Flask & peewee integration with DataTables server-side processing¶
As DataTables is a quite power and useful JavaScript library for manipulating
and displaying data, we intended to make integration of the client-side DataTables
scripts with the server-side processing based on Flask and peewee.
Installation¶
Note
As we have noticed, there’s already a Flask-DataTables library available
on PyPI. However, this package was intended for integration with SQLAlchemy
instead of peewee.
To start with, simply install the Flask-DataTables package from
PyPI:
pip install Flask-DataTables-peewee
or should you prefer the bleeding edge version:
git clone https://github.com/tekidltd/Flask-DataTables.git
cd Flask-DataTables
pip install .
Usage¶
Flask-DataTables is quite simple to use, just declare your data model in
the preferable way from peewee and voilà, that’s it.
Taking examples from the peewee documentation,
we can have a DataTables integrated data model just as below:
from flask import Flask
from flask_datatables import (CharField, DataTable, DateTimeField,
ForeignKeyField, Metadata, TextField)
DATABASE = 'postgresql://postgres:password@localhost:5432/my_database'
app = Flask(__name__)
app.config.from_object(__name__)
db_wrapper = DataTable(app)
class User(db_wrapper.Model):
username = CharField(unique=True)
class Meta(Metadata):
datatables = True
class Tweet(db_wrapper.Model):
user = ForeignKeyField(User, backref='tweets')
content = TextField()
timestamp = DateTimeField(default=datetime.datetime.now)
class Meta(Metadata):
datatables = True
And now, you may simply call Tweet.search
to perform the server-side processing queries.
