Enforcing Data Immutability on Specific Columns in SQLAlchemy

1. Using Attribute Hooks:

   • You can define a custom setter method for the column you want to protect.
   • In the setter method, you can check if an update is happening and raise an error if it is.

2. Conditional Updates:

   • When building your update statement with SQLAlchemy, you can specify which columns to update.
   • You can skip the column you want to protect from updates.

These approaches give you more control over how data is updated in your application.

Here are some additional things to consider:

• These approaches modify the application logic, not SQLAlchemy itself.
• Enforcing data immutability at the database level might be a better solution depending on your specific needs. You can achieve this using database constraints.

Example Codes for Blocking Updates on Specific Columns in SQLAlchemy

from sqlalchemy import Column, Integer, event

class MyModel(Base):
  __tablename__ = 'my_table'
  id = Column(Integer, primary_key=True)
  protected_value = Column(Integer)

  @property
  def protected_value(self):
    return self._protected_value

  @protected_value.setter
  def protected_value(self, value):
    if self.protected_value is not None:
      raise ValueError("Cannot update protected value")
    self._protected_value = value

# Listen for changes to the protected_value attribute
event.listen(MyModel.protected_value, 'set', MyModel.protected_value.setter)

In this example:

• The setter checks if the value is already set and raises an error if it is (preventing updates).
• We define a custom setter method for protected_value.

from sqlalchemy import update

session = Session()

# Update all rows except the protected_value column
session.execute(
  update(MyModel)
  .where(MyModel.id == 1)
  .values({MyModel.other_column: 'new_value'})
)

session.commit()

Here:

• We specify the columns to update (other_column) and exclude the protected column.
• We use the update function to build the update statement.

1. Using hybrid Properties:

   • Define a "hybrid" property using SQLAlchemy's hybrid decorator.
   • This property can handle setting and getting the protected value but restrict updates through logic within the setter.

2. Custom Data Types:

   • Create a custom data type that inherits from SQLAlchemy's base data types.
   • Override the setter method in the custom type to raise an error on update attempts.

3. Database-Level Constraints:

   • If your database supports it, explore setting constraints like NOT NULL DEFAULT on the protected column.
   • This might be a more robust solution compared to application-level logic.

Here's a brief explanation of each method:

from sqlalchemy import Column, Integer, hybrid

class MyModel(Base):
  __tablename__ = 'my_table'
  id = Column(Integer, primary_key=True)
  _protected_value = Column(Integer)

  @hybrid.property
  def protected_value(self):
    return self._protected_value

  @protected_value.setter
  def protected_value(self, value):
    if self._protected_value is None:
      self._protected_value = value
    else:
      raise ValueError("Cannot update protected value")

• The setter allows setting the value only once, raising an error on subsequent updates.
• We use a hybrid property to manage the protected value.

from sqlalchemy import Column, Integer

class ImmutableInteger(Integer):
  def __set__(self, instance, value):
    if instance._protected:
      raise ValueError("Cannot update protected value")
    super().__set__(instance, value)
    instance._protected = True

class MyModel(Base):
  __tablename__ = 'my_table'
  id = Column(Integer, primary_key=True)
  protected_value = Column(ImmutableInteger)

• The setter checks a flag (_protected) and raises an error on updates.
• We define a custom ImmutableInteger type that overrides the setter.

This approach requires checking your database capabilities. You can set constraints like NOT NULL DEFAULT on the protected column, preventing updates but allowing initial data insertion.