I have a record that I want to exist in the database if it is not there, and if it is there already (primary key exists) I want the fields to be updated to the current state. This is often called an upsert.
The following incomplete code snippet demonstrates what will work, but it seems excessively clunky (especially if there were a lot more columns). What is the better/best way?
Base = declarative_base()
class Template(Base):
__tablename__ = 'templates'
id = Column(Integer, primary_key = True)
name = Column(String(80), unique = True, index = True)
template = Column(String(80), unique = True)
description = Column(String(200))
def __init__(self, Name, Template, Desc):
self.name = Name
self.template = Template
self.description = Desc
def UpsertDefaultTemplate():
sess = Session()
desired_default = Template("default", "AABBCC", "This is the default template")
try:
q = sess.query(Template).filter_by(name = desiredDefault.name)
existing_default = q.one()
except sqlalchemy.orm.exc.NoResultFound:
#default does not exist yet, so add it...
sess.add(desired_default)
else:
#default already exists. Make sure the values are what we want...
assert isinstance(existing_default, Template)
existing_default.name = desired_default.name
existing_default.template = desired_default.template
existing_default.description = desired_default.description
sess.flush()
Is there a better or less verbose way of doing this? Something like this would be great:
sess.upsert_this(desired_default, unique_key = "name")
although the unique_key kwarg is obviously unnecessary (the ORM should be able to easily figure this out) I added it just because SQLAlchemy tends to only work with the primary key. eg: I've been looking at whether Session.merge would be applicable, but this works only on primary key, which in this case is an autoincrementing id which is not terribly useful for this purpose.
A sample use case for this is simply when starting up a server application that may have upgraded its default expected data. ie: no concurrency concerns for this upsert.
SQLAlchemy supports ON CONFLICT with two methods on_conflict_do_update() and on_conflict_do_nothing().
Copying from the documentation:
from sqlalchemy.dialects.postgresql import insert
stmt = insert(my_table).values(user_email='a#b.com', data='inserted data')
stmt = stmt.on_conflict_do_update(
index_elements=[my_table.c.user_email],
index_where=my_table.c.user_email.like('%#gmail.com'),
set_=dict(data=stmt.excluded.data)
)
conn.execute(stmt)
SQLAlchemy does have a "save-or-update" behavior, which in recent versions has been built into session.add, but previously was the separate session.saveorupdate call. This is not an "upsert" but it may be good enough for your needs.
It is good that you are asking about a class with multiple unique keys; I believe this is precisely the reason there is no single correct way to do this. The primary key is also a unique key. If there were no unique constraints, only the primary key, it would be a simple enough problem: if nothing with the given ID exists, or if ID is None, create a new record; else update all other fields in the existing record with that primary key.
However, when there are additional unique constraints, there are logical issues with that simple approach. If you want to "upsert" an object, and the primary key of your object matches an existing record, but another unique column matches a different record, then what do you do? Similarly, if the primary key matches no existing record, but another unique column does match an existing record, then what? There may be a correct answer for your particular situation, but in general I would argue there is no single correct answer.
That would be the reason there is no built in "upsert" operation. The application must define what this means in each particular case.
Nowadays, SQLAlchemy provides two helpful functions on_conflict_do_nothing and on_conflict_do_update. Those functions are useful but require you to swich from the ORM interface to the lower-level one - SQLAlchemy Core.
Although those two functions make upserting using SQLAlchemy's syntax not that difficult, these functions are far from providing a complete out-of-the-box solution to upserting.
My common use case is to upsert a big chunk of rows in a single SQL query/session execution. I usually encounter two problems with upserting:
For example, higher level ORM functionalities we've gotten used to are missing. You cannot use ORM objects but instead have to provide ForeignKeys at the time of insertion.
I'm using this following function I wrote to handle both of those issues:
def upsert(session, model, rows):
table = model.__table__
stmt = postgresql.insert(table)
primary_keys = [key.name for key in inspect(table).primary_key]
update_dict = {c.name: c for c in stmt.excluded if not c.primary_key}
if not update_dict:
raise ValueError("insert_or_update resulted in an empty update_dict")
stmt = stmt.on_conflict_do_update(index_elements=primary_keys,
set_=update_dict)
seen = set()
foreign_keys = {col.name: list(col.foreign_keys)[0].column for col in table.columns if col.foreign_keys}
unique_constraints = [c for c in table.constraints if isinstance(c, UniqueConstraint)]
def handle_foreignkeys_constraints(row):
for c_name, c_value in foreign_keys.items():
foreign_obj = row.pop(c_value.table.name, None)
row[c_name] = getattr(foreign_obj, c_value.name) if foreign_obj else None
for const in unique_constraints:
unique = tuple([const,] + [row[col.name] for col in const.columns])
if unique in seen:
return None
seen.add(unique)
return row
rows = list(filter(None, (handle_foreignkeys_constraints(row) for row in rows)))
session.execute(stmt, rows)
I use a "look before you leap" approach:
# first get the object from the database if it exists
# we're guaranteed to only get one or zero results
# because we're filtering by primary key
switch_command = session.query(Switch_Command).\
filter(Switch_Command.switch_id == switch.id).\
filter(Switch_Command.command_id == command.id).first()
# If we didn't get anything, make one
if not switch_command:
switch_command = Switch_Command(switch_id=switch.id, command_id=command.id)
# update the stuff we care about
switch_command.output = 'Hooray!'
