Metadata-Version: 1.1
Name: django-chunkator
Version: 2.0.0
Summary: Chunk large QuerySets into small chunks, and iterate over them without killing your RAM.
Home-page: https://github.com/peopledoc/django-chunkator
Author: PeopleDoc
Author-email: rd@people-doc.com
License: MIT
Description: ================
        django-chunkator
        ================
        
        
        Chunk large QuerySets into small chunks, and iterate over them without killing
        your RAM.
        
        .. image:: https://travis-ci.org/peopledoc/django-chunkator.svg
        
        Tested with all the combinations of:
        
        * Python: 3.5, 3.6, 3.7, 3.8
        * Django: 2, 2.1, 2.2, 3.0, master
        
        
        .. note::
        
            Django 3.0 is incompatible with Python 3.5, see <https://docs.djangoproject.com/en/3.0/releases/3.0/#python-compatibility>
        
        Usage
        =====
        
        .. code:: python
        
            from chunkator import chunkator
            for item in chunkator(LargeModel.objects.all(), 200):
                do_something(item)
        
        This tool is intended to work on Django querysets.
        
        Your model **must** define a ``pk`` field (this is done by default, but
        sometimes it can be overridden) and this pk has to be unique. ``django-
        chunkator`` has been tested with PostgreSQL and SQLite, using regular PKs and
        UUIDs as primary keys.
        
        You can also use ``values()``:
        
        .. code:: python
        
            from chunkator import chunkator
            for item in chunkator(LargeModel.objects.values('pk', 'name'), 200):
                do_something(item)
        
        .. important::
        
            If you're using ``values()`` you **have** to add at least your "pk" field
            to the values, otherwise, the chunkator will throw a
            ``MissingPkFieldException``.
        
        .. warning::
        
            This will not **accelerate** your process. Instead of having one BIG query,
            you'll have several small queries. This will save your RAM instead, because
            you'll not load a huge queryset result before looping on it.
        
        If you want to manipulate the pages directly, you can use `chunkator_page`:
        
        .. code:: python
        
            from chunkator import chunkator_page
            queryset = LargeModel.objects.all().values('pk')
            for page in chunkator_page(queryset, 200):
                launch_some_task([item['pk'] for item in page])
        
        License
        =======
        
        MIT License.
        
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Framework :: Django
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Classifier: License :: OSI Approved :: MIT License
