Flask-WhooshAlchemyPlus 0.7.2

Whoosh extension to Flask/SQLAlchemy

Flask-WhooshAlchemy is a Flask extension that integrates the text-search functionality of Whoosh with the ORM of SQLAlchemy for use in Flask applications.

Source code and issue tracking at GitHub.

Install

pip install flask_whooshalchemyplus

Or:

git clone https://github.com/Revolution1/Flask-WhooshAlchemyPlus.git

Quickstart

Let’s set up the environment and create our model:

import flask_whooshalchemyplus

# set the location for the whoosh index
app.config['WHOOSH_BASE'] = 'path/to/whoosh/base'


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 two steps to get started:

1. Set the WHOOSH_BASE to 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.

2. Add a __searchable__ field to the model which specifies the fields (as str s) to be indexed .

3. set WHOOSH_DISABLED to True to disable whoosh 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.

Manually Indexing

By defualt records can be indexed only when the server is running. So if you want to index them manually:

from flask_whooshalchemyplus import index_all

index_all(app)

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) 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)