switch_command.lastseen = datetime.datetime.utcnow()
session.add(switch_command)
# This will generate either an INSERT or UPDATE
# depending on whether we have a new object or not
session.commit()
The advantage is that this is db-neutral and I think it's clear to read. The disadvantage is that there's a potential race condition in a scenario like the following:
we query the db for a switch_command and don't find one
we create a switch_command
another process or thread creates a switch_command with the same primary key as ours
we try to commit our switch_command
There are multiple answers and here comes yet another answer (YAA). Other answers are not that readable due to the metaprogramming involved. Here is an example that
Uses SQLAlchemy ORM
Shows how to create a row if there are zero rows using on_conflict_do_nothing
Shows how to update the existing row (if any) without creating a new row using on_conflict_do_update
Uses the table primary key as the constraint
A longer example in the original question what this code is related to.
import sqlalchemy as sa
import sqlalchemy.orm as orm
from sqlalchemy import text
from sqlalchemy.dialects.postgresql import insert
from sqlalchemy.orm import Session
class PairState(Base):
__tablename__ = "pair_state"
# This table has 1-to-1 relationship with Pair
pair_id = sa.Column(sa.ForeignKey("pair.id"), nullable=False, primary_key=True, unique=True)
pair = orm.relationship(Pair,
backref=orm.backref("pair_state",
lazy="dynamic",
cascade="all, delete-orphan",
single_parent=True, ), )
# First raw event in data stream
first_event_at = sa.Column(sa.TIMESTAMP(timezone=True), nullable=False, server_default=text("TO_TIMESTAMP(0)"))
# Last raw event in data stream
last_event_at = sa.Column(sa.TIMESTAMP(timezone=True), nullable=False, server_default=text("TO_TIMESTAMP(0)"))
# The last hypertable entry added
last_interval_at = sa.Column(sa.TIMESTAMP(timezone=True), nullable=False, server_default=text("TO_TIMESTAMP(0)"))
#staticmethod
def create_first_event_if_not_exist(dbsession: Session, pair_id: int, ts: datetime.datetime):
"""Sets the first event value if not exist yet."""
dbsession.execute(
insert(PairState).
values(pair_id=pair_id, first_event_at=ts).
on_conflict_do_nothing()
)
#staticmethod
def update_last_event(dbsession: Session, pair_id: int, ts: datetime.datetime):
"""Replaces the the column last_event_at for a named pair."""
# Based on the original example of https://stackoverflow.com/a/49917004/315168
dbsession.execute(
insert(PairState).
values(pair_id=pair_id, last_event_at=ts).
on_conflict_do_update(constraint=PairState.__table__.primary_key, set_={"last_event_at": ts})
)
#staticmethod
def update_last_interval(dbsession: Session, pair_id: int, ts: datetime.datetime):
"""Replaces the the column last_interval_at for a named pair."""
dbsession.execute(
insert(PairState).
values(pair_id=pair_id, last_interval_at=ts).
on_conflict_do_update(constraint=PairState.__table__.primary_key, set_={"last_interval_at": ts})
)
The below works fine for me with redshift database and will also work for combined primary key constraint.
