diff --git a/docs/patterns/index.rst b/docs/patterns/index.rst index 78a66a1d..2737d695 100644 --- a/docs/patterns/index.rst +++ b/docs/patterns/index.rst @@ -34,7 +34,7 @@ Snippet Archives `_. jquery errorpages lazyloading - mongokit + mongoengine favicon streaming deferredcallbacks diff --git a/docs/patterns/mongoengine.rst b/docs/patterns/mongoengine.rst new file mode 100644 index 00000000..015e7b61 --- /dev/null +++ b/docs/patterns/mongoengine.rst @@ -0,0 +1,103 @@ +MongoDB with MongoEngine +======================== + +Using a document database like MongoDB is a common alternative to +relational SQL databases. This pattern shows how to use +`MongoEngine`_, a document mapper library, to integrate with MongoDB. + +A running MongoDB server and `Flask-MongoEngine`_ are required. :: + + pip install flask-mongoengine + +.. _MongoEngine: http://mongoengine.org +.. _Flask-MongoEngine: https://flask-mongoengine.readthedocs.io + + +Configuration +------------- + +Basic setup can be done by defining ``MONGODB_SETTINGS`` on +``app.config`` and creating a ``MongoEngine`` instance. :: + + from flask import Flask + from flask_mongoengine import MongoEngine + + app = Flask(__name__) + app.config['MONGODB_SETTINGS'] = { + "db": "myapp", + } + db = MongoEngine(app) + + +Mapping Documents +----------------- + +To declare a model that represents a Mongo document, create a class that +inherits from ``Document`` and declare each of the fields. :: + + import mongoengine as me + + class Movie(me.Document): + title = me.StringField(required=True) + year = me.IntField() + rated = me.StringField() + director = me.StringField() + actors = me.ListField() + +If the document has nested fields, use ``EmbeddedDocument`` to +defined the fields of the embedded document and +``EmbeddedDocumentField`` to declare it on the parent document. :: + + class Imdb(me.EmbeddedDocument): + imdb_id = me.StringField() + rating = me.DecimalField() + votes = me.IntField() + + class Movie(me.Document): + ... + imdb = me.EmbeddedDocumentField(Imdb) + + +Creating Data +------------- + +Instantiate your document class with keyword arguments for the fields. +You can also assign values to the field attributes after instantiation. +Then call ``doc.save()``. :: + + bttf = Movie(title="Back To The Future", year=1985) + bttf.actors = [ + "Michael J. Fox", + "Christopher Lloyd" + ] + bttf.imdb = Imdb(imdb_id="tt0088763", rating=8.5) + bttf.save() + + +Queries +------- + +Use the class ``objects`` attribute to make queries. A keyword argument +looks for an equal value on the field. :: + + bttf = Movies.objects(title="Back To The Future").get_or_404() + +Query operators may be used by concatenating them with the field name +using a double-underscore. ``objects``, and queries returned by +calling it, are iterable. :: + + some_theron_movie = Movie.objects(actors__in=["Charlize Theron"]).first() + + for recents in Movie.objects(year__gte=2017): + print(recents.title) + + +Documentation +------------- + +There are many more ways to define and query documents with MongoEngine. +For more information, check out the `official documentation +`_. + +Flask-MongoEngine adds helpful utilities on top of MongoEngine. Check +out their `documentation `_ as well. diff --git a/docs/patterns/mongokit.rst b/docs/patterns/mongokit.rst index 9d1b3e2a..cf072d5d 100644 --- a/docs/patterns/mongokit.rst +++ b/docs/patterns/mongokit.rst @@ -1,144 +1,7 @@ -.. mongokit-pattern: +:orphan: -MongoKit in Flask -================= +MongoDB with MongoKit +===================== -Using a document database rather than a full DBMS gets more common these days. -This pattern shows how to use MongoKit, a document mapper library, to -integrate with MongoDB. - -This pattern requires a running MongoDB server and the MongoKit library -installed. - -There are two very common ways to use MongoKit. I will outline each of them -here: - - -Declarative ------------ - -The default behavior of MongoKit is the declarative one that is based on -common ideas from Django or the SQLAlchemy declarative extension. - -Here