Using OR in SQLAlchemy

SQLAlchemy overloads the bitwise operators &, | and ~ so instead of the ugly and hard-to-read prefix syntax with or_() and and_() (like in Bastien's answer) you can use these operators:

.filter((AddressBook.lastname == 'bulger') | (AddressBook.firstname == 'whitey'))

Note that the parentheses are not optional due to the precedence of the bitwise operators.

So your whole query could look like this:

addr = session.query(AddressBook) \
    .filter(AddressBook.city == "boston") \
    .filter((AddressBook.lastname == 'bulger') | (AddressBook.firstname == 'whitey'))

or_() function can be useful in case of unknown number of OR query components.

For example, let's assume that we are creating a REST service with few optional filters, that should return record if any of filters return true. On the other side, if parameter was not defined in a request, our query shouldn't change. Without or_() function we must do something like this:

query = Book.query
if filter.title and filter.author:
    query = query.filter((Book.title.ilike(filter.title))|(Book.author.ilike(filter.author)))
else if filter.title:
    query = query.filter(Book.title.ilike(filter.title))
else if filter.author:
    query = query.filter(Book.author.ilike(filter.author))

With or_() function it can be rewritten to:

query = Book.query
not_null_filters = []
if filter.title:
    not_null_filters.append(Book.title.ilike(filter.title))
if filter.author:
    not_null_filters.append(Book.author.ilike(filter.author))

if len(not_null_filters) > 0:
    query = query.filter(or_(*not_null_filters))

For SQLAlchemy ORM 2.0 both | and or_ are accepted.

Documentation

from sqlalchemy.future import select
from sqlalchemy.sql import or_


query = select(User).where(or_(User.name == 'ed', User.name == 'wendy'))
print(query)

# also possible:

query = select(User).where((User.name == 'ed') | (User.name == 'wendy'))
print(query)

In case you need to apply an or condition if a condition is met filters can be stored in variable and chained them with a pipe. Here is an example

 class Student(db.Model):
     __tablename__ = "student"
     id = Column(Integer, primary_key=True)
     name = Column(String, nullable=False)

   def get_by_name(self, name):
      condition = # Code Here for condition
      filters = (Student.name == "Stack") | (Student.name == "Overflow") if 
condition else (Student.name == "Stack")
      query = Student.query.filter(filters).order_by(Student.id.asc())

This has been really helpful. Here is my implementation for any given table:

def sql_replace(self, tableobject, dictargs):

    #missing check of table object is valid
    primarykeys = [key.name for key in inspect(tableobject).primary_key]

    filterargs = []
    for primkeys in primarykeys:
        if dictargs[primkeys] is not None:
            filterargs.append(getattr(db.RT_eqmtvsdata, primkeys) == dictargs[primkeys])
        else:
            return

    query = select([tableobject]).where(and_(*filterargs))

    if self.r_ExecuteAndErrorChk2(query)[primarykeys[0]] is not None:
        # update
        filter = and_(*filterargs)
        query = tableobject.__table__.update().values(dictargs).where(filter)
        return self.w_ExecuteAndErrorChk2(query)

    else:
        query = tableobject.__table__.insert().values(dictargs)
        return self.w_ExecuteAndErrorChk2(query)

# example usage
inrow = {'eqmtvs_id': eqmtvsid, 'datetime': dtime, 'param_id': paramid}

self.sql_replace(tableobject=db.RT_eqmtvsdata, dictargs=inrow)

For filtering on values in JSON columns, the syntax would be like this:

query = query.filter(or_(func.json_contains(models.table.column, '"' + c + '"') for c in (list_of_values)))