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New in version 8.0: This page documents the New API added in Odoo 8.0 which should be the primary development API going forward. It also provides information about porting from or bridging with the “old API” of versions 7 and earlier, but does not explicitly document that API. See the old documentation for that.

Interaction with models and records is performed through recordsets, a sorted set of records of the same model.


contrary to what the name implies, it is currently possible for recordsets to contain duplicates. This may change in the future.

Methods defined on a model are executed on a recordset, and their self is a recordset:

class AModel(models.Model):
    _name = 'a.model'
    def a_method(self):
        # self can be anywhere between 0 records and all records in the
        # database

Iterating on a recordset will yield new sets of a single record (“singletons”), much like iterating on a Python string yields strings of a single characters:

def do_operation(self):
    print self # => a.model(1, 2, 3, 4, 5)
    for record in self:
        print record # => a.model(1), then a.model(2), then a.model(3), ...

Field access

Recordsets provide an “Active Record” interface: model fields can be read and written directly from the record, but only on singletons (single-record recordsets). Setting a field’s value triggers an update to the database:

>>> record.name
Example Name
>>> record.company_id.name
Company Name
>>> record.name = "Bob"

Trying to read or write a field on multiple records will raise an error.

Accessing a relational field (Many2one, One2many, Many2many) always returns a recordset, empty if the field is not set.


each assignment to a field triggers a database update, when setting multiple fields at the same time or setting fields on multiple records (to the same value), use write():

# 3 * len(records) database updates
for record in records:
    record.a = 1
    record.b = 2
    record.c = 3

# len(records) database updates
for record in records:
    record.write({'a': 1, 'b': 2, 'c': 3})

# 1 database update
records.write({'a': 1, 'b': 2, 'c': 3})

Set operations

Recordsets are immutable, but sets of the same model can be combined using various set operations, returning new recordsets. Set operations do not preserve order.

  • record in set returns whether record (which must be a 1-element recordset) is present in set. record not in set is the inverse operation
  • set1 | set2 returns the union of the two recordsets, a new recordset containing all records present in either source
  • set1 & set2 returns the intersection of two recordsets, a new recordset containing only records present in both sources
  • set1 - set2 returns a new recordset containing only records of set1 which are not in set2

Other recordset operations

Recordsets are iterable so the usual Python tools are available for transformation (map(), sorted(), ifilter(), ...) however these return either a list or an iterator, removing the ability to call methods on their result, or to use set operations.

Recordsets therefore provide these operations returning recordsets themselves (when possible):


returns a recordset containing only records satisfying the provided predicate function. The predicate can also be a string to filter by a field being true or false:

# only keep records whose company is the current user's
records.filtered(lambda r: r.company_id == user.company_id)

# only keep records whose partner is a company

returns a recordset sorted by the provided key function. If no key is provided, use the model’s default sort order:

# sort records by name
records.sorted(key=lambda r: r.name)

applies the provided function to each record in the recordset, returns a recordset if the results are recordsets:

# returns a list of summing two fields for each record in the set
records.mapped(lambda r: r.field1 + r.field2)

The provided function can be a string to get field values:

# returns a list of names

# returns a recordset of partners

# returns the union of all partner banks, with duplicates removed


The Environment stores various contextual data used by the ORM: the database cursor (for database queries), the current user (for access rights checking) and the current context (storing arbitrary metadata). The environment also stores caches.

All recordsets have an environment, which is immutable, can be accessed using env and gives access to the current user (user), the cursor (cr) or the context (context):

>>> records.env
<Environment object ...>
>>> records.env.user
>>> records.env.cr
<Cursor object ...)

When creating a recordset from an other recordset, the environment is inherited. The environment can be used to get an empty recordset in an other model, and query that model:

>>> self.env['res.partner']
>>> self.env['res.partner'].search([['is_company', '=', True], ['customer', '=', True]])
res.partner(7, 18, 12, 14, 17, 19, 8, 31, 26, 16, 13, 20, 30, 22, 29, 15, 23, 28, 74)

Altering the environment

The environment can be customized from a recordset. This returns a new version of the recordset using the altered environment.


creates a new environment with the provided user set, uses the administrator if none is provided (to bypass access rights/rules in safe contexts), returns a copy of the recordset it is called on using the new environment:

