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        "author": "Asad Dhamani",
        "author_email": "dhamaniasad+code@gmail.com",
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        "classifiers": [
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Topic :: Internet :: WWW/HTTP :: Dynamic Content",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "Welcome to Flask-WhooshAlchemy!\n===============================\n\n[![Build Status](https://travis-ci.org/dhamaniasad/Flask-WhooshAlchemy.svg?branch=master)](https://travis-ci.org/dhamaniasad/Flask-WhooshAlchemy) [![image](https://circleci.com/gh/dhamaniasad/Flask-WhooshAlchemy/tree/master.svg?style=shield)](https://circleci.com/gh/dhamaniasad/Flask-WhooshAlchemy/tree/master) [![image](https://img.shields.io/pypi/v/Flask-WhooshAlchemy-Redux.svg)](https://pypi.python.org/pypi/Flask-WhooshAlchemy-Redux)\n\nFlask-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.\n\nSource code and issue tracking at [GitHub](https://github.com/dhamaniasad/Flask-WhooshAlchemy).\n\nView the official docs [here](https://Flask-WhooshAlchemy.readthedocs.org/).\n\nInstall\n-------\n\n    pip install flask_whooshalchemy_redux\n\nOr:\n\n    git clone https://github.com/dhamaniasad/Flask-WhooshAlchemy.git\n\nQuickstart\n----------\n\nLet's set up the environment and create our model:\n\n```python\nimport flask.ext.whooshalchemy as whooshalchemy\n\n# set the location for the whoosh index\napp.config['WHOOSH_BASE'] = 'path/to/whoosh/base'\n\n\nclass BlogPost(db.Model):\n  __tablename__ = 'blogpost'\n  __searchable__ = ['title', 'content']  # these fields will be indexed by whoosh\n  __analyzer__ = SimpleAnalyzer()        # configure analyzer; defaults to\n                                         # StemmingAnalyzer if not specified\n\n  id = app.db.Column(app.db.Integer, primary_key=True)\n  title = app.db.Column(app.db.Unicode)  # Indexed fields are either String,\n  content = app.db.Column(app.db.Text)   # Unicode, or Text\n  created = db.Column(db.DateTime, default=datetime.datetime.utcnow)\n\nwhooshalchemy.whoosh_index(app, BlogPost)\n```\n\nOnly two steps to get started:\n\n1)  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.\n2)  Add a `__searchable__` field to the model which specifies the fields (as `str` s) to be indexed .\n\nLet's create a post:\n\n```python\ndb.session.add(\n    BlogPost(title='My cool title', content='This is the first post.')\n); db.session.commit()\n```\n\nAfter the session is committed, our new `BlogPost` is indexed. Similarly, if the post is deleted, it will be removed from the Whoosh index.\n\nText Searching\n--------------\n\nTo execute a simple search:\n\n```python\nresults = BlogPost.query.whoosh_search('cool')\n```\n\nThis will return all `BlogPost` instances in which at least one indexed\nfield (i.e., 'title' or 'content') is a text match to the query. Results\nare ranked according to their relevance score, with the best match\nappearing first when iterating. The result of this call is a (subclass\nof) sqlalchemy.orm.query.Query object, so you can chain other SQL\noperations. For example:\n\n```python\ntwo_days_ago = datetime.date.today() - datetime.timedelta(2)\nrecent_matches = BlogPost.query.whoosh_search('first').filter(\n    BlogPost.created >= two_days_ago)\n```\n\nOr, in alternative (likely slower) order:\n\n```python\nrecent_matches = BlogPost.query.filter(\n    BlogPost.created >= two_days_ago).whoosh_search('first')\n```\n\nWe can limit results:\n\n```python\n# get 2 best results:\nresults = BlogPost.query.whoosh_search('cool', limit=2)\n```\n\nBy default, the search is executed on all of the indexed fields as an OR\nconjunction. For example, if a model has 'title' and 'content' indicated\nas `__searchable__`, a query will be checked against both fields,\nreturning any instance whose title or content are a content match for\nthe query. To specify particular fields to be checked, populate the\n`fields` parameter with the desired fields:\n\n```python\nresults = BlogPost.query.whoosh_search('cool', fields=('title',))\n```\n\nBy default, results will only be returned if they contain all of the\nquery terms (AND). To switch to an OR grouping, set the `or_` parameter\nto `True`:\n\n```python\nresults = BlogPost.query.whoosh_search('cool', or_=True)\n```",
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