Currently, ``Session.bulk_insert_mappings`` omits NULL values which
causes it to break up batches of inserts based on which batches
contain NULL and which do not.

By adding this flag, the same columns are rendered in the INSERT
for all rows allowing them to be batched.  The downside is that
server-side defaults are omitted.

Doctext-author: Mike Bayer <mike_mp@zzzcomputing.com>
Change-Id: Iec5969304d4bdbf57290b200331bde02254aa3a5
Pull-request: https://github.com/zzzeek/sqlalchemy/pull/243

:meth:`.Session.bulk_save_objects` and related bulk methods have
been scaled back to the extent that this functionality is not
currently used, e.g. checks for column default values to be
fetched after an INSERT or UPDATE statement.
fixes #3526

column that had some kind of "fetch on update" value and was not
locally present in the given object would cause an AttributeError
within the operation.
fixes #3525

- also add a bulk_insert_mappings test

Suppose you have a model class with a primary key.

Base = declarative_base()
class User(Base):
  id = Column(BigInteger, primary_key=True)
  name = Column(String)

Previously, running
`bulk_update_mappings(User, {'id': 1, 'name': 'hello'})`
would emit the following:

```UPDATE users SET id=1, name='hello' WHERE id=1```

This is contrary to the stated behaviour, where primary keys are omitted
from the SET clause. Furthermore, this behaviour is harmful, as it
can cause the db engine to lock over-aggresively (at least in Postgres).

With this change, the emitted SQL is:

```UPDATE users SET name='hello' WHERE id=1```

- start writing docs