I'm trying to create a function for updating rows in a database, based on an instance of a class.
Basically I would like to do something like this:
def update_table(self, result):
session = self.Session()
session.query(result.__class__).filter_by(id=result.id).update(result)
session.commit()
session.close_all()
user = db.Model.User(
id = 1,
name = "foo"
)
# Store user to db
db.save(user)
updated_user = db.Model.User(
id = 1,
user = "bar"
)
# Update the users name with id=1
update_table(updated_user)
The problem is ofc that the session query results in a
TypeError: 'User' object is not iterable
but in my mind, this should end up with an updated user with name="bar".
Is there way to create such a function using the SQLAlchemy ORM?
You don't need an extra update procedure ...
user = db.Model.User(
id = 1,
name = "foo"
)
# Store user to db
db.save(user)
new_user = session.query(User).filter(User.id==1).first()
new_user.name = "bar"
session.commit()
I ended up with this solution:
# Update single entry
def update_table_by_id(self, entry):
# Open connection to database
session = self.Session()
# Fetch entry from database
db_result = session.query(entry.__class__).filter_by(id=entry.id)
# Convert Models to dicts
entry_dict = entry.as_dict()
db_result_dict = db_result.first().as_dict()
# Update database result with passed in entry. Skip of None
for value in entry_dict:
if entry_dict[value] is not None:
db_result_dict[value] = entry_dict[value]
# Update db and close connections
db_result.update(db_result_dict)
session.commit()
session.close_all()
It allows me to send in arbitrary models, and they are all handled the same.
Suggestions and improvements are welcome!
In continue to my previous post
I'm trying to use the bulk_save_objects for a list of objects (the objects dont have a PK value therefore it should create it for each object). When I use the bulk_save_objects I see an insert per object instead of one insert for all objects.
The code :
class Product(Base):
__tablename__ = 'products'
id = Column('id',BIGINT, primary_key=True)
barcode = Column('barcode' ,BIGINT)
productName = Column('name', TEXT,nullable=False)
objectHash=Column('objectHash',TEXT,unique=True,nullable=False)
def __init__(self, productData,picture=None):
self.barcode = productData[ProductTagsEnum.barcode.value]
self.productName = productData[ProductTagsEnum.productName.value]
self.objectHash = md5((str(self.barcode)+self.produtName).encode('utf-8')).hexdigest()
Another class contains the following save method :
def saveNewProducts(self,products):
Session = sessionmaker()
session=Session()
productsHashes=[ product.objectHash for product in products]
query = session.query(Product.objectHash).filter(Product.objectHash.in_(productsHashes))
existedHashes=query.all()
newProducts = [ product for product in products if product.objectHash not in productsHashes]
/*also tried : session.bulk_save_objects(newProducts, preserve_order=False)*/
session.bulk_save_objects(newProducts)
UPDATE 1
I following what #Ilja Everilä recommended in the comments, I added a few parameters to the connection string :
engine = create_engine('postgresql://postgres:123#localhost:5432/mydb', pool_size=25, max_overflow=0,
executemany_mode='values',
executemany_values_page_size=10000, executemany_batch_page_size=500,
echo=True)
In the console I saw multiple inserts with the following format :
2019-09-16 16:48:46,509 INFO sqlalchemy.engine.base.Engine INSERT INTO products (barcode, productName, objectHash) VALUES (%(barcode)s, %(productName)s, %(objectHash)s, ) RETURNING products.id
2019-09-16 16:48:46,509 INFO sqlalchemy.engine.base.Engine {'barcode': '5008251', 'productName': 'ice ream','object_hash': 'b2752233ec523f2e874dc95b70020ae5'}
In my case, the solution I used : I deleted the id column and set the objectHash as PK, and afterwards the save_bulk and add_all functions worked and actually did bulk insert. It seems like those functions work only if you already have the pk inside the object.
I have a table that has one column declared as a json and I need to update records by adding a key-value to the json value.
model
class User(db.Model):
__tablename__ = 'users'
loginId = db.Column(db.String(128), nullable=False, primary_key=True)
_password = db.Column(db.String(128), nullable=True)
views = db.Column(JSON, nullable=True)
controller
#mod_event.route('/view', methods=['POST'])
def view():
try:
params = request.json
loginId = params['dream']['loginId']
users.update().\
where(users.c.loginId==loginId).\
values(views=<query>))
Assume current value in views is {'1001' : 1}
What should be the query if views has to be updated to -
{'1001' : 2}
{'1001' : 1, '1002' : 1}
if i don't want to query the value first, change and update back.
I'm having a hard time figuring how to do this in a single query, please help, thanks!
if you are using JSONB, you can use the jsonb_set function
(table
.update()
.values(views=func.jsonb_set(table.c.views,
'{%s}' % '1002',
1))
.where(...))
if you are inserting from other column
(table
.update()
.values(views=func.jsonb_set(table.c.views,
'{%s}' % '1002',
other_table.c.other_column.cast(String).cast(JSONB)))
.where(...))
Refer to this answer for how to do it in SQL.
