Run `odoo-bin help`, you'll notice that some descriptions are missing,
this commit fixes that.
Run `odoo-bin shell --help`, you'll notice that the `usage:` line says
`odoo-bin [options]` instead of `odoo-bin shell [options]`. Other
commands that depend on the server cli are broken too. Fix those too.
closesodoo/odoo#121085
X-original-commit: 9c6bac741ff437564e7dbe4d0aa8dbd307b71f8d
Signed-off-by: Vincent Schippefilt (vsc) <vsc@odoo.com>
Signed-off-by: Julien Castiaux (juc) <juc@odoo.com>
This provides a new API for those operations, in order to make the
distinction between the use cases more explicit. The former API was
using obscure parameter combinations to correspond to various cases.
In the summary below, `fnames` is an iterable of field names. If the
parameter is not given, it means "all fields" in the given context.
Note that method recompute() is now mostly private, as it should not be
used in business code.
# process pending computations and updates
records.env.flush_all() # all fields of all models
records.flush_model(fnames) # the fields of all records of the model
records.flush_recordset(fnames) # the fields of the given records
# process pending computations, became non-public methods
records.env._recompute_all() # all fields of all models
records._recompute_model(fnames) # the fields of all records of the model
records._recompute_recordset(fnames) # the fields of the given records
# invalidate the cache of fields
records.env.invalidate_all() # all fields of all models
records.invalidate_model(fnames) # the fields of all records of the model
records.invalidate_recordset(fnames) # the fields of the given records
Part-of: odoo/odoo#87527
Profiling: creation of ir.profile records for each models population
Rollback: allow triggering multiple times the same population,
without any risk of records conflicts (& having to recreated a clean database)
Note: those two options are mostly recommended for small models population.
Indeed, profiling slows down the population, and large/medium population is
already quite slow for some models (and it seems that the rollback breaks as well
for some advanced models).
Part-of: odoo/odoo#85537
Refactor the Environments object into a Transaction object, which is
bound to one cursor, and is no longer shared among several cursors.
The following methods/properties have been changed:
- Environment.envs no longer works (because of the design change);
- Environment.manage() is deprecated (no longer useful);
- Environment.reset() is now an instance method;
- env.clear_upon_failure() is deprecated in favor of cr.savepoint().
closesodoo/odoo#75598
Related: odoo/enterprise#20451
Signed-off-by: Raphael Collet (rco) <rco@openerp.com>
Co-authored-by: Xavier Dollé <xdo@odoo.com>
Some use case like testing performance or upgrade scripts required a database
with prefilled data, covering basic corner cases. A solution can be to
create data a procedural way.
This commit proposes an API to easily populate a model, usually by giving a
list of possible values for each field or by giving a compute method that will
be based on raw values of other fields.
The basic way to define how to populate a new field is to override `_populate_factories`,
a method that returns a sequence of pairs `(field_name, factory)`.
The definition of a field is a "factory", a function that returns a neverending iterator
combining its value(s) with the values of the iterator given in parameter.
Some factory helpers are given in `tools.populate.py`:
- `iterate(vals, weighs)` ensures that one record is created for each value
by iterating on them, then resumes as `random.choice` on those vals following weights
once the first iteration is finished.
- `cartesian(vals, weights)` makes a cartesian product of its own values with the values
of its input iterator, then resumes as a randomized generator.
- `compute(function)` calls the given function with the current values dict and a random object,
and assigns the current field to the returned value.
- ...
Each iterator yields dictionaries of field values, and the factory should add a
value for the current field(s). The yielded dictionaries also contain a pseudo_field
`"__complete"`, that indicates whether this step is some randomized data
to reach the expected count of records. A falsy value indicates that the iterator
is still covering mandatory cases. This indicates whether a cartesian product is
finished, or an `iterate` has consumed all its values.
The order of the factories is quite important, since some computed fields may need
other fields to be defined, and `cartesian` factories should always be at the beginning
to avoid having too many combination. That is why the factories are given as a list of
pairs instead of a dictionary; this makes it easier to insert elements at any place.
Example:
field A: cartesian([T, F])
field B: cartesian([0, 1])
field C: iterate([a, b, c, d, e])
field D: compute(1-B)
_c is shortcut for __complete
_ is a random value, or result of a random value
```
iter | root | field A | field B | field C | field D | result
0 {_c:F} {... A:T} {... B:0} {...C:a} {...D:1} T,0,a,1 complete:False
{... B:1} {...C:b} {...D:0} T,1,b,0 complete:False
{... A:F} {... B:0} {...C:c} {...D:1} F,0,c,1 complete:False
{... B:1} {...C:d} {...D:0} F,1,d,0 complete:False
1 {_c:T} {... A:_} {... B:_} {...C:e,_c:F} {...D:_} _,_,e,_ complete:False
2 {_c:T} {... A:_} {... B:_} {...C:_} {...D:_} _,_,_,_ complete:True
```
X-original-commit: 4c0182dafa584853ed83a166096f45c33c06a245
Julien Castiaux