The package is available on PyPI and is tested on Python 2.7 to 3.4
pip install datatablesUsing 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.
models.py
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)
@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)
@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
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
<table class="table" id="clients_list">
<thead>
<tr>
<th>Id</th>
<th>User name</th>
<th>Address</th>
</tr>
</thead>
<tbody>
</tbody>
</table>
<script>
$("#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" }
]
</script>