SOURCE : this
Just few modifications required for creating SQLAlchemy engine in the function
def start_engine()
from sqlalchemy import Column, Integer, Date ,Metadata
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.dialects.postgresql import insert
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.dialects import postgresql
Base = declarative_base()
def start_engine():
engine = create_engine(os.getenv('SQLALCHEMY_URI',
'postgresql://localhost:5432/upsert'))
connect = engine.connect()
meta = MetaData(bind=engine)
meta.reflect(bind=engine)
return engine
class DigitalSpend(Base):
__tablename__ = 'digital_spend'
report_date = Column(Date, nullable=False)
day = Column(Date, nullable=False, primary_key=True)
impressions = Column(Integer)
conversions = Column(Integer)
def __repr__(self):
return str([getattr(self, c.name, None) for c in self.__table__.c])
def compile_query(query):
compiler = query.compile if not hasattr(query, 'statement') else
query.statement.compile
return compiler(dialect=postgresql.dialect())
def upsert(session, model, rows, as_of_date_col='report_date', no_update_cols=[]):
table = model.__table__
stmt = insert(table).values(rows)
update_cols = [c.name for c in table.c
if c not in list(table.primary_key.columns)
and c.name not in no_update_cols]
on_conflict_stmt = stmt.on_conflict_do_update(
index_elements=table.primary_key.columns,
set_={k: getattr(stmt.excluded, k) for k in update_cols},
index_where=(getattr(model, as_of_date_col) < getattr(stmt.excluded, as_of_date_col))
)
print(compile_query(on_conflict_stmt))
session.execute(on_conflict_stmt)
session = start_engine()
upsert(session, DigitalSpend, initial_rows, no_update_cols=['conversions'])
This allows access to the underlying models based on string names
def get_class_by_tablename(tablename):
"""Return class reference mapped to table.
https://stackoverflow.com/questions/11668355/sqlalchemy-get-model-from-table-name-this-may-imply-appending-some-function-to
:param tablename: String with name of table.
:return: Class reference or None.
"""
for c in Base._decl_class_registry.values():
if hasattr(c, '__tablename__') and c.__tablename__ == tablename:
return c
sqla_tbl = get_class_by_tablename(table_name)
def handle_upsert(record_dict, table):
"""
handles updates when there are primary key conflicts
"""
try:
self.active_session().add(table(**record_dict))
except:
# Here we'll assume the error is caused by an integrity error
# We do this because the error classes are passed from the
# underlying package (pyodbc / sqllite) SQLAlchemy doesn't mask
# them with it's own code - this should be updated to have
# explicit error handling for each new db engine
# <update>add explicit error handling for each db engine</update>
active_session.rollback()
# Query for conflic class, use update method to change values based on dict
c_tbl_primary_keys = [i.name for i in table.__table__.primary_key] # List of primary key col names
c_tbl_cols = dict(sqla_tbl.__table__.columns) # String:Col Object crosswalk
c_query_dict = {k:record_dict[k] for k in c_tbl_primary_keys if k in record_dict} # sub-dict from data of primary key:values
c_oo_query_dict = {c_tbl_cols[k]:v for (k,v) in c_query_dict.items()} # col-object:query value for primary key cols
c_target_record = session.query(sqla_tbl).filter(*[k==v for (k,v) in oo_query_dict.items()]).first()
# apply new data values to the existing record
for k, v in record_dict.items()
setattr(c_target_record, k, v)
This works for me with sqlite3 and postgres. Albeit it might fail with combined primary key constraints and will most likely fail with additional unique constraints.
try:
t = self._meta.tables[data['table']]
except KeyError:
self._log.error('table "%s" unknown', data['table'])
return
try:
q = insert(t, values=data['values'])
self._log.debug(q)
self._db.execute(q)
except IntegrityError:
self._log.warning('integrity error')
where_clause = [c.__eq__(data['values'][c.name]) for c in t.c if c.primary_key]
update_dict = {c.name: data['values'][c.name] for c in t.c if not c.primary_key}
q = update(t, values=update_dict).where(*where_clause)
self._log.debug(q)
self._db.execute(q)
except Exception as e:
self._log.error('%s: %s', t.name, e)
As we had problems with generated default-ids and references which lead to ForeignKeyViolation-Errors like
update or delete on table "..." violates foreign key constraint
Key (id)=(...) is still referenced from table "...".
we had to exclude the id for the update dict, as otherwise the it will be always generated as new default value.
In addition the method is returning the created/updated entity.
from sqlalchemy.dialects.postgresql import insert # Important to use the postgresql insert
def upsert(session, data, key_columns, model):
stmt = insert(model).values(data)