To do the same thing in Python (with PostgreSQL 9.5):
update().where(...)\
.values(views=cast(cast(u.c.views, JSONB)
.concat(func.jsonb_build_object('1002', 1)), JSON)
For PostgreSQL 9.3+, you'll have to create the function in PostgreSQL first, then:
update().where(...)\
.values(views=func.json_object_set_key(u.c.views, '1002', 1))
This way we can update new key-value pair in the views field.
from sqlalchemy import cast,func, JSON
from sqlalchemy.dialects.postgresql import JSONB
users.query.filter(users.c.loginId==loginId).update({users.data: cast(
cast(users.data, JSONB).concat(func.jsonb_build_object('1002', 1)), JSON)}, synchronize_session="fetch")
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)
I want to add a field to an existing mapped class, how would I update the sql table automatically. Does sqlalchemy provide a method to update the database with a new column, if a field is added to the class.
Sometimes Migrate is too much work - you just want to column automatically added when you run your changed code. So here is a function that does that.
Caveats: it pokes around in the SQLAlchemy internals and tends to require small changes every time SQLAlchemy undergoes a major revision. (There's probably a much better way of doing this - I am not a SQLAlchemy expert). It also doesn't handle constraints.
import logging
import re
import sqlalchemy
from sqlalchemy import MetaData, Table, exceptions
import sqlalchemy.engine.ddl
_new_sa_ddl = sqlalchemy.__version__.startswith('0.7')
def create_and_upgrade(engine, metadata):
"""For each table in metadata, if it is not in the database then create it.
If it is in the database then add any missing columns and warn about any columns
whose spec has changed"""
db_metadata = MetaData()
db_metadata.bind = engine
for model_table in metadata.sorted_tables:
try:
db_table = Table(model_table.name, db_metadata, autoload=True)
except exceptions.NoSuchTableError:
logging.info('Creating table %s' % model_table.name)
model_table.create(bind=engine)
else:
if _new_sa_ddl:
ddl_c = engine.dialect.ddl_compiler(engine.dialect, None)
else:
# 0.6
ddl_c = engine.dialect.ddl_compiler(engine.dialect, db_table)
# else:
# 0.5
# ddl_c = engine.dialect.schemagenerator(engine.dialect, engine.contextual_connect())
logging.debug('Table %s already exists. Checking for missing columns' % model_table.name)
model_columns = _column_names(model_table)
db_columns = _column_names(db_table)
to_create = model_columns - db_columns
to_remove = db_columns - model_columns
to_check = db_columns.intersection(model_columns)
for c in to_create:
model_column = getattr(model_table.c, c)
logging.info('Adding column %s.%s' % (model_table.name, model_column.name))
assert not model_column.constraints, \
'Arrrgh! I cannot automatically add columns with constraints to the database'\
'Please consider fixing me if you care!'
model_col_spec = ddl_c.get_column_specification(model_column)
sql = 'ALTER TABLE %s ADD %s' % (model_table.name, model_col_spec)
engine.execute(sql)
# It's difficult to reliably determine if the model has changed
# a column definition. E.g. the default precision of columns
# is None, which means the database decides. Therefore when I look at the model
# it may give the SQL for the column as INTEGER but when I look at the database
# I have a definite precision, therefore the returned type is INTEGER(11)
for c in to_check:
model_column = model_table.c[c]
db_column = db_table.c[c]
x = model_column == db_column
logging.debug('Checking column %s.%s' % (model_table.name, model_column.name))
model_col_spec = ddl_c.get_column_specification(model_column)
db_col_spec = ddl_c.get_column_specification(db_column)
model_col_spec = re.sub('[(][\d ,]+[)]', '', model_col_spec)
db_col_spec = re.sub('[(][\d ,]+[)]', '', db_col_spec)
db_col_spec = db_col_spec.replace('DECIMAL', 'NUMERIC')
db_col_spec = db_col_spec.replace('TINYINT', 'BOOL')
if model_col_spec != db_col_spec:
logging.warning('Column %s.%s has specification %r in the model but %r in the database' %
(model_table.name, model_column.name, model_col_spec, db_col_spec))
if model_column.constraints or db_column.constraints:
# TODO, check constraints
logging.debug('Column constraints not checked. I am too dumb')
for c in to_remove:
model_column = getattr(db_table.c, c)
logging.warning('Column %s.%s in the database is not in the model' % (model_table.name, model_column.name))
def _column_names(table):
# Autoloaded columns return unicode column names - make sure we treat all are equal
return set((unicode(i.name) for i in table.c))
SQLAlchemy itself doesn't support automatic updates of schema, but there is a third party SQLAlchemy Migrate tool to automate migrations. Look though "Database schema versioning workflow" chapter to see how it works.
Alembic is the latest package that offers migration of database.
See sqlalchemy docs regarding migration here.
# database.py has definition for engine.
# from sqlalchemy import create_engine
# engine = create_engine('mysql://......', convert_unicode=True)
from database import engine
from sqlalchemy import DDL
add_column = DDL('ALTER TABLE USERS ADD COLUMN city VARCHAR(60) AFTER email')
engine.execute(add_column)
It's possible to do with sqlalchemy-migrate but not actually use migrations:
sqlalchemy.MetaData(bind=dbinterface.db.engine)
table = sqlalchemy.schema.Table(table_name, meta_data)
try:
col = sqlalchemy.Column('column_name', sqlalchemy.String)
col.create(table)
except Exception as e:
print "Error adding column: {}".format(e)
To use with python 3 I needed sqlalchemy-migrate==0.12.0.
You can install 'DB Browser (SQLite)' and open your current database file and simple add/edit table in your database and save it, and run your app
(add script in your model after save above process)