Elasticsearch (DSL) <https://elasticsearch-dsl.readthedocs.io/en/latest/>/
OpenSearch (DSL) <https://opensearch.org/docs/latest/clients/python/>
integration for Graphene <http://graphene-python.org/>__.
.. image:: https://img.shields.io/pypi/v/graphene-elastic.svg :target: https://pypi.python.org/pypi/graphene-elastic :alt: PyPI Version
.. image:: https://img.shields.io/pypi/pyversions/graphene-elastic.svg :target: https://pypi.python.org/pypi/graphene-elastic/ :alt: Supported Python versions
.. image:: https://github.com/barseghyanartur/graphene-elastic/workflows/test/badge.svg :target: https://github.com/barseghyanartur/graphene-elastic/actions?query=workflow%3Atest :alt: Build Status
.. image:: https://readthedocs.org/projects/graphene-elastic/badge/?version=latest :target: http://graphene-elastic.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status
.. image:: https://img.shields.io/badge/license-GPL--2.0--only%20OR%20LGPL--2.1--or--later-blue.svg :target: https://github.com/barseghyanartur/graphene-elastic/#License :alt: GPL-2.0-only OR LGPL-2.1-or-later
.. image:: https://coveralls.io/repos/github/barseghyanartur/graphene-elastic/badge.svg?branch=master :target: https://coveralls.io/github/barseghyanartur/graphene-elastic?branch=master :alt: Coverage
ElasticsearchConnectionField and ElasticsearchObjectType
are the core classes to work with graphene.See the Road-map_ for what's yet planned to implemented.
Do you need a similar tool for Django REST Framework? Check
django-elasticsearch-dsl-drf <https://github.com/barseghyanartur/django-elasticsearch-dsl-drf>__.
Check the live demo app <https://graphene-elastic.herokuapp.com/?query=query%20%7B%0A%20%20allPostDocuments%7B%0A%20%20%20%20edges%20%7B%0A%20%20%20%20%20%20node%20%7B%0A%20%20%20%20%20%20%20%20id%0A%20%20%20%20%20%20%20%20title%0A%20%20%20%20%20%20%20%20content%0A%20%20%20%20%20%20%20%20tags%0A%20%20%20%20%20%20%20%20createdAt%0A%20%20%20%20%20%20%7D%0A%20%20%20%20%7D%0A%20%20%7D%0A%7D>__
(FastAPI + Graphene 2 + Elasticsearch 7) hosted on Heroku and bonsai.io.
Documentation is available on Read the Docs <http://graphene-elastic.readthedocs.io/>_.
Install latest stable version from PyPI:
.. code-block:: bash
pip install graphene-elasticOr latest development version from GitHub:
.. code-block:: bash
pip install https://github.com/barseghyanartur/graphene-elastic/archive/master.zip.. note::
Staring from version 0.8, the ``elasticsearch`` and ``elasticsearch-dsl``
packages are no longer installed by default. You must either install them
explicitly in your requirements or install as optional dependencies as
follows: ``pip install graphene-elastic[elasticsearch]``.
Alternatively, you can use ``opensearch-py`` and ``opensearch-dsl``.
You would then need to install the ``opensearch-py`` and ``opensearch-dsl``
packages explicitly in your requirements or install them as optional
dependencies as follows: ``pip install graphene-elastic[opensearch]``... note::
In the examples, we use ``elasticsearch_dsl`` package for schema definition.
You can however use ``opensearch_dsl`` or if you want to achieve
portability between ``Elasticsearch`` and ``OpenSearch``, use ``anysearch``
package. Read more `here <https://github.com/barseghyanartur/anysearch>`__... code-block:: sh
pip install -r requirements.txtThe following command will create indexes for User and Post documents
and populate them with sample data:
.. code-block:: sh
./scripts/populate_elasticsearch_data.shsearch_index/documents/post.py
See examples/search_index/documents/post.py <https://github.com/barseghyanartur/graphene-elastic/blob/master/examples/search_index/documents/post.py>_
for full example.
