django-chunkator
Chunk large QuerySets into small chunks, and iterate over them without killing your RAM.
Decision gist · record as of 2026-08-14
No. The package is abandoned (last release 2020-06-22, last commit 2022-07-11) and untested against Django versions beyond 3.0. Compatibility with modern Django and Python versions is unverified. For new projects, consider using Django's built-in QuerySet.iterator() with chunk_size parameter, which provides similar functionality and is actively maintained.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Your Django model must define a unique pk field (the default), and the queryset must include it if using values().
- Low install friction with a single Django dependency.
- However, the package is abandoned—last release was 2020-06-22, with no commits since 2022-07-11.
License · maintenance · safety
MIT (permissive) — MIT license is permissive and imposes no restrictions on use, modification, or distribution in proprietary or open-source projects.
last release 2020-06-22 (2244 days) · last repo commit 2022-07-11 · 110 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 178,291 downloads/mo, #10,198 on PyPI
Alternatives
Verify before relying
pip install django-chunkator
from chunkator import chunkator
for item in chunkator(LargeModel.objects.all(), 200):
do_something(item)- Compatibility with Django versions released after 3.0 and Python versions after 3.8.
- Performance characteristics and memory savings on very large datasets.
- Whether the package functions correctly with modern dependency versions.
What it is and what it does
django-chunkator provides a simple iterator that breaks a Django QuerySet into smaller batches, fetching and processing them one chunk at a time instead of loading the entire result set into memory. This is useful when you need to process large numbers of records but don't have enough RAM to hold them all at once. The package exports two main functions: chunkator() for iterating over individual items in chunks, and chunkator_page() for working with entire pages of results as lists.
The tool works by repeatedly querying the database with offset and limit, fetching each batch sequentially. It requires that your model has a unique primary key (which Django provides by default) and works with both standard integer PKs and UUIDs. The package has been tested with PostgreSQL and SQLite. Note that chunking does not speed up the overall process—it trades a single large query for multiple smaller ones, with the main benefit being reduced memory consumption during iteration.
Use it for
- Bulk-update large numbers of records in a Django model without exhausting available RAM.
- Export large datasets to CSV or other formats by processing rows in manageable batches.
- Perform background tasks on all records in a table by chunking the queryset and dispatching each chunk to a task queue.
- Migrate or transform data from one table to another when the result set is too large to fit in memory.
- Generate reports or analytics by iterating over a large queryset in controlled increments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The package is abandoned (last release 2020-06-22, last commit 2022-07-11) and untested against Django versions beyond 3.0. Compatibility with modern Django and Python versions is unverified. For new projects, consider using Django's built-in QuerySet.iterator() with chunk_size parameter, which provides similar functionality and is actively maintained.
Install
django-chunkator on PyPI
Before you install
Low install friction with a single Django dependency. However, the package is abandoned—last release was 2020-06-22, with no commits since 2022-07-11.
Your Django model must define a unique pk field (the default), and the queryset must include it if using values().
License in practice
MIT license is permissive and imposes no restrictions on use, modification, or distribution in proprietary or open-source projects.
Quickstart
pip install django-chunkator
from chunkator import chunkator
for item in chunkator(LargeModel.objects.all(), 200):
do_something(item)Verify before relying
- Compatibility with Django versions released after 3.0 and Python versions after 3.8.
- Performance characteristics and memory savings on very large datasets.
- Whether the package functions correctly with modern dependency versions.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagedjango |
| Maintenance | Abandoned 2,244 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 178,291 / month, #10,198 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Environment :: Web EnvironmentFramework :: DjangoLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Topic :: Internet :: WWW/HTTPTopic :: Internet :: WWW/HTTP :: Dynamic Content |
Evidence: django_chunkator-2.0.0-py3-none-any.whl
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See also django-cursor-pagination · iterproxy · django-queryset-csv · graphene-django-optimizer · django-mock-queries · django-tables2 · django-sql-utils · django-query-builder · django-cacheops · django-pg-returning