Welcome to Flask-WhooshAlchemy!
Flask-WhooshAlchemy is a Flask extension that integrates the text-search functionality of Whoosh <https://bitbucket.org/mchaput/whoosh/wiki/Home>_ with the ORM of SQLAlchemy <http://www.sqlalchemy.org/>_ for use in Flask <http://flask.pocoo.org/>_ applications.
Source code and issue tracking at GitHub <http://github.com/gyllstromk/Flask-WhooshAlchemy>_.
View the official docs at http://packages.python.org/Flask-WhooshAlchemy/.
Install
::
pip install flask_whooshalchemy
Or:
::
git clone https://github.com/gyllstromk/Flask-WhooshAlchemy.git
Quickstart
Let's set up the environment and create our model:
::
from whoosh.analysis import StemmingAnalyzer
import flask_whooshalchemy
# set the location for the whoosh index
app.config['WHOOSH_BASE'] = 'path/to/whoosh/base'
# set the global analyzer, defaults to StemmingAnalyzer.
app.config['WHOOSH_ANALYZER'] = StemmingAnalyzer()
class BlogPost(db.Model):
__tablename__ = 'blogpost'
__searchable__ = ['title', 'content'] # these fields will be indexed by whoosh
__analyzer__ = SimpleAnalyzer() # configure analyzer; defaults to
# StemmingAnalyzer if not specified
id = app.db.Column(app.db.Integer, primary_key=True)
title = app.db.Column(app.db.Unicode) # Indexed fields are either String,
content = app.db.Column(app.db.Text) # Unicode, or Text
created = db.Column(db.DateTime, default=datetime.datetime.utcnow)
Only four steps to get started:
(Actually, only the third one is required for using, others are all optional.)
- Set the
WHOOSH_BASEto the path for the whoosh index. If not set, it will default to a directory called 'whoosh_index' in the directory from which the application is run. - Set the
WHOOSH_ANALYZERto the global analyzer. If not set, it will defalt toStemmingAnalyzer. - Add a
__searchable__field to the model which specifies the fields (asstrs) to be indexed . - Add a
__analyzer__field to the model if you need a local custom analyzer for indexing.
Let's create a post:
::
db.session.add(
BlogPost(title='My cool title', content='This is the first post.')
); db.session.commit()
After the session is committed, our new BlogPost is indexed. Similarly, if the post is deleted, it will be removed from the Whoosh index.
Text Searching
To execute a simple search:
::
results = BlogPost.query.whoosh_search('cool')
This will return all BlogPost instances in which at least one indexed field (i.e., 'title' or 'content') is a text match to the query. Results are ranked according to their relevance score, with the best match appearing first when iterating. The result of this call is a (subclass of) :class:sqlalchemy.orm.query.Query object, so you can chain other SQL operations. For example::
two_days_ago = datetime.date.today() - datetime.timedelta(2)
recent_matches = BlogPost.query.whoosh_search('first').filter(
BlogPost.created >= two_days_ago)
Or, in alternative (likely slower) order::
recent_matches = BlogPost.query.filter(
BlogPost.created >= two_days_ago).whoosh_search('first')
We can limit results::
# get 2 best results:
results = BlogPost.query.whoosh_search('cool', limit=2)
By default, the search is executed on all of the indexed fields as an OR conjunction. For example, if a model has 'title' and 'content' indicated as __searchable__, a query will be checked against both fields, returning any instance whose title or content are a content match for the query. To specify particular fields to be checked, populate the fields parameter with the desired fields::
results = BlogPost.query.whoosh_search('cool', fields=('title',))
By default, results will only be returned if they contain all of the query terms (AND). To switch to an OR grouping, set the or_ parameter to True::
results = BlogPost.query.whoosh_search('cool', or_=True)