.. code-block:: python
import datetime
from elasticsearch_dsl import (
Boolean,
Date,
Document,
InnerDoc,
Keyword,
Nested,
Text,
Integer,
)
class Comment(InnerDoc):
author = Text(fields={'raw': Keyword()})
content = Text(analyzer='snowball')
created_at = Date()
def age(self):
return datetime.datetime.now() - self.created_at
class Post(Document):
title = Text(
fields={'raw': Keyword()}
)
content = Text()
created_at = Date()
published = Boolean()
category = Text(
fields={'raw': Keyword()}
)
comments = Nested(Comment)
tags = Text(
analyzer=html_strip,
fields={'raw': Keyword(multi=True)},
multi=True
)
num_views = Integer()
class Index:
name = 'blog_post'
settings = {
'number_of_shards': 1,
'number_of_replicas': 1,
'blocks': {'read_only_allow_delete': None},
}Sample Flask app
**Run the sample Flask app:**
.. code-block:: sh
./scripts/run_flask.sh
**Open Flask graphiql client**
.. code-block:: text
http://127.0.0.1:8001/graphql
Sample Django appRun the sample Django app:
.. code-block:: sh
./scripts/run_django.sh runserverOpen Django graphiql client
.. code-block:: text
http://127.0.0.1:8000/graphqlConnectionField example
ConnectionField is the most flexible and feature rich solution you have. It
uses filter backends which you can tie to your needs the way you want in a
declarative manner.
**Sample schema definition**
.. code-block:: python
import graphene
from graphene_elastic import (
ElasticsearchObjectType,
ElasticsearchConnectionField,
)
from graphene_elastic.filter_backends import (
FilteringFilterBackend,
SearchFilterBackend,
HighlightFilterBackend,
OrderingFilterBackend,
DefaultOrderingFilterBackend,
)
from graphene_elastic.constants import (
LOOKUP_FILTER_PREFIX,
LOOKUP_FILTER_TERM,
LOOKUP_FILTER_TERMS,
LOOKUP_FILTER_WILDCARD,
LOOKUP_QUERY_EXCLUDE,
LOOKUP_QUERY_IN,
)
# Object type definition
class Post(ElasticsearchObjectType):
class Meta(object):
document = PostDocument
interfaces = (Node,)
filter_backends = [
FilteringFilterBackend,
SearchFilterBackend,
HighlightFilterBackend,
OrderingFilterBackend,
DefaultOrderingFilterBackend,
]
