https://github.com/actuarial-tools/py-datatables

Framework agnostic data tables using SQLAlchemy.
https://github.com/actuarial-tools/py-datatables

Last synced: 7 months ago
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Framework agnostic data tables using SQLAlchemy.

• Host: GitHub
• URL: https://github.com/actuarial-tools/py-datatables
• Owner: actuarial-tools
• License: mit
• Created: 2021-04-04T01:20:44.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-04-04T01:32:56.000Z (about 4 years ago)
• Last Synced: 2024-08-13T07:09:33.217Z (10 months ago)
• Language: Python
• Size: 12.7 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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• jimsghstars - actuarial-tools/py-datatables - Framework agnostic data tables using SQLAlchemy. (Python)

README

        
===============================================

datatables |PyPi Version| |TravisCI| |Coverage|

===============================================

.. |PyPi Version| image:: http://img.shields.io/pypi/v/datatables.svg?style=flat

    :target: https://pypi.python.org/pypi/datatables

.. |TravisCI| image:: https://api.travis-ci.org/orf/datatables.svg

    :target: https://travis-ci.org/orf/datatables

.. |Coverage| image:: https://coveralls.io/repos/orf/datatables/badge.png?branch=master

  :target: https://coveralls.io/r/orf/datatables?branch=master

Installation

------------

The package is available on `PyPI `_ and is tested on Python 2.7 to 3.4

.. code-block:: bash

    pip install datatables

Usage

-----

Using Datatables is simple. Construct a DataTable instance by passing it your request parameters (or another dict-like

object), your model class, a base query and a set of columns. The columns list can contain simple strings which are

column names, or tuples containing (datatable_name, model_name), (datatable_name, model_name, filter_function) or

(datatable_name, filter_function).

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)

        # Use lazy=joined to prevent O(N) queries

        address     = relationship("Address", uselist=False, backref="user", lazy="joined")

    class Address(Base):

        __tablename__ = 'addresses'

        id          = Column(Integer, primary_key=True)

        description = Column(Text, unique=True)

        user_id     = Column(Integer, ForeignKey('users.id'))

**views.py (pyramid)**

.. code-block:: python

    @view_config(route_name="data", request_method="GET", renderer="json")

    def users_data(request):

        # User.query = session.query(User)

        table = DataTable(request.GET, User, User.query, [

            "id",

            ("name", "full_name", lambda i: "User: {}".format(i.full_name)),

            ("address", "address.description"),

        ])

        table.add_data(link=lambda o: request.route_url("view_user", id=o.id))

        table.searchable(lambda queryset, user_input: perform_search(queryset, user_input))

        table.searchable_column(

            lambda model_column, queryset, user_input:

                perform_column_search(model_column, queryset, user_input)

        )

        return table.json()

**views.py (flask)**

.. code-block:: python

    @app.route("/data")

    def datatables():

        table = DataTable(request.args, User, db.session.query(User), [

            "id",

            ("name", "full_name", lambda i: "User: {}".format(i.full_name)),

            ("address", "address.description"),

        ])

        table.add_data(link=lambda obj: url_for('view_user', id=obj.id))

        table.searchable(lambda queryset, user_input: perform_search(queryset, user_input))

        table.searchable_column(

            lambda model_column, queryset, user_input:

                perform_column_search(model_column, queryset, user_input)

        )

        return json.dumps(table.json())

**Global and individual column searching**

.. code-block:: python

    def perform_search(queryset, user_input):

        return queryset.filter(

            db.or_(

                User.full_name.like('%' + user_input + '%'),

                Address.description.like('%' + user_input + '%')

                )

            )

    def perform_column_search(model_column, queryset, user_input):

        return queryset.filter(model_column.like("%" + user_input + "%"))

**template.jinja2**

.. code-block:: html

    

        

            

                Id

                User name

                Address

            

        

        

        

    

    

        $("#clients_list").dataTable({

            serverSide: true,

            processing: true,

            ajax: "{{ request.route_url("data") }}",

            columns: [

                {

                    data: "id",

                    "render": function(data, type, row){

                        return $("<div>").append($("<a/>").attr("href", row.DT_RowData.link).text(data)).html();

                    }

                },

                { data: "name" },

                { data: "address" }

            ]