# create partner object as administrator
env['res.partner'].sudo().create({'name': "A Partner"})

# list partners visible by the "public" user
public = env.ref('base.public_user')
  1. can take a single positional parameter, which replaces the current environment’s context
  2. can take any number of parameters by keyword, which are added to either the current environment’s context or the context set during step 1
# look for partner, or create one with specified timezone if none is
# found
replaces the existing environment entirely

Common ORM methods


Takes a search domain, returns a recordset of matching records. Can return a subset of matching records (offset and limit parameters) and be ordered (order parameter):

>>> # searches the current model
>>> self.search([('is_company', '=', True), ('customer', '=', True)])
res.partner(7, 18, 12, 14, 17, 19, 8, 31, 26, 16, 13, 20, 30, 22, 29, 15, 23, 28, 74)
>>> self.search([('is_company', '=', True)], limit=1).name


to just check if any record matches a domain, or count the number of records which do, use search_count()


Takes a number of field values, and returns a recordset containing the record created:

>>> self.create({'name': "New Name"})

Takes a number of field values, writes them to all the records in its recordset. Does not return anything:

self.write({'name': "Newer Name"})

Takes a database id or a list of ids and returns a recordset, useful when record ids are obtained from outside Odoo (e.g. round-trip through external system) or when calling methods in the old API:

>>> self.browse([7, 18, 12])
res.partner(7, 18, 12])

Returns a new recordset containing only the records which exist in the database. Can be used to check whether a record (e.g. obtained externally) still exists:

if not record.exists():
    raise Exception("The record has been deleted")

or after calling a method which could have removed some records:

# only keep records which were not deleted
records = records.exists()

Environment method returning the record matching a provided external id:

>>> env.ref('base.group_public')

checks that the recordset is a singleton (only contains a single record), raises an error otherwise:

# is equivalent to but clearer than:
assert len(records) == 1, "Expected singleton"

Creating Models

Model fields are defined as attributes on the model itself:

from openerp import models, fields
class AModel(models.Model):
    _name = 'a.model.name'

    field1 = fields.Char()


this means you can not define a field and a method with the same name, they will conflict

By default, the field’s label (user-visible name) is a capitalized version of the field name, this can be overridden with the string parameter:

field2 = fields.Integer(string="an other field")

For the various field types and parameters, see the fields reference.

Default values are defined as parameters on fields, either a value:

a_field = fields.Char(default="a value")

or a function called to compute the default value, which should return that value:

a_field = fields.Char(default=compute_default_value)
def compute_default_value(self):
    return self.get_value()

Computed fields

Fields can be computed (instead of read straight from the database) using the compute parameter. It must assign the computed value to the field. If it uses the values of other fields, it should specify those fields using depends():

from openerp import api
total = fields.Float(compute='_compute_total')

@api.depends('value', 'tax')
def _compute_total(self):
    for record in self:
        record.total = record.value + record.value * record.tax
  • dependencies can be dotted paths when using sub-fields:

    def _compute_total(self):
        for record in self:
            record.total = sum(line.value for line in record.line_ids)
  • computed fields are not stored by default, they are computed and returned when requested. Setting store=True will store them in the database and automatically enable searching

  • searching on a computed field can also be enabled by setting the search parameter. The value is a method name returning a Domains:

    upper_name = field.Char(compute='_compute_upper', search='_search_upper')
    def _search_upper(self, operator, value):
        if operator == 'like':
            operator = 'ilike'
        return [('name', operator, value)]
  • to allow setting values on a computed field, use the inverse parameter. It is the name of a function reversing the computation and setting the relevant fields:

    document = fields.Char(compute='_get_document', inverse='_set_document')
    def _get_document(self):
        for record in self:
            with open(record.get_document_path) as f:
                record.document = f.read()
    def _set_document(self):
        for record in self:
            if not record.document: continue
            with open(record.get_document_path()) as f:
  • multiple fields can be computed at the same time by the same method, just use the same method on all fields and set all of them:

    discount_value = fields.Float(compute='_apply_discount')
    total = fields.Float(compute='_apply_discount')
    @depends('value', 'discount')
    def _apply_discount(self):
        for record in self:
            # compute actual discount from discount percentage
            discount = self.value * self.discount
            self.discount_value = discount
            self.total = self.value - discount

onchange: updating UI on the fly

When a user changes a field’s value in a form (but hasn’t saved the form yet), it can be useful to automatically update other fields based on that value e.g. updating a final total when the tax is changed or a new invoice line is added.