# Important to exclude the ID for update!
exclude_for_update = [model.id.name, *key_columns]
update_dict = {c.name: c for c in stmt.excluded if c.name not in exclude_for_update}
stmt = stmt.on_conflict_do_update(
index_elements=key_columns,
set_=update_dict
).returning(model)
orm_stmt = (
select(model)
.from_statement(stmt)
.execution_options(populate_existing=True)
)
return session.execute(orm_stmt).scalar()
Example:
class UpsertUser(Base):
__tablename__ = 'upsert_user'
id = Column(Id, primary_key=True, default=uuid.uuid4)
name: str = Column(sa.String, nullable=False)
user_sid: str = Column(sa.String, nullable=False, unique=True)
house_admin = relationship('UpsertHouse', back_populates='admin', uselist=False)
class UpsertHouse(Base):
__tablename__ = 'upsert_house'
id = Column(Id, primary_key=True, default=uuid.uuid4)
admin_id: Id = Column(Id, ForeignKey('upsert_user.id'), nullable=False)
admin: UpsertUser = relationship('UpsertUser', back_populates='house_admin', uselist=False)
# Usage
upserted_user = upsert(session, updated_user, [UpsertUser.user_sid.name], UpsertUser)
Note: Only tested on postgresql but could work also for other DBs which support ON DUPLICATE KEY UPDATE e.g. MySQL
In case of sqlite, the sqlite_on_conflict='REPLACE' option can be used when defining a UniqueConstraint, and sqlite_on_conflict_unique for unique constraint on a single column. Then session.add will work in a way just like upsert. See the official documentation.
I use this code for upsert
Before using this code, you should add primary keys to table in database.
from sqlalchemy import create_engine
from sqlalchemy import MetaData, Table
from sqlalchemy.inspection import inspect
from sqlalchemy.engine.reflection import Inspector
from sqlalchemy.dialects.postgresql import insert
def upsert(df, engine, table_name, schema=None, chunk_size = 1000):
metadata = MetaData(schema=schema)
metadata.bind = engine
table = Table(table_name, metadata, schema=schema, autoload=True)
# olny use common columns between df and table.
table_columns = {column.name for column in table.columns}
df_columns = set(df.columns)
intersection_columns = table_columns.intersection(df_columns)
df1 = df[intersection_columns]
records = df1.to_dict('records')
# get list of fields making up primary key
primary_keys = [key.name for key in inspect(table).primary_key]
with engine.connect() as conn:
chunks = [records[i:i + chunk_size] for i in range(0, len(records), chunk_size)]
for chunk in chunks:
stmt = insert(table).values(chunk)
update_dict = {c.name: c for c in stmt.excluded if not c.primary_key}
s = stmt.on_conflict_do_update(
index_elements= primary_keys,
set_=update_dict)
conn.execute(s)
With a SQLAlchemy query like:
result = db.session.query(Model).add_columns(
func.min(Model.foo).over().label("min_foo"),
func.max(Model.foo).over().label("max_foo"),
# ...
)
The result is an iterable of tuples, consisting of firstly the Model row, and then the added columns.
How can I either:
Contribute the added columns to Model, such that they can be accessed from each element as model.min_foo et al.; or
Map the added columns into a separate dataclass, such that they can be accessed as e.g. extra.min_foo?
The main thing I'm trying to achieve here is access by name - such as the given labels - without enumerating them all as model, min_foo, max_foo, ... and relying on maintaining the same order. With model, *extra, extra is just a plain list of the aggregate values, there's no reference to the label.
If I dynamically add the columns to the model first:
Model.min_foo = Column(Numeric)
then it complains:
Implicitly combining column modeltable.min_foo with column modeltable.min_foo under attribute 'min_foo'.
Please configure one or more attributes for these same-named columns explicitly
Apparently the solution to that is to explicitly join the tables. But this isn't one!
It seems that this ought to be possible with 'mappers', but I can't find any examples that don't explicitly map to a 'table name' or its columns, which I don't really have here - it's not clear to me if/how they can be used with aggregates, or other 'virtual' columns from the query that aren't actually stored in any table.
I think that what you are looking for is a Query-time SQL expressions as mapped attributes:
from sqlalchemy import create_engine, Column, Integer, select, func
from sqlalchemy.orm import (Session, declarative_base, query_expression,
with_expression)
Base = declarative_base()
class Model(Base):
__tablename__ = 'model'
id = Column(Integer, primary_key=True)
foo = Column(Integer)
foo2 = Column(Integer, default=0)
engine = create_engine('sqlite:///', future=True)
Base.metadata.drop_all(engine)
Base.metadata.create_all(engine)
with Session(engine) as session:
session.add(Model(foo=10))
session.add(Model(foo=20))
session.add(Model(foo=30))
session.add(Model(foo=40))
session.add(Model(foo=50, foo2=1))
session.add(Model(foo=60, foo2=1))
session.add(Model(foo=70, foo2=1))
session.add(Model(foo=80))
session.add(Model(foo=90))
session.add(Model(foo=100))
session.commit()
Model.min_foo = query_expression(func.min(Model.foo).over())
stmt = select(Model).where(Model.foo2 == 1)
models = session.execute(stmt).all()
for model, in models:
print(model.min_foo)
with Session(engine) as session:
Model.max_foo = query_expression()
stmt = select(Model).options(with_expression(Model.max_foo,
func.max(Model.foo).over())
).where(Model.foo2 == 1)
models = session.execute(stmt).all()
for model, in models:
print(model.max_foo)
You can define a default expression when defining the query_expression or using .options with with_expression you can define a runtime expression. The only thing is that the Mapped attribute cannot be unmapped and will return None for max_foo as there is no default expression defined.
