This is a modern replacement of django-simple-elasticsearch (DSE). Both Django and Elasticsearch have seen major changes over the years; this is a move to keep up.

Why not just update django-simple-elasticsearch?

• DSE is Django-specific; I wanted to build a solution that could be used in a broader scope of applications
• To start fresh and avoid assumptions made in the DSE project
• Dropped support for Python 2

Details

• Flexible and modular; eg. Django support is available via a 'contrib' module
• Supports multi-process indexing and asynchronous IO via gevent
• Depends on elasticsearch-dsl-py rather than the low level elasticsearch-py package
  • You get a lot of functionality for free!
• Python 3 only
• esdocs >= 0.6 supports Elasticsearch 7.x

Installation

pip install esdocs

If multi-process indexing is desired, you will want to install it along with the necessary gevent dependencies:

pip install esdocs[gevent]

Command Line Usage

$ esdocs -h
usage: esdocs [-h] [-v] [--version] [--no_input] [--indexes INDEXES]
              [--using USING] [--multi [MULTI]]
              {list,init,update,rebuild,cleanup} ...

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         increase output verbosity
  --version             show program's version number and exit
  --no_input, --noinput
                        Do not prompt for user input (assumes 'Yes' for
                        actions)
  --indexes INDEXES     Comma-separate list of index names to target
  --using USING         Elasticsearch named connection to use
  --multi [MULTI]       Enable multiple processes and optionally set number of
                        CPU cores to use (defaults to all cores)

commands:
  {list,init,update,rebuild,cleanup}
    list                List indexes
    init                Initialize indexes
    update              Update indexes
    rebuild             Rebuild indexes
    cleanup             Delete unaliased indexes

To rebuild indexes specified by document serializers in ESDOCS_SERIALIZER_MODULES:

export ESDOCS_SERIALIZER_MODULES="mypackage.module1,myotherpackage.module2"
export ESDOCS_SERIALIZER_COMPATIBILITY_HOOKS="esdocs.contrib.postgresql.compatibility.range_field"

esdocs rebuild

Multi-process indexing:

export ESDOCS_GEVENT=y
export ESDOCS_SERIALIZER_MODULES="mypackage.module1,myotherpackage.module2"
export ESDOCS_SERIALIZER_COMPATIBILITY_HOOKS="esdocs.contrib.postgresql.compatibility.range_field"

# auto detect number of CPU cores to use
esdocs rebuild --multiproc

# specify the number of cores to use
esdocs rebuild --multiproc --numprocs=4

Django

You must specify ESDOCS_SERIALIZER_MODULES in your Django settings and add esdocs.contrib.esdjango to your INSTALLED_APPS. You can optionally set ESDOCS_SERIALIZER_COMPATIBILITY_HOOKS as well:

INSTALLED_APPS = [
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    ...,
    'esdocs.contrib.esdjango'
]


ESDOCS_SERIALIZER_MODULES = [
    'mypackage.module1',
    'myotherpackage.module2'
]

# these are the current defaults for this setting
ESDOCS_SERIALIZER_COMPATIBILITY_HOOKS = [
    'esdocs.contrib.esdjango.compatibility.manager',
    'esdocs.contrib.esdjango.compatibility.geosgeometry',
    'esdocs.contrib.postgresql.compatibility.range_field'
]

Serializing Data

For esdocs to work, you need to define Document and Serializer (or DjangoSerializer) subclasses to index your data. Document comes from the excellent elasticsearch-dsl-py, while Serializer/DjangoSerializer are a part of esdocs.

• Document defines the Elasticsearch field mappings
• Serializer is associated with a Document
• Serializer defines how to retrieve the dataset
• For each record in your dataset, the Serializer will attempt to retrieve a value for each field defined on the associated Document
  • There are a number of methods you can implement on a Serializer to retrieve (or construct/munge) each value

Examples