[sqlalchemy] Re: Is it possible to define multiple model objects that refer to the same table?
Thanks so much! Your pointers were exactly what I needed,
specifically the bit which led me to discover exclude_properties.
I'll leave my working code here in case it ever helps anybody else
out:
from sqlalchemy import Column, Date, Enum, Integer, String, Table,
create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import ColumnProperty, sessionmaker
from sqlalchemy.orm.mapper import class_mapper
engine = create_engine('mysql://user:password@localhost/
issue_tracker')
Session = sessionmaker(bind=engine)
Base = declarative_base()
tables = {'issue_type':
Table('issue_type', Base.metadata,
Column('id', Integer, primary_key=True),
Column('type', Enum('Bug', 'Feature',
'Improvement', 'One-Time Task')),
Column('created', Date),
Column('num_visits', Integer)),
'issue_type_label':
Table('issue_type_label', Base.metadata,
Column('id', Integer, primary_key=True),
Column('type', Enum('Bug', 'Feature',
'Improvement', 'One-Time Task')),
Column('label_id', String),
Column('created', Date),
Column('num_visits', Integer))}
def get_columns(model):
return [x.key for x in class_mapper(model).iterate_properties if
isinstance(x, ColumnProperty)]
class IssueType(Base):
__table__ = tables['issue_type']
class IssueLabel(Base):
__table__ = tables['issue_type_label']
__mapper_args__ = {'exclude_properties': ['type']}
class IssueTypeLabel(Base):
__table__ = tables['issue_type_label']
print issue type:, get_columns(IssueType)
print issue label:, get_columns(IssueLabel)
print issue type label:, get_columns(IssueTypeLabel)
This code correctly prints the following:
issue type: ['id', 'type', 'created', 'num_visits']
issue label: ['id', 'label_id', 'created', 'num_visits']
issue type label: ['id', 'type', 'label_id', 'created',
'num_visits']
On Nov 16, 8:49 pm, Michael Bayer mike...@zzzcomputing.com wrote:
On Nov 16, 2012, at 2:59 PM, Rob Crowell wrote:
Thanks for the help so far Michael! I can explain a little more about
what I'm trying to do (I'm using a fictional application here but I
think it pretty accurately translates into my actual application).
BACKGROUND
--
Let's say I'm writing an issue tracking application. Each issue that
we're tracking has a type (an issue must have exactly one type), and
each issue may have an unlimited number of user-provided labels.
Each day, people browse our issue tracker and each time they do they
generate a page view on the issue. Here's an example of one day's
worth of data:
IssueA: Views: 1, Type: Bug, Labels: [login-page (id=1),
show-stopper (id=2)]
IssueB: Views: 20, Type: One-Time Task, Labels: [disk-full
(id=3), show-stopper (id=2)]
IssueC: Views: 300, Type: Bug, Labels: [login-page (id=1)]
The BigCo. I'm working for is very interested in knowing which issues
are read by the most people, and they need the ability to generate
reports sliced by arbitrary date ranges. However, we can tolerate a
day delay, so we are writing summary tables each night. Two of these
summary tables are aggregated by either issue type or label, and we
also write a third table that can be used to drill-down and see page
visits bucketed by both type and label:
CREATE TABLE `issue_type` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_type_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_visits` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
So we'd run these insert statements at midnight:
INSERT INTO issue_type (created, type, num_visits) VALUES
(2012-11-15, Bug, 301),
(2012-11-15, One-Time Task, 20);
INSERT INTO issue_labels (created, label_id, num_visits) VALUES
(2012-11-15, 1, 301),
(2012-11-15, 2, 21),
(2012-11-15, 3, 20);
INSERT INTO issue_type_label (created, type, label_id, num_visits)
VALUES
(2012-11-15, Bug, 1, 301),
(2012-11-15, Bug, 2, 1),
(2012-11-15, One-Time Task, 3, 20),
(2012-11-15, One-Time Task, 2, 20);
Now when we want to generate the summary reports, we query one of the
first two tables (if we're generating a report aggregated by issue
type we hit issue_type, if we're
[sqlalchemy] Re: Is it possible to define multiple model objects that refer to the same table?
On Nov 15, 10:48 pm, Michael Bayer mike...@zzzcomputing.com wrote:
On Nov 15, 2012, at 7:33 PM, Rob Crowell wrote:
Sorry, that got cut off at the end.
class IssueTag(Base):
__tablename__ = 'issue_user_tag'
sqlalchemy.exc.InvalidRequestError: Table 'issue_user_tag' is already
defined for this MetaData instance. Specify 'extend_existing=True' to
redefine options and columns on an existing Table object.
On Thursday, November 15, 2012 7:32:29 PM UTC-5, Rob Crowell wrote:
I'm working with a denormalized cache schema, and I've run into a situation
where it would be helpful to be able to create multiple classes that extend
Base but refer to the same __tablename__. Is this possible to do? I am
getting this Exception:
sqlalchemy.exc.InvalidRequestError: Table '[tablename]' is already
defined for this MetaData instance. Specify 'extend_existing=True' to
redefine options and columns on an existing Table object.