# For `FilteringFilterBackend` backend
filter_fields = {
# The dictionary key (in this case `title`) is the name of
# the corresponding GraphQL query argument. The dictionary
# value could be simple or complex structure (in this case
# complex). The `field` key points to the `title.raw`, which
# is the field name in the Elasticsearch document
# (`PostDocument`). Since `lookups` key is provided, number
# of lookups is limited to the given set, while term is the
# default lookup (as specified in `default_lookup`).
'title': {
'field': 'title.raw',
# Available lookups
'lookups': [
LOOKUP_FILTER_TERM,
LOOKUP_FILTER_TERMS,
LOOKUP_FILTER_PREFIX,
LOOKUP_FILTER_WILDCARD,
LOOKUP_QUERY_IN,
LOOKUP_QUERY_EXCLUDE,
],
# Default lookup
'default_lookup': LOOKUP_FILTER_TERM,
},
# The dictionary key (in this case `category`) is the name of
# the corresponding GraphQL query argument. Since no lookups
# or default_lookup is provided, defaults are used (all lookups
# available, term is the default lookup). The dictionary value
# (in this case `category.raw`) is the field name in the
# Elasticsearch document (`PostDocument`).
'category': 'category.raw',
# The dictionary key (in this case `tags`) is the name of
# the corresponding GraphQL query argument. Since no lookups
# or default_lookup is provided, defaults are used (all lookups
# available, term is the default lookup). The dictionary value
# (in this case `tags.raw`) is the field name in the
# Elasticsearch document (`PostDocument`).
'tags': 'tags.raw',
# The dictionary key (in this case `num_views`) is the name of
# the corresponding GraphQL query argument. Since no lookups
# or default_lookup is provided, defaults are used (all lookups
# available, term is the default lookup). The dictionary value
# (in this case `num_views`) is the field name in the
# Elasticsearch document (`PostDocument`).
'num_views': 'num_views',
}
# For `SearchFilterBackend` backend
search_fields = {
'title': {'boost': 4},
'content': {'boost': 2},
'category': None,
}
# For `OrderingFilterBackend` backend
ordering_fields = {
# The dictionary key (in this case `tags`) is the name of
# the corresponding GraphQL query argument. The dictionary
# value (in this case `tags.raw`) is the field name in the
# Elasticsearch document (`PostDocument`).
'title': 'title.raw',
# The dictionary key (in this case `created_at`) is the name of
# the corresponding GraphQL query argument. The dictionary
# value (in this case `created_at`) is the field name in the
# Elasticsearch document (`PostDocument`).
'created_at': 'created_at',
# The dictionary key (in this case `num_views`) is the name of
# the corresponding GraphQL query argument. The dictionary
# value (in this case `num_views`) is the field name in the
# Elasticsearch document (`PostDocument`).
'num_views': 'num_views',
}
# For `DefaultOrderingFilterBackend` backend
ordering_defaults = (
'-num_views', # Field name in the Elasticsearch document
'title.raw', # Field name in the Elasticsearch document
)
# For `HighlightFilterBackend` backend
highlight_fields = {
'title': {
'enabled': True,
'options': {
'pre_tags': ["<b>"],
'post_tags': ["</b>"],
}
},
'content': {
'options': {
'fragment_size': 50,
'number_of_fragments': 3
}
},
'category': {},
}
# Query definition
class Query(graphene.ObjectType):
all_post_documents = ElasticsearchConnectionField(Post)
# Schema definition
schema = graphene.Schema(query=Query)
Filter
^^^^^^
Sample queries
++++++++++++++
Since we didn't specify any lookups on `category`, by default all lookups
are available and the default lookup would be ``term``. Note, that in the
``{value:"Elastic"}`` part, the ``value`` stands for default lookup, whatever
it has been set to.
.. code-block:: javascript
query PostsQuery {
allPostDocuments(filter:{category:{value:"Elastic"}}) {
edges {
node {
id
title
category
content
createdAt
comments
}
}
}
}
But, we could use another lookup (in example below - ``terms``). Note, that
in the ``{terms:["Elastic", "Python"]}`` part, the ``terms`` is the lookup
name.
.. code-block:: javascript
query PostsQuery {
allPostDocuments(
filter:{category:{terms:["Elastic", "Python"]}}
) {
edges {
node {
id
title
category
content
createdAt
comments
}
}
}
}
Or apply a ``gt`` (``range``) query in addition to filtering:
.. code-block:: javascript
{
allPostDocuments(filter:{
category:{term:"Python"},
numViews:{gt:"700"}
}) {
edges {
node {
category
title
comments
numViews
}
}
}
}
Implemented filter lookups
++++++++++++++++++++++++++
The following lookups are available:
- ``contains``
- ``ends_with`` (or ``endsWith`` for camelCase)
- ``exclude``
- ``exists``
- ``gt``
- ``gte``
- ``in``
- ``is_null`` (or ``isNull`` for camelCase)
- ``lt``
- ``lte``
- ``prefix``
- ``range``
- ``starts_with`` (or ``startsWith`` for camelCase)
- ``term``
- ``terms``
- ``wildcard``
See `dedicated documentation on filter lookups
<https://graphene-elastic.readthedocs.io/en/latest/filtering.html>`__ for
more information.