  • computed fields are automatically checked and recomputed, they do not need an onchange

  • for non-computed fields, the onchange() decorator is used to provide new field values:

    @api.onchange('field1', 'field2') # if these fields are changed, call method
    def check_change(self):
        if self.field1 < self.field2:
            self.field3 = True

    the changes performed during the method are then sent to the client program and become visible to the user

  • Both computed fields and new-API onchanges are automatically called by the client without having to add them in views

  • It is possible to suppress the trigger from a specific field by adding on_change="0" in a view:

    <field name="name" on_change="0"/>

    will not trigger any interface update when the field is edited by the user, even if there are function fields or explicit onchange depending on that field.


onchange methods work on virtual records assignment on these records is not written to the database, just used to know which value to send back to the client

Low-level SQL

The cr attribute on environments is the cursor for the current database transaction and allows executing SQL directly, either for queries which are difficult to express using the ORM (e.g. complex joins) or for performance reasons:

self.env.cr.execute("some_sql", param1, param2, param3)

Because models use the same cursor and the Environment holds various caches, these caches must be invalidated when altering the database in raw SQL, or further uses of models may become incoherent. It is necessary to clear caches when using CREATE, UPDATE or DELETE in SQL, but not SELECT (which simply reads the database).

Clearing caches can be performed using the invalidate_all() method of the Environment object.

Compatibility between new API and old API

Odoo is currently transitioning from an older (less regular) API, it can be necessary to manually bridge from one to the other manually:

  • RPC layers (both XML-RPC and JSON-RPC) are expressed in terms of the old API, methods expressed purely in the new API are not available over RPC
  • overridable methods may be called from older pieces of code still written in the old API style

The big differences between the old and new APIs are:

  • values of the Environment (cursor, user id and context) are passed explicitly to methods instead
  • record data (ids) are passed explicitly to methods, and possibly not passed at all
  • methods tend to work on lists of ids instead of recordsets

By default, methods are assumed to use the new API style and are not callable from the old API style.


calls from the new API to the old API are bridged

when using the new API style, calls to methods defined using the old API are automatically converted on-the-fly, there should be no need to do anything special:

>>> # method in the old API style
>>> def old_method(self, cr, uid, ids, context=None):
...    print ids

>>> # method in the new API style
>>> def new_method(self):
...     # system automatically infers how to call the old-style
...     # method from the new-style method
...     self.old_method()

>>> env[model].browse([1, 2, 3, 4]).new_method()
[1, 2, 3, 4]

Two decorators can expose a new-style method to the old API:


the method is exposed as not using ids, its recordset will generally be empty. Its “old API” signature is cr, uid, *arguments, context:

def some_method(self, a_value):
# can be called as
old_style_model.some_method(cr, uid, a_value, context=context)

the method is exposed as taking a list of ids (possibly empty), its “old API” signature is cr, uid, ids, *arguments, context:

def some_method(self, a_value):
# can be called as
old_style_model.some_method(cr, uid, [id1, id2], a_value, context=context)

Because new-style APIs tend to return recordsets and old-style APIs tend to return lists of ids, there is also a decorator managing this:


the function is assumed to return a recordset, the first parameter should be the name of the recordset’s model or self (for the current model).

No effect if the method is called in new API style, but transforms the recordset into a list of ids when called from the old API style:

>>> @api.multi
... @api.returns('self')
... def some_method(self):
...     return self
>>> new_style_model = env['a.model'].browse(1, 2, 3)
>>> new_style_model.some_method()
a.model(1, 2, 3)
>>> old_style_model = pool['a.model']
>>> old_style_model.some_method(cr, uid, [1, 2, 3], context=context)
[1, 2, 3]

Model Reference

Method decorators


Basic fields

Relational fields

Inheritance and extension

Odoo provides three different mechanisms to extend models in a modular way:

  • creating a new model from an existing one, adding new information to the copy but leaving the original module as-is
  • extending models defined in other modules in-place, replacing the previous version
  • delegating some of the model’s fields to records it contains

Classical inheritance

When using the _inherit and _name attributes together, Odoo creates a new model using the existing one (provided via _inherit) as a base. The new model gets all the fields, methods and meta-information (defaults & al) from its base.