For a little more insight, we have some attributes that always have exactly
one value (user who created the issue), and other attributes that can have
1 or more values (user-defined tags for the issue). If we were being
exhaustive, we would create two cached tables for our issues since
sometimes we want to display recent issues sometimes by user and sometimes
by tag:
* issue_user
* issue_tag
However, we can get away with writing just one table and querying it with
an appropriate group_by(user_id) to achieve the same end as having 2
tables. Since my application should behave as if there were 2 separate
cache tables (and I'd like to keep open the option of adding two separate
cache tables in the future), I would like to have 2 different Base classes
representing the two ways in which we would query the table. The obvious
way of doing this doesn't work:
class IssueUser(Base):
__tablename__ = 'issue_user_tag'
class IssueTag(Base):
--
two^H^H^H three ways:
1. map to a Table:
mytable = Table(mytable, Base.metadata, Column(...))
class A(Base):
__table__ = mytable
class B(Base):
__table__ = mytable
1a: variant of 1, map A as you did but use __table__ on B
class A(Base):
__tablename__ = 'mytable'
x = Column(...)
class B(Base):
__table__ = A.__table__
2. use single table inheritance with no discriminator
class MyTable(Base):
__tablename__ = 'mytable'
class A(MyTable):
#
class B(MyTable):
# ...
I don't have an understanding of your querying situation yet, discriminating
on group_by() seems a little strange as group_by() is only intended to be
used to group for aggregates, but #1, #1a or #2 should fit the bill.
Thanks for the help so far Michael! I can explain a little more about
what I'm trying to do (I'm using a fictional application here but I
think it pretty accurately translates into my actual application).
BACKGROUND
--
Let's say I'm writing an issue tracking application. Each issue that
we're tracking has a type (an issue must have exactly one type), and
each issue may have an unlimited number of user-provided labels.
Each day, people browse our issue tracker and each time they do they
generate a page view on the issue. Here's an example of one day's
worth of data:
IssueA: Views: 1, Type: Bug, Labels: [login-page (id=1),
show-stopper (id=2)]
IssueB: Views: 20, Type: One-Time Task, Labels: [disk-full
(id=3), show-stopper (id=2)]
IssueC: Views: 300, Type: Bug, Labels: [login-page (id=1)]
The BigCo. I'm working for is very interested in knowing which issues
are read by the most people, and they need the ability to generate
reports sliced by arbitrary date ranges. However, we can tolerate a
day delay, so we are writing summary tables each night. Two of these
summary tables are aggregated by either issue type or label, and we
also write a third table that can be used to drill-down and see page
visits bucketed by both type and label:
CREATE TABLE `issue_type` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_type_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_visits` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
So we'd run these insert statements at midnight:
INSERT INTO issue_type (created, type, num_visits) VALUES
(2012-11-15, Bug, 301),
(2012-11-15, One-Time Task, 20);
INSERT INTO issue_labels (created, label_id,
Re: [sqlalchemy] Re: Is it possible to define multiple model objects that refer to the same table?
On Nov 16, 2012, at 2:59 PM, Rob Crowell wrote:
Thanks for the help so far Michael! I can explain a little more about
what I'm trying to do (I'm using a fictional application here but I
think it pretty accurately translates into my actual application).
BACKGROUND
--
Let's say I'm writing an issue tracking application. Each issue that
we're tracking has a type (an issue must have exactly one type), and
each issue may have an unlimited number of user-provided labels.
