All Projects → mathandpencil → django-bulk-sync

mathandpencil / django-bulk-sync

Licence: MIT License
Combine bulk add, update, and delete into a single call.

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to django-bulk-sync

reactant
Generate code for "models, views, and urls" based on Python type annotations. Supports Django REST, SQLAlchemy, Peewee.
Stars: ✭ 14 (-69.57%)
Mutual labels:  django-orm
djantic
Pydantic model support for Django
Stars: ✭ 256 (+456.52%)
Mutual labels:  django-orm
postmodel
ORM library for Python 3.6+, asyncio. Provides Django ORM like API.
Stars: ✭ 15 (-67.39%)
Mutual labels:  django-orm
xsd to django model
Generate Django models from an XSD schema description (and a bunch of hints)
Stars: ✭ 20 (-56.52%)
Mutual labels:  django-orm
django-sqlalchemy
Django ORM built on top of SQLalchemy core 2.0 for seamless integration of SQLAlchemy with Django 4.1+ PostgreSQL 14+ only for now. [pre POC now]
Stars: ✭ 101 (+119.57%)
Mutual labels:  django-orm
django-concurrency-talk
🎭 Database Integrity in Django: Safely Handling Critical Data in Distributed Systems
Stars: ✭ 49 (+6.52%)
Mutual labels:  django-orm
djaq
Django queries
Stars: ✭ 54 (+17.39%)
Mutual labels:  django-orm

django-bulk-sync

Combine bulk create, update, and delete into a single call.

django-bulk-sync is a package for the Django ORM that combines bulk_create, bulk_update, and delete into a single method call to bulk_sync.

It manages all necessary creates, updates, and deletes with as few database calls as possible to maximize performance.

It can use either database PKs or key_fields to match up objects with existing records.

Installation

The package is available on pip as [django-bulk-sync][django-bulk-sync]. Run:

pip install django-bulk-sync

then import via:

from bulk_sync import bulk_sync

A Usage Scenario

Companies have zero or more Employees. You want to efficiently sync the names of all employees for a single Company from an import from that company, but some are added, updated, or removed. The simple approach is inefficient -- read the import line by line, and:

For each of N records:

  • SELECT to check for the employee's existence
  • UPDATE if it exists, INSERT if it doesn't

Then figure out some way to identify what was missing and delete it. As is so often the case, the speed of this process is controlled mostly by the number of queries run, and here it is about two queries for every record, and so O(N).

Instead, with bulk_sync, we can avoid the O(N) number of queries, and simplify the logic we have to write as well.

Example Usage

from django.db.models import Q
from bulk_sync import bulk_sync

new_models = []
for line in company_import_file:
	# The `.id` (or `.pk`) field should not be set. Instead, `key_fields`
	# tells it how to match.
	e = Employee(name=line['name'], phone_number=line['phone_number'], ...)
	new_models.append(e)

# `filters` controls the subset of objects considered when deciding to
# update or delete.  Here we sync only company 501 employees.
filters = Q(company_id=501)

# `key_fields` matches an existing object if all `key_fields` are equal.
key_fields = ('name', )

ret = bulk_sync(
        new_models=new_models,
        filters=filters,
        fields=['name', 'phone_number', ...],
        key_fields=key_fields)

print("Results of bulk_sync: "
      "{created} created, {updated} updated, {deleted} deleted."
      		.format(**ret['stats']))

Under the hood, it will atomically call bulk_create, bulk_update, and a single queryset delete() call, to correctly and efficiently update all fields of all employees for the filtered Company, using name to match properly.

Argument Reference

def bulk_sync(new_models, key_fields, filters, batch_size=None, fields=None, skip_creates=False, skip_updates=False, skip_deletes=False): Combine bulk create, update, and delete. Make the DB match a set of in-memory objects.

  • new_models: An iterable of Django ORM Model objects that you want stored in the database. They may or may not have id set, but you should not have already called save() on them.

  • key_fields: Identifying attribute name(s) to match up new_models items with database rows. If a foreign key is being used as a key field, be sure to pass the fieldname_id rather than the fieldname. Use ['pk'] if you know the PKs already and want to use them to identify and match up new_models with existing database rows.

  • filters: Q() filters specifying the subset of the database to work in. Use None or [] if you want to sync against the entire table.

  • batch_size: (optional) passes through to Django bulk_create.batch_size and bulk_update.batch_size, and controls how many objects are created/updated per SQL query.

  • fields: (optional) List of fields to update. If not set, will sync all fields that are editable and not auto-created.

  • exclude_fields: (optional) list of fields to exclude from updates. Subtracts from the passed-in fields or default-calculated fields (see fields documentation above).

  • exclude_fields: (optional) List of fields to exclude from updates.

  • skip_creates: (optional) If truthy, will not perform any object creations needed to fully sync. Defaults to not skip.

  • skip_updates: (optional) If truthy, will not perform any object updates needed to fully sync. Defaults to not skip.

  • skip_deletes: (optional) If truthy, will not perform any object deletions needed to fully sync. Defaults to not skip.

  • db_class: (optional) Model class to operate on. If new_models always contains at least one object, this can be set automatically so is optional.

  • Returns a dict:

    {
    'stats': {
        "created": number of `new_models` not found in database and so created,
        "updated": number of `new_models` that were found in database as matched by `key_fields`,
        "deleted": number of deleted objects - rows in database that matched `filters` but were not present in `new_models`.
        }
    }
    

def bulk_compare(old_models, new_models, key_fields, ignore_fields=None): Compare two sets of models by key_fields.

  • old_models: Iterable of Django ORM objects to compare.
  • new_models: Iterable of Django ORM objects to compare.
  • key_fields: Identifying attribute name(s) to match up new_models items with database rows. If a foreign key is being used as a key field, be sure to pass the fieldname_id rather than the fieldname.
  • ignore_fields: (optional) If set, provide field names that should not be considered when comparing objects.
  • Returns dict:
        {
            'added': list of all added objects.
            'unchanged': list of all unchanged objects.
            'updated': list of all updated objects.
            'updated_details': dict of {obj: {field_name: (old_value, new_value)}} for all changed fields in each updated object.
            'removed': list of all removed objects.
        }
    

Frameworks Supported

This library is tested using Python 3 against Django 2.2+. If you are looking for versions that work with Django < 2.2, please use the 1.x releases.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].