Initial commit: OCA Technical packages (595 packages)

odoo-bringout-oca-server-tools-base_partition/base_partition/models/__init__.py

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+from . import models

odoo-bringout-oca-server-tools-base_partition/base_partition/models/models.py

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+# © 2020 Acsone (http://www.acsone.eu)
+# License LGPL-3.0 or later (http://www.gnu.org/licenses/lgpl.html).
+
+from odoo import _, models
+from odoo.exceptions import UserError
+
+
+class Base(models.AbstractModel):
+
+    _inherit = "base"
+
+    def partition(self, accessor):
+        """Returns a dictionary forming a partition of self into a dictionary
+        value/recordset for each value obtained from the accessor.
+        The accessor itself can be either a string that can be passed to mapped,
+        or an arbitrary function.
+        Note that it is always at least as fast to pass a function,
+        hence the current implementation.
+        If we have a 'field.subfield' accessor such that subfield is not a relational
+        then the result is a list (not hashable). Then the str(key) are used.
+        In the general case a value could both not be hashable nor stringifiable,
+        in a which case this function would crash.
+        """
+        partition = {}
+
+        if isinstance(accessor, str):
+            if "." not in accessor:
+                func = lambda r: r[accessor]  # noqa: E731
+            else:
+                func = lambda r: r.mapped(accessor)  # noqa: E731
+        else:
+            func = accessor
+
+        for record in self:
+            key = func(record)
+            if not key.__hash__:
+                key = str(key)
+            if key not in partition:
+                partition[key] = record
+            else:
+                partition[key] += record
+
+        return partition
+
+    def batch(self, batch_size=None):
+        """Yield successive batches of size batch_size, or ."""
+        if not (batch_size or "_default_batch_size" in dir(self)):
+            raise UserError(
+                _(
+                    "Either set up a '_default_batch_size' on the model"
+                    " or provide a batch_size parameter."
+                )
+            )
+        batch_size = batch_size or self._default_batch_size
+        for i in range(0, len(self), batch_size):
+            yield self[i : i + batch_size]
+
+    def read_per_record(self, fields=None, load="_classic_read"):
+        result = {}
+        data_list = self.read(fields=fields, load=load)
+        for d in data_list:
+            key = d.pop("id")
+            result[key] = d
+        return result