stock_picking is one of the core model for Odoo if you using Odoo for ‘Inventory’. Now, if you use ‘Sales’ module, then stock_picking would be extended with a new field for model and column for database table, naming ‘sale_id’. This can be used to detect if the picking is originated from a sale order or not. But if you install ‘Purchase’ module, then stock_picking model is extended with ‘purchase_id’ like the ‘sale_id’ for purchases, but the database isn’t expanded with a column like ‘Sale’ module.
What does this mean?
This means, if you use Odoo ORM, only then, you may use purchase_id of a stock_picking. An example could be like the following. Let’s say, we would like to pick the pickings that originated from purchase orders, aka, GRN, we could use something like this:
purchase_pickings = self.env['stock.picking'].search([('purchase_id', '!=', False)])
This works, only if you are not trying to make a report from a huge lot of pickings, purchase orders and sale orders, when you want to use SQL statement to produce efficient joins and generate the report quickly.
Let me demonstrate what I meant
We know, stock_picking has a field called sale_id and also this also belongs to the database column as well. Hence, to get all the pickings belongs to sale order, we may first use the ORM:
sale_pickings = self.env['stock.picking'].search([('sale_id', '!=', False)])
or a direct PostGRE SQL
query = """select * from stock_picking where sale_id is not null""" self.env.cr.execute(query) result = self.env.cr.fetchall()
Now, the second example is not only faster, but also, it allows you to extend the facility further to use joins or select specific field of a table result, which is only possible using ‘read’ Odoo ORM method, again, domain specification is not permissible like it is available in ‘search’.
We are able to do things like the following with the sql:
query = """select sale_order.name, stock_picking.name from stock_picking left join on stock_picking.sale_id = sale_order.id where stock_picking.sale_id is not null""" self.env.cr.execute(query) result = self.env.cr.fetchall()
This would give you a result of each sale order with it’s picking name. To produce a result like the above using ORM is costly as it follows ‘N+1’ algorithm, hence inefficient in making reports or scaling the software.
Now, we understand, we are able to use such field and make the reports efficient using SQL as sale_id is distinctively available in the database. But what if you want to check how the product has been purchased, and then sold? Then, we also need purchase_order model to connect to our above query, right? But unfortunately, as ‘Purchase’ module doesn’t add a column purchase_id, we are unable to use this directly.
So, how can we still use purchase_id in the SQL Query to generate report in Odoo?
First, we need to see, how purchase_id is added in Odoo.
purchase_id is added in stock_picking model in the ‘purchase_stock’ module. If you open the following file:
you may see, how purchase_id is defined as related Many2one field:
class StockPicking(models.Model): _inherit = 'stock.picking' purchase_id = fields.Many2one('purchase.order', related='move_lines.purchase_line_id.order_id', string="Purchase Orders", readonly=True)
A related field in Odoo, is like a pointer, a syntactic sugar of foreign key for less used fields. If the field is highly used, this might cause performance issue, as Odoo has to do multiple lookups unlike direct lookup for a related field. Now, get to the point, purchase_id is related to ‘move_lines.purchase_line_id.order_id’. This is a long relation. Let me go one by one:
- move_lines : stock_picking has an One2many relation with stock.move model, that derives the available moves for the picking.
- purchase_line_id: Each move line derived from a purchase order line, and while doing so, it keeps the ID of the purchase order line in a foreign key of stock.move model, namely purchase_line_id.
- order_id: Each purchase_order_line has a foreign key with the purchase.order model kept in order_id field.
Now, we know, how the purchase_id derives the purchase_order id using the following relation:
Picking > Moves > Purchase Order Line > Purchase Order
Now we can use the following kind of relation for detecting purchase order from stock picking:
select purchase_order.name, stock_picking.name from stock_picking left join stock_move on stock_move.picking_id = stock_picking.id left join purchase_order_line on purchase_order_line.id = stock_move.purchase_line_id left join purchase_order on purchase_order.id = purchase_order_line.order_id where stock_move.purchase_line_id is not null group by stock_picking.name, purchase_order.name
Here, we are able to get the picking and purchase in relation with one query. This concept can be used to derive many data, like, let’s say, you would like to see, how many of your products are purchased, then, sold and returned, all can be done in few queries, without having N+1 problem.