When we group by date with DST change within a range, we could get a
reocrd inside two date range grouping, or inside no grouping.
This is because we computed range just with [+ 1 month], so we possibly
had these ranges (in UTC):
- October 2019 : [('datetime', '>=', '2019-10-01 02:00:00')
('datetime', '<', '2019-11-01 02:00:00')]
- November 2019 : [('datetime', '>=', '2019-11-01 01:00:00')
('datetime', '<', '2019-12-01 01:00:00')]
So a record on 2019-11-01 01:30:00 would be both inside October and
November.
This happen because the DST is removed on happen on 27 October 2019 and
this was not taken into account when computing the end of the range.
With this changeset, for the given example aboth, we will have:
- October 2019 : [('datetime', '>=', '2019-10-01 02:00:00')
('datetime', '<', '2019-11-01 01:00:00')]
Added test without the change fails with "AssertionError: Lists differ"
because:
- "Q1 2019" finished on 17:00:00 instead of 16:00:00
- "Q3 2019" finished on 16:00:00 instead of 17:00:00
opw-2278829
closes#54056closesodoo/odoo#54345
Note: maxDiff added for test to work in 13.0
X-original-commit: af5d03de28fa300ebbaa37a3d226b41051ebdf0f
Signed-off-by: Nicolas Lempereur (nle) <nle@odoo.com>
Replaces the auto_join scheme which is pretty fast but doesn't quite
work (it's *completely* broken for read_group) by a subquery which is
slower but has the same semantics as the ORM version.
Ideally we'd use `EXISTS (select 1 from ...)` but that has no support
inside the SQL compiler right now, so use `id in (select inverse_field
from ...)`.
Here are some measures of a `read_group` on a simple object with lines
filtered on line values, similar to
read_group([('order_line.product_uom', '=', xxx)],
fields=['total_amount'], groupby=['user_id'])
+-------+-------+-------+--------+
| | ORM | join |subquery|
+-------+-------+-------+--------+
| large | 160 | 10 | 20 |
+-------+-------+-------+--------+
| many | 36000 | 50 | 180 |
+-------+-------+-------+--------+
* values of data fields (filtering, grouping and aggregating) randomly
picked between 10 different values
* "large" is 1000 objects with 1000~15000 lines each
* "many" is 1000000 objects with 1~40 lines each
closesodoo/odoo#48494
Signed-off-by: Raphael Collet (rco) <rco@openerp.com>
Purpose
=======
The current kanban view is messy. It is difficult to identify which
apps are installed or not. The user can completely miss a module
that might have interested him. A search panel would make things way
more readable.
closesodoo/odoo#44401
Taskid: 2181557
Related: odoo/enterprise#8144
Related: odoo/upgrade#879
Signed-off-by: Yannick Tivisse (yti) <yti@odoo.com>
Purpose of this commit is to give description more "business oriented"
because those descriptions appears in Odoo Studio which is supposed to be used by end users, not only by developers.
Related Task ID : 37311
This commit add an extra parameter 'fill_temporal' to read_group which allows
the orm to add missing groups for date intervals. This is useful for charts.
Suppose that we are in a use case where data are grouped by a date fields
(typically months but it could be another interval) and displayed in a Bar Chart
or a Line Char.
Let's says a request has to group records by month for August, September
and ...December. If we don't changed anything, we would get a Bar Chart
looking like this :
___
___ | |
| | | |
| | ___ | |
| || || |
|___||___||___|
Aug Sep D
December follows directly after September, it can be unintuitive for the
user, so we change that. We add some fake records for each missing months
between the earliest and the lastest date of the result
___
___ | |
| | | |
| | ___ | |
| || | | |
|___||___| ___ ___ |___|
Aug Sep Oct Nov Dec
This commit is part of task #1835644
The caller of `read_group` can now provide the aggregating function to use for
a given field:
# set aggregating operator for fields 'foo' and 'bar'
model.read_group(domain, ['foo:sum', 'bar:avg'], ...)
One can also aggregate the same field several times, by giving a specific
output name for each:
# aggregate 'foo' with both 'min' and 'max'
model.read_group(domain, ['foomin:min(foo)', 'foomax:max(foo)'], ...)
The attribute `group_expand` allows to reorder and add empty groups to the
result of `read_group`. Enable this feature for other fields than many2one
fields.
Nicolas Lempereur