I have a, somewhat odd, query that gets me all the items in a parent table that have no matches in its corresponding child table.
If possible, id like to turn it into an SQLAlchemy query. But I have no idea how. I can do basic gets and filters, but this one is beyond my experience so far. Any help you folks might give would be greatly appreciated.
class customerTranslations(Base):
"""parent table. holds customer names"""
__tablename__ = 'customer_translation'
id = Column(Integer, primary_key=True)
class customerEmails(Base):
"""child table. hold emails for customers in translation table"""
__tablename__ = 'customer_emails'
id = Column(Integer, primary_key=True)
parent_id = Column(Integer, ForeignKey('customer_translation.id'))
I want to build:
SELECT * FROM customer_translation
WHERE id NOT IN (SELECT parent_id FROM customer_emails)
You have a subquery, so create one first:
all_emails_stmnt = session.query(customerEmails.parent_id).subquery()
and then you can use that to filter your other table:
translations_with_no_email = session.query(customerTranslations).filter(
~customerTranslations.id.in_(all_emails_stmnt))
This produces the same SQL (but with all the column names expanded, rather than using *, the ORM then can create your objects):
>>> all_emails_stmnt = session.query(customerEmails.parent_id).subquery()
>>> print(all_emails_stmnt)
SELECT customer_emails.parent_id
FROM customer_emails
>>> translations_with_no_email = session.query(customerTranslations).filter(
... ~customerTranslations.id.in_(all_emails_stmnt))
>>> print(translations_with_no_email)
SELECT customer_translation.id AS customer_translation_id
FROM customer_translation
WHERE customer_translation.id NOT IN (SELECT customer_emails.parent_id
FROM customer_emails)
You could also use NOT EXISTS:
from sqlalchemy.sql import exists
has_no_email_stmnt = ~exists().where(customerTranslations.id == customerEmails.parent_id)
translations_with_no_email = session.query(customerTranslations).filter(has_no_email_stmnt)
or, if you have a a backreference on the customerTranslations class pointing to emails, named emails, use .any() on the relationship and invert:
session.query(customerTranslations).filter(
~customerTranslations.emails.any())
Back in 2010 NOT EXISTS was a little slower on MySQL but you may want to re-assess if that is still the case.
I have this SQL expression that I'm trying to write in SQL Alchemy
select * from candidates1 c
inner join uploaded_emails1 e
on c.id=e.candidate_id
group by e.thread_id
How would I go about doing that?
The execute method can be used to run raw SQL, like so:
from sqlalchemy import text
sql = text('select * from candidates1 c inner join uploaded_emails1 e on c.id=e.candidate_id group by e.thread_id')
result = db.engine.execute(sql)
... do stuff ...
If you have some models that you're working with, you could use the relationship field type to create a one-to-many relationship between the Candidate and the UploadedEmail, like so:
class Candidate(Base):
__tablename__ = 'candidates1'
id = Column(Integer, primary_key=True)
uploaded_emails = relationship("UploadedEmail", lazy='dynamic')
class UploadedEmail(Base):
__tablename__ = 'uploaded_emails1'
id = Column(Integer, primary_key=True)
candidate_id = Column(Integer, ForeignKey('candidate.id'))
thread_id = Column(Integer)
And in your code, you might use that like this (including the group_by)
candidate_id = 1
c = Candidate.query.filter_by(id=candidate_id).first()
thread_id_results = c.uploaded_emails.with_entities(UploadedEmail.thread_id).group_by(UploadedEmail.thread_id).all()
thread_ids = [row[0] for row in thread_id_results]
Note that you have to use the .with_entities clause to specify the columns you would like to select, and then the fact that you are specifying the thread_id column. If you don't do this, you'll get errors along the lines of "Expression #X of SELECT list is not in GROUP BY clause and contains nonaggregated column ... which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by".
Sorry I didn't provide enough information to answer the question. This ended up working:
x = db_session.query(Candidate1, Uploaded_Emails1).filter(Candidate1.id == Uploaded_Emails1.candidate_id).group_by(Uploaded_Emails1.thread_id).all()