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django-pgbulk
provides functions for doing native Postgres bulk upserts (i.e. UPDATE ON CONFLICT), bulk updates, and COPY FROM.
Bulk upserts can distinguish between updated/created rows and ignore unchanged updates.
Bulk updates are true bulk updates, unlike Django's bulk_update which can still suffer from O(N) queries and can create poor locking scenarios.
Bulk copies can significantly speed-up bulk inserts, sometimes by an order of magnitude over Django's bulk_create
.
import pgbulk
pgbulk.upsert(
MyModel,
[
MyModel(int_field=1, some_attr="some_val1"),
MyModel(int_field=2, some_attr="some_val2"),
],
# These are the fields that identify the uniqueness constraint.
["int_field"],
# These are the fields that will be updated if the row already
# exists. If not provided, all fields will be updated
["some_attr"]
)
import pgbulk
pgbulk.update(
MyModel,
[
MyModel(id=1, some_attr='some_val1'),
MyModel(id=2, some_attr='some_val2')
],
# These are the fields that will be updated. If not provided,
# all fields will be updated
['some_attr']
)
import pgbulk
pgbulk.copy(
MyModel,
# Insert these rows using COPY FROM
[
MyModel(id=1, some_attr='some_val1'),
MyModel(id=2, some_attr='some_val2')
],
)
Here are some advanced features at a glance:
pgbulk.upsert
can categorize which rows were inserted or updated.pgbulk.upsert
and pgbulk.update
can ignore updating unchanged fields.pgbulk.upsert
and pgbulk.update
can use expressions in updates.View the django-pgbulk docs here for more examples.
django-pgbulk
is compatible with Python 3.9 - 3.13, Django 4.2 - 5.1, Psycopg 2 - 3, and Postgres 13 - 17.
Install django-pgbulk
with:
pip3 install django-pgbulk
For information on setting up django-pgbulk for development and contributing changes, view CONTRIBUTING.md.
FAQs
Native Postgres update, upsert, and copy operations.
We found that django-pgbulk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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