r} is not of type bool')
class Integer(FieldType):
  """Represents an integer type."""
  def ddl(self) -> str:
    """See base class."""
    del self  # Unused.
    return 'INT64'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.INT64
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, int):
      raise error.ValidationError(f'{value!r} is not of type int')
class Float(FieldType):
  """Represents a float type."""
  def ddl(self) -> str:
    """See base class."""
    del self  # Unused.
    return 'FLOAT64'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.FLOAT64
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, (int, float)):
      raise error.ValidationError(f'{value!r} is not of type float')
class String(FieldType):
  """Represents a string type."""
  def __init__(self, length: Optional[int] = None):
    """Initializer.
      length: Length of the String. MAX is used if not specified.
    if length is not None and length <= 0:
      raise error.ValidationError('String length must be positive')
    self._length = length
  def ddl(self) -> str:
    """See base class."""
    if self._length is not None:
      return f'STRING({self._length})'
    return 'STRING(MAX)'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.STRING
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, str):
      raise error.ValidationError(f'{value!r} is not of type str')
class Timestamp(FieldType):
  """Represents a timestamp type."""
  def ddl(self) -> str:
    """See base class."""
    del self  # Unused.
    return 'TIMESTAMP'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.TIMESTAMP
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, datetime.datetime):
      raise error.ValidationError(f'{value!r} is not of type datetime')
class BytesBase64(FieldType):
  """Represents a bytes type that must be base64 encoded."""
  def __init__(self, length: Optional[int] = None):
    """Initializer.
      length: Length of the Bytes. MAX is used if not specified.
    if length is not None and length <= 0:
      raise error.ValidationError('Bytes length must be positive')
    self._length = length
  def ddl(self) -> str:
    """See base class."""
    if self._length is not None:
      return f'BYTES({self._length})'
    return 'BYTES(MAX)'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    del self  # Unused.
    return spanner.param_types.BYTES
  def validate_type(self, value: Any) -> None:
    """See base class."""
    del self  # Unused.
    if not isinstance(value, bytes):
      raise error.ValidationError(f'{value!r} is not of type bytes')
    # Rudimentary test to check for base64 encoding.
      base64.b64decode(value, altchars=None, validate=True)
    except binascii.Error:
      raise error.ValidationError(f'{value!r} must be base64-encoded bytes.')
class Array(FieldType):
  """Represents an array type."""
  def __init__(self, element_type: FieldType):
    """Initializer.
      element_type: Type of the values in the array. Can't be an Array type
        itself.
    if isinstance(element_type, Array):
      # https://cloud.google.com/spanner/docs/reference/standard-sql/data-types#array_type
      raise error.SpannerError(
          'Cloud Spanner does not support arrays of arrays.')
    self._element_type = element_type
  def ddl(self) -> str:
    """See base class."""
    return f'ARRAY<{self._element_type.ddl()}>'
  def grpc_type(self) -> spanner_v1.Type:
    """See base class."""
    return spanner.param_types.Array(self._element_type.grpc_type())
  def validate_type(self, value: Any) -> None:
    """See base class."""
    if not isinstance(value, list):
      raise error.ValidationError(f'{value!r} is not of type list')
    for element in value:
      self._element_type.validate_type(element)
  def comparable_with(self, other: FieldType) -> bool:
    """See base class."""
    # Running `select [1, 2] = [1, 2];` in Cloud Spanner gives this error: Query
    # failed: Equality is not defined for arguments of type ARRAY<INT64> at line
    # 3, column 8
    return False
class StringArray(Array):
  """Deprecated way to represent an array of strings type."""
  def __init__(self):
    super().__init__(String())
    warnings.warn(
        DeprecationWarning('Use Array(String()) instead of StringArray().'))
def field_type_from_ddl(ddl: str) -> FieldType:
  """Returns the field type for the given DDL expression."""
  if ddl == 'BOOL':
    return Boolean()
  elif ddl == 'INT64':
    return Integer()
  elif ddl == 'FLOAT64':
    return Float()
  elif ddl == 'STRING(MAX)':
    return String()
  elif (match := re.fullmatch(r'STRING\(([0-9]+)\)', ddl)) is not None:
    return String(int(match.group(1)))
  elif ddl == 'TIMESTAMP':
    return Timestamp()
  elif ddl == 'BYTES(MAX)':
    return BytesBase64()
  elif (match := re.fullmatch(r'BYTES\(([0-9]+)\)', ddl)) is not None:
    return BytesBase64(int(match.group(1)))
  elif (match := re.fullmatch(r'ARRAY<(.*)>', ddl)) is not None:
    return Array(field_type_from_ddl(match.group(1)))
    raise error.SpannerError(f'Invalid or unimplemented DDL type: {ddl!r}')
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