an example :file:`app.py` module for your application:: - - from flask import Flask - from mongokit import Connection, Document - - # configuration - MONGODB_HOST = 'localhost' - MONGODB_PORT = 27017 - - # create the little application object - app = Flask(__name__) - app.config.from_object(__name__) - - # connect to the database - connection = Connection(app.config['MONGODB_HOST'], - app.config['MONGODB_PORT']) - - -To define your models, just subclass the `Document` class that is imported -from MongoKit. If you've seen the SQLAlchemy pattern you may wonder why we do -not have a session and even do not define a `init_db` function here. On the -one hand, MongoKit does not have something like a session. This sometimes -makes it more to type but also makes it blazingly fast. On the other hand, -MongoDB is schemaless. This means you can modify the data structure from one -insert query to the next without any problem. MongoKit is just schemaless -too, but implements some validation to ensure data integrity. - -Here is an example document (put this also into :file:`app.py`, e.g.):: - - from mongokit import ValidationError - - def max_length(length): - def validate(value): - if len(value) <= length: - return True - # must have %s in error format string to have mongokit place key in there - raise ValidationError('%s must be at most {} characters long'.format(length)) - return validate - - class User(Document): - structure = { - 'name': unicode, - 'email': unicode, - } - validators = { - 'name': max_length(50), - 'email': max_length(120) - } - use_dot_notation = True - def __repr__(self): - return '' % (self.name) - - # register the User document with our current connection - connection.register([User]) - - -This example shows you how to define your schema (named structure), a -validator for the maximum character length and uses a special MongoKit feature -called `use_dot_notation`. Per default MongoKit behaves like a python -dictionary but with `use_dot_notation` set to ``True`` you can use your -documents like you use models in nearly any other ORM by using dots to -separate between attributes. - -You can insert entries into the database like this: - ->>> from yourapplication.database import connection ->>> from yourapplication.models import User ->>> collection = connection['test'].users ->>> user = collection.User() ->>> user['name'] = u'admin' ->>> user['email'] = u'admin@localhost' ->>> user.save() - -Note that MongoKit is kinda strict with used column types, you must not use a -common `str` type for either `name` or `email` but unicode. - -Querying is simple as well: - ->>> list(collection.User.find()) -[] ->>> collection.User.find_one({'name': u'admin'}) - - -.. _MongoKit: http://bytebucket.org/namlook/mongokit/ - - -PyMongo Compatibility Layer ---------------------------- - -If you just want to use PyMongo, you can do that with MongoKit as well. You -may use this process if you need the best performance to get. Note that this -example does not show how to couple it with Flask, see the above MongoKit code -for examples:: - - from MongoKit import Connection - - connection = Connection() - -To insert data you can use the `insert` method. We have to get a -collection first, this is somewhat the same as a table in the SQL world. - ->>> collection = connection['test'].users ->>> user = {'name': u'admin', 'email': u'admin@localhost'} ->>> collection.insert(user) - -MongoKit will automatically commit for us. - -To query your database, you use the collection directly: - ->>> list(collection.find()) -[{u'_id': ObjectId('4c271729e13823182f000000'), u'name': u'admin', u'email': u'admin@localhost'}] ->>> collection.find_one({'name': u'admin'}) -{u'_id': ObjectId('4c271729e13823182f000000'), u'name': u'admin', u'email': u'admin@localhost'} - -These results are also dict-like objects: - ->>> r = collection.find_one({'name': u'admin'}) ->>> r['email'] -u'admin@localhost' - -For more information about MongoKit, head over to the -`website `_. +MongoKit is no longer maintained. See :doc:`/patterns/mongoengine` +instead.