Integrates SQLAlchemy with DataTables (framework Flask)
Project description
====================
Flask-restful only version of orf/datatables with Flask-restless style filtering
====================
Additional Functionality
------------
One thing I needed to do so that this would support our needs internally is
to support arbitrary join depth to be able to do search and sort functionality
on the results. With Orf's version, I was only able to order by or search on 2
levels deep of a query result. Now that level is arbitrary such that you can
provide a column on say a Subnet table that is associated with a location
through relations like subnet.vlan.switch.rack.location and make the location name
filterable AND orderable with just "vlan__switch__rack__location__name"
Installation
------------
The package is available on PyPI and is passing tests on Python 2.7, 3.3 and 3.4
Working on getting this on PyPI
.. code-block:: bash
pip install flask_datatables
Usage
-----
This is SUPER simple. In datatables I provide a function called get_resource that can be used to create a
datatables api endpoint with full flask-restless style filtering built in.
Additional data such as hyperlinks can be added via DataTable.add_data, which accepts a callable that is called for
each instance. Check out the usage example below for more info.
Example
-------
**models.py**
.. code-block:: python
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
full_name = Column(Text)
created_at = Column(DateTime, default=datetime.datetime.utcnow)
class Address(Base):
__tablename__ = 'addresses'
id = Column(Integer, primary_key=True)
description = Column(Text)
user_id = Column(Integer, ForeignKey('users.id'))
user = relationship("User", backref=backref("address", uselist=False))
def __repr__(self):
return "{}".format(self.description)
**api.py**
.. code-block:: python
from model import Session, User, Address
from datatables import *
app = Flask(__name__)
api = Api(app)
# add User resource
resource, path, endpoint = get_resource(Resource, User, Session, basepath="/")
api.add_resource(resource, path, endpoint=endpoint)
# add Address resource
resource, path, endpoint = get_resource(Resource, Address, Session, basepath="/")
api.add_resource(resource, path, endpoint=endpoint)
if __name__ == '__main__':
app.run(host='127.0.0.1', port=5001, debug=True)
Flask-restful only version of orf/datatables with Flask-restless style filtering
====================
Additional Functionality
------------
One thing I needed to do so that this would support our needs internally is
to support arbitrary join depth to be able to do search and sort functionality
on the results. With Orf's version, I was only able to order by or search on 2
levels deep of a query result. Now that level is arbitrary such that you can
provide a column on say a Subnet table that is associated with a location
through relations like subnet.vlan.switch.rack.location and make the location name
filterable AND orderable with just "vlan__switch__rack__location__name"
Installation
------------
The package is available on PyPI and is passing tests on Python 2.7, 3.3 and 3.4
Working on getting this on PyPI
.. code-block:: bash
pip install flask_datatables
Usage
-----
This is SUPER simple. In datatables I provide a function called get_resource that can be used to create a
datatables api endpoint with full flask-restless style filtering built in.
Additional data such as hyperlinks can be added via DataTable.add_data, which accepts a callable that is called for
each instance. Check out the usage example below for more info.
Example
-------
**models.py**
.. code-block:: python
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
full_name = Column(Text)
created_at = Column(DateTime, default=datetime.datetime.utcnow)
class Address(Base):
__tablename__ = 'addresses'
id = Column(Integer, primary_key=True)
description = Column(Text)
user_id = Column(Integer, ForeignKey('users.id'))
user = relationship("User", backref=backref("address", uselist=False))
def __repr__(self):
return "{}".format(self.description)
**api.py**
.. code-block:: python
from model import Session, User, Address
from datatables import *
app = Flask(__name__)
api = Api(app)
# add User resource
resource, path, endpoint = get_resource(Resource, User, Session, basepath="/")
api.add_resource(resource, path, endpoint=endpoint)
# add Address resource
resource, path, endpoint = get_resource(Resource, Address, Session, basepath="/")
api.add_resource(resource, path, endpoint=endpoint)
if __name__ == '__main__':
app.run(host='127.0.0.1', port=5001, debug=True)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
flask_datatables-0.6.9.tar.gz
(20.7 kB
view details)
Built Distributions
flask_datatables-0.6.9-py3.5.egg
(48.5 kB
view details)
flask_datatables-0.6.9-py3.4.egg
(48.6 kB
view details)
flask_datatables-0.6.9-py3.3.egg
(49.2 kB
view details)
flask_datatables-0.6.9-py3.2.egg
(48.6 kB
view details)
flask_datatables-0.6.9-py2.7.egg
(47.9 kB
view details)
File details
Details for the file flask_datatables-0.6.9.tar.gz
.