Each day, people browse our issue tracker and each time they do they
generate a page view on the issue. Here's an example of one day's
worth of data:
IssueA: Views: 1, Type: Bug, Labels: [login-page (id=1),
show-stopper (id=2)]
IssueB: Views: 20, Type: One-Time Task, Labels: [disk-full
(id=3), show-stopper (id=2)]
IssueC: Views: 300, Type: Bug, Labels: [login-page (id=1)]
The BigCo. I'm working for is very interested in knowing which issues
are read by the most people, and they need the ability to generate
reports sliced by arbitrary date ranges. However, we can tolerate a
day delay, so we are writing summary tables each night. Two of these
summary tables are aggregated by either issue type or label, and we
also write a third table that can be used to drill-down and see page
visits bucketed by both type and label:
CREATE TABLE `issue_type` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_watchers` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
CREATE TABLE `issue_type_label` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`created` datetime NOT NULL,
`type` enum('Bug','Feature','Improvement','One-Time Task') NOT NULL,
`label_id` int(10) unsigned NOT NULL,
`num_visits` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`)
)
So we'd run these insert statements at midnight:
INSERT INTO issue_type (created, type, num_visits) VALUES
(2012-11-15, Bug, 301),
(2012-11-15, One-Time Task, 20);
INSERT INTO issue_labels (created, label_id, num_visits) VALUES
(2012-11-15, 1, 301),
(2012-11-15, 2, 21),
(2012-11-15, 3, 20);
INSERT INTO issue_type_label (created, type, label_id, num_visits)
VALUES
(2012-11-15, Bug, 1, 301),
(2012-11-15, Bug, 2, 1),
(2012-11-15, One-Time Task, 3, 20),
(2012-11-15, One-Time Task, 2, 20);
Now when we want to generate the summary reports, we query one of the
first two tables (if we're generating a report aggregated by issue
type we hit issue_type, if we're generating a report aggregated by
label we hit issue_label), and when we want to run a drill-down query
both both type and label, we hit issue_type_label:
# broken down by type
SELECT type, SUM(num_visits) FROM issue_type WHERE created =
2012-11-01 AND created = 2012-11-16 GROUP BY type;
# broken down by label
SELECT label_id, SUM(num_visits) FROM issue_label WHERE created =
2012-11-01 AND created = 2012-11-16 GROUP BY label_id;
# broken down by both type and label
SELECT type, label_id, SUM(num_visits) FROM issue_type_label WHERE
created = 2012-11-01 AND created = 2012-11-16 GROUP BY type,
label_id;
This works fine and is very fast for our application. However, it's a
bit redundant since each issue has exactly one issue type, so we can
safely ignore it when generating the label summary report. So really,
we can get away with not having the issue_label table at all, and just
run this instead (we must continue to have the issue_type table
however, since a single issue can have many labels or none at all):
# broken down by label
SELECT label_id, SUM(num_visits) FROM issue_type_label WHERE
created = 2012-11-01 AND created = 2012-11-16 GROUP BY label_id;
THE ISSUE
-
In reality, we have many types of fields that we generate reports on
(not just type and label), so we have more than a dozen of these
aggregate tables rolled up by different sets of fields. While porting
our data access layer to SQLAlchemy (we have a separate process to
write these tables which we aren't going to move to SQLAlchemy), I've
created a bunch of functions that use reflection on the various Model
objects I've built to figure out what columns we need to select.
Each column that we don't want to GROUP BY or filter out with a WHERE
clause gets wrapped by func.sum() and passed to a call to
session.query(). My columns are very consistently named so I have
automated almost all of this using object reflection, which lets my
code populate which columns to select, group by, and sum on
automatically. I really don't want to write a custom call to query()
for each table type that
Re: [sqlalchemy] Re: Is it possible to define multiple model objects that refer to the same table?
On Nov 15, 2012, at 7:33 PM, Rob Crowell wrote: Sorry, that got cut off at the end. class IssueTag(Base): __tablename__ = 'issue_user_tag' sqlalchemy.exc.InvalidRequestError: Table 'issue_user_tag' is already defined for this MetaData instance. Specify 'extend_existing=True' to redefine options and columns on an existing Table object. On Thursday, November 15, 2012 7:32:29 PM UTC-5, Rob Crowell wrote: I'm working with a denormalized cache schema, and I've run into a situation where it would be helpful to be able to create multiple classes that extend Base but refer to the same __tablename__. Is this possible to do? I am getting this Exception: sqlalchemy.exc.InvalidRequestError: Table '[tablename]' is already defined for this MetaData instance. Specify 'extend_existing=True' to redefine options and columns on an existing Table object. For a little more insight, we have some attributes that always have exactly one value (user who created the issue), and other attributes that can have 1 or more values (user-defined tags for the issue). If we were being exhaustive, we would create two cached tables for our issues since sometimes we want to display recent issues sometimes by user and sometimes by tag: * issue_user * issue_tag However, we can get away with writing just one table and querying it with an appropriate group_by(user_id) to achieve the same end as having 2 tables. Since my application should behave as if there were 2 separate cache tables (and I'd like to keep open the option of adding two separate cache tables in the future), I would like to have 2 different Base classes representing the two ways in which we would query the table. The obvious way of doing this doesn't work: class IssueUser(Base): __tablename__ = 'issue_user_tag' class IssueTag(Base): -- two^H^H^H three ways: 1. map to a Table: mytable = Table(mytable, Base.metadata, Column(...)) class A(Base): __table__ = mytable class B(Base): __table__ = mytable 1a: variant of 1, map A as you did but use __table__ on B class A(Base): __tablename__ = 'mytable' x = Column(...) class B(Base): __table__ = A.__table__ 2. use single table inheritance with no discriminator class MyTable(Base): __tablename__ = 'mytable' class A(MyTable): # class B(MyTable): # ... I don't have an understanding of your querying situation yet, discriminating on group_by() seems a little strange as group_by() is only intended to be used to group for aggregates, but #1, #1a or #2 should fit the bill. You received this message because you are subscribed to the Google Groups sqlalchemy group. To view this discussion on the web visit https://groups.google.com/d/msg/sqlalchemy/-/pPc-8bqYaSUJ. To post to this group, send email to sqlalchemy@googlegroups.com. To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en. -- You received this message because you are subscribed to the Google Groups sqlalchemy group. To post to this group, send email to sqlalchemy@googlegroups.com. To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en.