Search
^^^^^^
Search in all fields:
.. code-block:: javascript
query {
allPostDocuments(
search:{query:"Release Box"}
) {
edges {
node {
category
title
content
}
}
}
}
Search in specific fields:
.. code-block:: javascript
query {
allPostDocuments(
search:{
title:{value:"Release", boost:2},
content:{value:"Box"}
}
) {
edges {
node {
category
title
content
}
}
}
}
Ordering
^^^^^^^^
Possible choices are ``ASC`` and ``DESC``.
.. code-block:: javascript
query {
allPostDocuments(
filter:{category:{term:"Photography"}},
ordering:{title:ASC}
) {
edges {
node {
category
title
content
numViews
tags
}
}
}
}
Pagination
^^^^^^^^^^
The ``first``, ``last``, ``before`` and ``after`` arguments are supported.
By default number of results is limited to 100.
.. code-block:: javascript
query {
allPostDocuments(first:12) {
pageInfo {
startCursor
endCursor
hasNextPage
hasPreviousPage
}
edges {
cursor
node {
category
title
content
numViews
}
}
}
}
Highlighting
^^^^^^^^^^^^
Simply, list the fields you want to highlight. This works only in combination
with search.
.. code-block:: javascript
query {
allPostDocuments(
search:{content:{value:"alice"}, title:{value:"alice"}},
highlight:[category, content]
) {
edges {
node {
title
content
highlight
}
cursor
}
}
}
Road-map
========
Road-map and development plans.
This package is designed after `django-elasticsearch-dsl-drf
<https://github.com/barseghyanartur/django-elasticsearch-dsl-drf>`__ and
is intended to offer similar functionality.
Lots of features are planned to be released in the upcoming Beta releases:
- Suggester backend.
- Nested backend.
- Geo-spatial backend.
- Filter lookup ``geo_bounding_box`` (or ``geoBoundingBox`` for camelCase).
- Filter lookup ``geo_distance`` (or ``geoDistance`` for camelCase).
- Filter lookup ``geo_polygon`` (or ``geoPolygon`` for camelCase).
- More-like-this backend.
Stay tuned or reach out if you want to help.
Testing
=======
Project is covered with tests.
Testing with Docker
-------------------
.. code-block:: sh
make docker-test
Running tests with virtualenv or tox
------------------------------------
By defaults tests are executed against the Elasticsearch 7.x.
**Run Elasticsearch 7.x with Docker**
.. code-block:: bash
docker-compose up elasticsearch
**Install test requirements**
.. code-block:: sh
pip install -r requirements/test.txt
To test with all supported Python versions type:
.. code-block:: sh
tox
To test against specific environment, type:
.. code-block:: sh
tox -e py38-elastic7
To test just your working environment type:
.. code-block:: sh
./runtests.py
To run a single test module in your working environment type:
.. code-block:: sh
./runtests.py src/graphene_elastic/tests/test_filter_backend.py
To run a single test class in a given test module in your working environment
type:
.. code-block:: sh
./runtests.py src/graphene_elastic/tests/test_filter_backend.py::FilterBackendElasticTestCase
Debugging
=========
For development purposes, you could use the flask app (easy to debug). Standard
``pdb`` works (``import pdb; pdb.set_trace()``). If ``ipdb`` does not work
well for you, use ``ptpdb``.
Writing documentation
=====================
Keep the following hierarchy.
.. code-block:: text
=====
title
=====
header
======
sub-header
----------
sub-sub-headersub-sub-sub-header
^^^^^^^^^^^^^^^^^^
sub-sub-sub-sub-header
++++++++++++++++++++++
sub-sub-sub-sub-sub-header
**************************GPL-2.0-only OR LGPL-2.1-or-later
For any security issues contact me at the e-mail given in the Author section.
For overall issues, go to GitHub <https://github.com/barseghyanartur/graphene-elastic/issues>.
Artur Barseghyan artur.barseghyan@gmail.com