Set RDBMS_URI env var to a connection string like postgresql://username:password#host/database, then on Python 3.9 with PostgreSQL 15 and SQLalchemy 1.14 run:
from os import environ
from sqlalchemy import Boolean, Column, Identity, Integer
from sqlalchemy import create_engine
from sqlalchemy.orm import declarative_base
Base = declarative_base()
class Tbl(Base):
__tablename__ = 'Tbl'
__has_error__ = Column(Boolean)
id = Column(Integer, primary_key=True, server_default=Identity())
engine = create_engine(environ["RDBMS_URI"])
Base.metadata.create_all(engine)
Checking the database:
=> \d "Tbl"
Table "public.Tbl"
Column | Type | Collation | Nullable | Default
--------+---------+-----------+----------+----------------------------------
id | integer | | not null | generated by default as identity
Indexes:
"Tbl_pkey" PRIMARY KEY, btree (id)
How do I force the column names with double underscore to work?
I believe that the declarative machinery explicitly excludes attributes whose names start with a double underscore from the mapping process (based on this and this). Consequently your __has_error__ column is not created in the target table.
There are at least two possible workarounds. Firstly, you could give the model attribute a different name, for example:
_has_error = Column('__has_error__', BOOLEAN)
This will create the database column __has_attr__, accessed through Tbl._has_error*.
If you want the model's attribute to be __has_error__, then you can achieve this by using an imperative mapping.
import sqlalchemy as sa
from sqlalchemy import orm
mapper_registry = orm.registry()
tbl = sa.Table(
'tbl',
mapper_registry.metadata,
sa.Column('__has_error__', sa.Boolean),
sa.Column(
'id', sa.Integer, primary_key=True, server_default=sa.Identity()
),
)
class Tbl:
pass
mapper_registry.map_imperatively(Tbl, tbl)
mapper_registry.metadata.create_all(engine)
* I tried using a synonym to map __has_error__ to _has_error but it didn't seem to work. It probably gets exluded in the mapper as well, but I didn't investigate further.
This question is similar to SQLAlchemy query where a column contains a substring, but the other way around: I'm trying to query a column containing a string which is a sub-string of another given string. How can I achieve this?
Here is a code example of a database set up using the ORM:
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy.sql import exists
engine = create_engine('sqlite:///:memory:')
Base = declarative_base()
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
url = Column(String)
fullname = Column(String)
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
session.add_all([
User(url='john', fullname='John Doe'),
User(url='mary', fullname='Mary Contrary')
])
session.commit()
The following works:
e = session.query(exists().where(User.url == 'john')).scalar()
upon which e has the value True. However, I would like to do something like
e = session.query(exists().where(User.url in 'johndoe')).scalar()
where in is in the sense of the __contains__ method of Python's string type. Is this possible?
It's just like (heh) the linked question, except you turn it around:
SELECT ... WHERE 'johndoe' LIKE '%' || url || '%';
You'll need to take care to escape special characters if you've got those in your table:
SELECT ... WHERE 'johndoe' LIKE '%' || replace(replace(replace(url, '\', '\\'), '%', '\%'), '_', '\_') ESCAPE '\';
In SQLAlchemy:
escaped_url = func.replace(func.replace(func.replace(User.url, "\\", "\\\\"),
"%", "\\%"),
"_", "\\_")
session.query(... .where(literal("johndoe").like("%" + escaped_url + "%", escape="\\")))
Note the escaped backslashes in Python.
You can use like
e = session.query(exists().where(User.url.like("%{}%".format('put your string here')))).scalar()
I am using sqlalchemy to reflect the columns of a table in a mysql database into a python script. This is a database I have inherited and some of the column headers for the table have spaces in eg "Chromosome Position". A couple of the column headers also are strings which start with a digit eg "1st time".
I would like to alters these headers so that spaces are replaced with underscores and there are no digits at the beginning of the column header string eg "1st time" becomes "firsttime". I followed the advice given sqlalchemy - reflecting tables and columns with spaces which partially solved my problem.
from sqlalchemy import create_engine, Column, event, MetaData
from sqlalchemy.ext.declarative import declarative_base, DeferredReflection
from sqlalchemy.orm import sessionmaker, Session
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.schema import Table
from twisted.python import reflect
Base = automap_base()
engine = create_engine('mysql://username:password#localhost/variants_database', echo=False)
#Using a reflection event to access the column attributes
#event.listens_for(Table, "column_reflect")
def reflect_col(inspector, table, column_info):
column_info['key'] = column_info['name'].replace(' ', '_')
metadata = MetaData()
session = Session(engine)
class Variants(Base):
__table__ = Table("variants", Base.metadata, autoload=True, autoload_with=engine)
Base.prepare(engine, reflect=True)
session = Session(engine)
a = session.query(Variants).filter(Variants.Gene == "AGL").first()
print a.Chromosome_Position
This allows me to return the values in a.Chromosome_Position. Likewise if I change the method reflect_col to:
#event.listens_for(Table, "column_reflect")
def reflect_col(inspector, table, column_info):
column_info['key'] = column_info['name'].replace('1st time', 'firsttime')
a = session.query(Variants).filter(Variants.Gene == "AGL").first()
print a.firsttime
This also allow me to return the values in a.firsttime. However I am not able to alter both attributes of the column headers at the same time so changing the method to:
#event.listens_for(Table, "column_reflect")
def reflect_col(inspector, table, column_info):
column_info['key'] = column_info['name'].replace(' ', '_')
column_info['key'] = column_info['name'].replace('1st time', 'secondcheck')
will only modify the last call to column_info which in this case is the column '1st time'. So I can return the values of a.firsttime but not a.Chromosome_Position. How do I change both column name features in the same reflection event?
It seems that you are overwriting the first value after the second replacement. I hope chaining the .replace works:
#event.listens_for(Table, "column_reflect")
def reflect_col(inspector, table, column_info):
column_info['key'] = column_info['name'].replace(' ', '_').replace('1st_time', 'secondcheck')
[EDIT]: You have to also make sure that the changes wouldn't clash.
Because in this example the first change replaces spaces with underscore, you have to adapt the second replacement, as it's already called 1st_time when the second replace is called.
I have a simple table defined with SQLAlchemy declarative:
Base = declarative_base()
class MyTable(Base):
__tablename__ = 'mytable1'
row_id = Column(INT, primary_key=True)
another_column = Column(CHAR(10))
I'd like to create a set of tables, with these names:
table_names = ('mytable1', 'mytable2', 'mytable3', 'mytable4')
Is there a simple way to create this set of tables, all with the same column definitions (but each with its own name), without repeating the table definition?
A dictionary would be the best way to go here. Perhaps something like:
table_dict = {}
for i in range(4): # Create
table_name = "mytable" + str(i)
table_dict[table_name] = MyTable(table_name)
for i in range(4): # Query
session.query(table_dict["mytable" + str(i)])
Something like that is probably what you're looking for. This would also let you create the dictionary keys automatically, like in a for loop.
EDIT: I assumed you were making instances of the MyTable class, but looking again that does not appear to be the case. I don't know the specifics of SQLAlchemy but my guess is you'll want to create MyTable instances using the __init__ function.
EDIT EDIT: if you want to create multiple table objects, you could create a function to generate and return a new class. Maybe something like this:
Base = declarative_base()
def TableCreator(tablename):
class MyTable(Base):
__tablename__ = tablename
row_id = Column(INT, primary_key=True)
another_column = Column(CHAR(10))
return MyTable
Then you could call it with mytable1 = TableCreator("mytable1").
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)