How can I verify Column data types in the SQLAlchemy ORM?

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一生所求
一生所求 2020-11-28 08:54

Using the SQLAlchemy ORM, I want to make sure values are the right type for their columns.

For example, say I have an Integer column. I try to insert the value “hell

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  • 2020-11-28 09:17

    Improving on the answer of @zzzeek , I suggest the following solution:

    from sqlalchemy import String
    from sqlalchemy.ext.declarative import declarative_base
    from sqlalchemy.event import listen_for
    
    Base = declarative_base()
    
    @listens_for(Base, 'attribute_instrument')
    def configure_listener(table_cls, attr, col_inst):
        if not hasattr(col_inst.property, 'columns'):
            return
        validator = getattr(col_inst.property.columns[0].type, 'validator', None)
        if validator:
            # Only decorate columns, that need to be decorated
            @listens_for(col_inst, "set", retval=True)
            def set_(instance, value, oldvalue, initiator):
                return validator(value)
    

    That lets you do things like:

    class Name(String):
        def validator(self, name):
            if isinstance(name, str):
                return name.upper()
            raise TypeError("name must be a string")
    

    This has two benefits: Firstly, there is only an event triggered, when there actually is a validator attached to the data field object. It does not waste precious CPU cycles on set events for objects, that have no function for validation defined. Secondly, it allows you to define your own field types and just add a validator method there, so not all things that you want to store as Integer etc run through the same checks, just the ones derived from your new field type.

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  • 2020-11-28 09:19

    SQLAlchemy doesn't build this in as it defers to the DBAPI/database as the best and most efficient source of validation and coercion of values.

    To build your own validation, usually TypeDecorator or ORM-level validation is used. TypeDecorator has the advantage that it operates at the core and can be pretty transparent, though it only occurs when SQL is actually emitted.

    To do validation and coercion sooner, this is at the ORM level.

    Validation can be ad-hoc, at the ORM layer, via @validates:

    http://docs.sqlalchemy.org/en/latest/orm/mapped_attributes.html#simple-validators

    The event system that @validates uses is also available directly. You can write a generalized solution that links validators of your choosing to the types being mapped:

    from sqlalchemy import Column, Integer, String, DateTime
    from sqlalchemy.ext.declarative import declarative_base
    from sqlalchemy import event
    import datetime
    
    Base= declarative_base()
    
    def validate_int(value):
        if isinstance(value, basestring):
            value = int(value)
        else:
            assert isinstance(value, int)
        return value
    
    def validate_string(value):
        assert isinstance(value, basestring)
        return value
    
    def validate_datetime(value):
        assert isinstance(value, datetime.datetime)
        return value
    
    validators = {
        Integer:validate_int,
        String:validate_string,
        DateTime:validate_datetime,
    }
    
    # this event is called whenever an attribute
    # on a class is instrumented
    @event.listens_for(Base, 'attribute_instrument')
    def configure_listener(class_, key, inst):
        if not hasattr(inst.property, 'columns'):
            return
        # this event is called whenever a "set" 
        # occurs on that instrumented attribute
        @event.listens_for(inst, "set", retval=True)
        def set_(instance, value, oldvalue, initiator):
            validator = validators.get(inst.property.columns[0].type.__class__)
            if validator:
                return validator(value)
            else:
                return value
    
    
    class MyObject(Base):
        __tablename__ = 'mytable'
    
        id = Column(Integer, primary_key=True)
        svalue = Column(String)
        ivalue = Column(Integer)
        dvalue = Column(DateTime)
    
    
    m = MyObject()
    m.svalue = "ASdf"
    
    m.ivalue = "45"
    
    m.dvalue = "not a date"
    

    Validation and coercion can also be built at the type level using TypeDecorator, though this is only when SQL is being emitted, such as this example which coerces utf-8 strings to unicode:

    http://docs.sqlalchemy.org/en/latest/core/custom_types.html#coercing-encoded-strings-to-unicode

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