class Inheritance0(models.Model):
    _name = 'inheritance.0'

    name = fields.Char()

    def call(self):
        return self.check("model 0")

    def check(self, s):
        return "This is {} record {}".format(s, self.name)

class Inheritance1(models.Model):
    _name = 'inheritance.1'
    _inherit = 'inheritance.0'

    def call(self):
        return self.check("model 1")

and using them:

        a = env['inheritance.0'].create({'name': 'A'})
        b = env['inheritance.1'].create({'name': 'B'})

will yield:

        This is model 0 record A
        This is model 1 record B

the second model has inherited from the first model’s check method and its name field, but overridden the call method, as when using standard Python inheritance.


When using _inherit but leaving out _name, the new model replaces the existing one, essentially extending it in-place. This is useful to add new fields or methods to existing models (created in other modules), or to customize or reconfigure them (e.g. to change their default sort order):

class Extension0(models.Model):
    _name = 'extension.0'

    name = fields.Char(default="A")

class Extension1(models.Model):
    _inherit = 'extension.0'

    description = fields.Char(default="Extended")
        record = env['extension.0'].create({})

will yield:

        {'name': "A", 'description': "Extended"}


it will also yield the various automatic fields unless they’ve been disabled


The third inheritance mechanism provides more flexibility (it can be altered at runtime) but less power: using the _inherits a model delegates the lookup of any field not found on the current model to “children” models. The delegation is performed via Reference fields automatically set up on the parent model:

class Child0(models.Model):
    _name = 'delegation.child0'

    field_0 = fields.Integer()

class Child1(models.Model):
    _name = 'delegation.child1'

    field_1 = fields.Integer()

class Delegating(models.Model):
    _name = 'delegation.parent'

    _inherits = {
        'delegation.child0': 'child0_id',
        'delegation.child1': 'child1_id',

    child0_id = fields.Many2one('delegation.child0', required=True, ondelete='cascade')
    child1_id = fields.Many2one('delegation.child1', required=True, ondelete='cascade')
        record = env['delegation.parent'].create({
            'child0_id': env['delegation.child0'].create({'field_0': 0}).id,
            'child1_id': env['delegation.child1'].create({'field_1': 1}).id,

will result in:


and it’s possible to write directly on the delegated field:

        record.write({'field_1': 4})


when using delegation inheritance, methods are not inherited, only fields


A domain is a list of criteria, each criterion being a triple (either a list or a tuple) of (field_name, operator, value) where:

field_name (str)
a field name of the current model, or a relationship traversal through a Many2one using dot-notation e.g. 'street' or 'partner_id.country'
operator (str)

an operator used to compare the field_name with the value. Valid operators are:

equals to
not equals to
greater than
greater than or equal to
less than
less than or equal to
unset or equals to (returns true if value is either None or False, otherwise behaves like =)
matches field_name against the value pattern. An underscore _ in the pattern stands for (matches) any single character; a percent sign % matches any string of zero or more characters.
matches field_name against the %value% pattern. Similar to =like but wraps value with ‘%’ before matching
not like
doesn’t match against the %value% pattern
case insensitive like
not ilike
case insensitive not like
case insensitive =like
is equal to any of the items from value, value should be a list of items
not in
is unequal to all of the items from value

is a child (descendant) of a value record.

Takes the semantics of the model into account (i.e following the relationship field named by _parent_name).

variable type, must be comparable (through operator) to the named field

Domain criteria can be combined using logical operators in prefix form:

logical AND, default operation to combine criteria following one another. Arity 2 (uses the next 2 criteria or combinations).
logical OR, arity 2.

logical NOT, arity 1.


Mostly to negate combinations of criteria

Individual criterion generally have a negative form (e.g. = -> !=, < -> >=) which is simpler than negating the positive.


To search for partners named ABC, from belgium or germany, whose language is not english:


This domain is interpreted as:

    (name is 'ABC')
AND (language is NOT english)
AND (country is Belgium OR Germany)

Porting from the old API to the new API

  • bare lists of ids are to be avoided in the new API, use recordsets instead

  • methods still written in the old API should be automatically bridged by the ORM, no need to switch to the old API, just call them as if they were a new API method. See Automatic bridging of old API methods for more details.