File metadata
- Download URL: flask_datatables-0.6.9.tar.gz
- Upload date:
- Size: 20.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7e838c1a6ece1c1680d855f5ed680ec0321972e7393ab0ed0e880a1821f3f01a |
|
MD5 | 6fa61d9f419d4e46fab07793bab8d7df |
|
BLAKE2b-256 | 1b237f76bcbf49ab9a0604f8283f34b5ed821948472e5e2e98bb95128fe69a1b |
Provenance
File details
Details for the file flask_datatables-0.6.9-py3.5.egg
.
File metadata
- Download URL: flask_datatables-0.6.9-py3.5.egg
- Upload date:
- Size: 48.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 65637be5aa3a3782ae753a59deba844a948fcacde36c4c9e74e98a8286b60d25 |
|
MD5 | 90cebb0545d4d7730558af74c5d53c5d |
|
BLAKE2b-256 | 22a1dd37fad7e12ba4b8d3b7d1656c8a19e04ae593077a37089f98b6fed002c0 |
Provenance
File details
Details for the file flask_datatables-0.6.9-py3.4.egg
.
File metadata
- Download URL: flask_datatables-0.6.9-py3.4.egg
- Upload date:
- Size: 48.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a42da7686f1330eb2ccdd99a44e0bc5f2ce4fbe0a50353c32da36de86a29b7a8 |
|
MD5 | 2cd7bd5cc616531e9bb74e827cdb75d4 |
|
BLAKE2b-256 | 65b6d561b6bf29c287eb49950be228fa224a17f1b46f176402594ab9652a8557 |
Provenance
File details
Details for the file flask_datatables-0.6.9-py3.3.egg
.
File metadata
- Download URL: flask_datatables-0.6.9-py3.3.egg
- Upload date:
- Size: 49.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 701ecdcbbe3460502cf05dcfd1392f99ee391abce9d04320ca8e94b280f0cd96 |
|
MD5 | ffc06b898162e9e909774b4f2b137dfa |
|
BLAKE2b-256 | fc83123a61e4c3e2f9c18ac77dd166c79d81f434eecbabfe24791a38a15fdad6 |
Provenance
File details
Details for the file flask_datatables-0.6.9-py3.2.egg
.
File metadata
- Download URL: flask_datatables-0.6.9-py3.2.egg
- Upload date:
- Size: 48.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 69f6bff1697bf25a04fbc25ee0de87f8b8d7f6538b3df9ee099092d94baf0337 |
|
MD5 | e6f4ca32b429dbd8a24912905860a8dc |
|
BLAKE2b-256 | 011540882941b686010e216c93af052bfd5592387965c6898283b30753b95f56 |
Provenance
File details
Details for the file flask_datatables-0.6.9-py2.7.egg
.
File metadata
- Download URL: flask_datatables-0.6.9-py2.7.egg
- Upload date:
- Size: 47.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 110ecbbf422e46097d84cfae436136018af3f82c6bfcf332eeab9756f6bb635b |
|
MD5 | 97f7d33c5e175aa0774312c2a8576797 |
|
BLAKE2b-256 | e51e254153d195a3469c2fbe900144ec4ffffc355923225540b42a9b0f08e7b2 |