Odoo 'Missing Required Field' — NOT NULL Constraint and Validation Errors Fix

Missing Required Field Errors in Odoo

When creating or updating records in Odoo, you may encounter:

ValidationError: Missing required value for the field 'Partner' (partner_id)

psycopg2.errors.NotNullViolation: null value in column "company_id" of relation
"sale_order" violates not-null constraint
DETAIL: Failing row contains (42, null, ...)

IntegrityError: NOT NULL constraint failed: account_move.journal_id

These errors occur when a record is being saved without a value in a field that Odoo or PostgreSQL requires to be filled.

Understanding Required Fields in Odoo

There are three levels of "required" in Odoo:

Fix 1: Set Default Values

If the field should have a default value when not provided:

# In your model
class MyModel(models.Model):
    _name = 'my.model'

    company_id = fields.Many2one(
        'res.company',
        required=True,
        default=lambda self: self.env.company  # Provide default
    )

    state = fields.Selection([
        ('draft', 'Draft'),
        ('confirmed', 'Confirmed'),
    ], required=True, default='draft')  # Default for selection

Fix 2: Fix Data Imports

CSV/Excel imports often fail because required columns are missing or empty:

# Error during import:
# Missing required value for the field 'Customer' (partner_id)

# Check your CSV has the required columns:
# partner_id/id or partner_id (External ID or Name)

# For Many2one fields, use external IDs:
partner_id/id
base.res_partner_1

# Or use the display name (slower, less reliable):
partner_id
My Customer Name

Fix 3: Handle Required Fields in API Calls

When creating records via XML-RPC or JSON-RPC, include all required fields:

# Find required fields for a model
fields_info = models.execute_kw(
    db, uid, password,
    'sale.order', 'fields_get',
    [], {'attributes': ['required', 'string', 'type']}
)
required_fields = {
    k: v for k, v in fields_info.items()
    if v.get('required')
}

# Then include all required fields in create call
models.execute_kw(db, uid, password, 'sale.order', 'create', [{
    'partner_id': 1,        # Required
    'company_id': 1,        # Required
    'pricelist_id': 1,      # Required
    'date_order': '2026-03-24',
}])

Fix 4: Conditional Required Fields

Some fields are required only in certain states. If your field definition uses conditional required:

# Model definition
tracking_ref = fields.Char(
    string='Tracking Reference',
    required=False  # Not always required
)

# View makes it conditionally required


# In Odoo 17+, use the new attribute syntax:

Fix 5: NOT NULL Violations from ORM Bypass

Direct SQL operations bypass Odoo's default value mechanism:

# This fails because ORM defaults are not applied:
env.cr.execute("INSERT INTO sale_order (partner_id) VALUES (1)")
# company_id has no default in SQL, only in Python

# Fix: Use the ORM instead
env['sale.order'].create({'partner_id': 1})
# ORM applies all defaults automatically

# If you must use SQL, include all NOT NULL columns:
env.cr.execute("""
    INSERT INTO sale_order (partner_id, company_id, state, ...)
    VALUES (%s, %s, %s, ...)
""", (1, 1, 'draft', ...))

Fix 6: Adding Required Fields to Existing Models

When you add a required field to a model that already has data:

# Wrong — this will fail if existing records have no value
name = fields.Char(required=True)

# Right — provide a default for existing records
name = fields.Char(required=True, default='Unnamed')

# Or compute it
def _compute_default_name(self):
    for rec in self:
        if not rec.name:
            rec.name = f'Record {rec.id}'

# Or set values before adding the constraint
def init(self):
    self.env.cr.execute("""
        UPDATE my_table SET name = 'Default'
        WHERE name IS NULL
    """)

Debugging Required Fields

# List all required fields for a model via shell
odoo shell -d mydb
for name, field in env['sale.order']._fields.items():
    if field.required:
        print(f"{name}: {field.type}, default={field.default}")

Prevention

DeployMonkey's AI agent validates data imports and API calls against model requirements before execution. Required field mismatches are detected early with clear guidance on which fields need values.