  • search() returns a recordset, no point in e.g. browsing its result

  • fields.related and fields.function are replaced by using a normal field type with either a related= or a compute= parameter

  • depends() on compute= methods must be complete, it must list all the fields and sub-fields which the compute method uses. It is better to have too many dependencies (will recompute the field in cases where that is not needed) than not enough (will forget to recompute the field and then values will be incorrect)

  • remove all onchange methods on computed fields. Computed fields are automatically re-computed when one of their dependencies is changed, and that is used to auto-generate onchange by the client

  • the decorators model() and multi() are for bridging when calling from the old API context, for internal or pure new-api (e.g. compute) they are useless

  • remove _default, replace by default= parameter on corresponding fields

  • if a field’s string= is the titlecased version of the field name:

    name = fields.Char(string="Name")

    it is useless and should be removed

  • the multi= parameter does not do anything on new API fields use the same compute= methods on all relevant fields for the same result

  • provide compute=, inverse= and search= methods by name (as a string), this makes them overridable (removes the need for an intermediate “trampoline” function)

  • double check that all fields and methods have different names, there is no warning in case of collision (because Python handles it before Odoo sees anything)

  • the normal new-api import is from openerp import fields, models. If compatibility decorators are necessary, use from openerp import api, fields, models

  • avoid the one() decorator, it probably does not do what you expect

  • remove explicit definition of create_uid, create_date, write_uid and write_date fields: they are now created as regular “legitimate” fields, and can be read and written like any other field out-of-the-box

  • when straight conversion is impossible (semantics can not be bridged) or the “old API” version is not desirable and could be improved for the new API, it is possible to use completely different “old API” and “new API” implementations for the same method name using v7() and v8(). The method should first be defined using the old-API style and decorated with v7(), it should then be re-defined using the exact same name but the new-API style and decorated with v8(). Calls from an old-API context will be dispatched to the first implementation and calls from a new-API context will be dispatched to the second implementation. One implementation can call (and frequently does) call the other by switching context.


    using these decorators makes methods extremely difficult to override and harder to understand and document

  • uses of _columns or _all_columns should be replaced by _fields, which provides access to instances of new-style openerp.fields.Field instances (rather than old-style openerp.osv.fields._column).

    Non-stored computed fields created using the new API style are not available in _columns and can only be inspected through _fields

  • reassigning self in a method is probably unnecessary and may break translation introspection

  • Environment objects rely on some threadlocal state, which has to be set up before using them. It is necessary to do so using the openerp.api.Environment.manage() context manager when trying to use the new API in contexts where it hasn’t been set up yet, such as new threads or a Python interactive environment:

    >>> from openerp import api, modules
    >>> r = modules.registry.RegistryManager.get('test')
    >>> cr = r.cursor()
    >>> env = api.Environment(cr, 1, {})
    Traceback (most recent call last):
    AttributeError: environments
    >>> with api.Environment.manage():
    ...     env = api.Environment(cr, 1, {})
    ...     print env['res.partner'].browse(1)

Automatic bridging of old API methods

When models are initialized, all methods are automatically scanned and bridged if they look like models declared in the old API style. This bridging makes them transparently callable from new-API-style methods.

Methods are matched as “old-API style” if their second positional parameter (after self) is called either cr or cursor. The system also recognizes the third positional parameter being called uid or user and the fourth being called id or ids. It also recognizes the presence of any parameter called context.

When calling such methods from a new API context, the system will automatically fill matched parameters from the current Environment (for cr, user and context) or the current recordset (for id and ids).

In the rare cases where it is necessary, the bridging can be customized by decorating the old-style method:

  • disabling it entirely, by decorating a method with noguess() there will be no bridging and methods will be called the exact same way from the new and old API styles

  • defining the bridge explicitly, this is mostly for methods which are matched incorrectly (because parameters are named in unexpected ways):


    will automatically prepend the current cursor to explicitly provided parameters, positionally


    will automatically prepend the current cursor and user’s id to explictly provided parameters


    will automatically prepend the current cursor, user’s id and recordset’s ids to explicitly provided parameters


    will loop over the current recordset and call the method once for each record, prepending the current cursor, user’s id and record’s id to explicitly provided parameters.


    the result of this wrapper is always a list when calling from a new-API context

    All of these methods have a _context-suffixed version (e.g. cr_uid_context()) which also passes the current context by keyword.

  • dual implementations using v7() and v8() will be ignored as they provide their own “bridging”