datatables-server 3.0.0b1

Server-side processing for DataTables and Editor using SQLAlchemy Core

DataTables Python server-side libraries

This is a collection of Python libraries to provide easy server-side support for the DataTables Javascript library - the Javascript table library.

These libraries provide support for:

• Server-side processing - work with millions of rows
• Editor - CRUD UI for DataTables
• ColumnControl - Column search controls for DataTables
• SearchBuilder - Complex search logic UI

SQLAlchemy Core is used to provide the SQL database integration, allowing a wide range of databases to be supported. Furthermore, the library is framework-agnostic: use it with Flask, FastAPI, Django, or any other Python web framework that can pass a request body and a SQLAlchemy Connection or Engine to a route handler.

Installation

pip install datatables_server

SQLAlchemy 2.x and Python date utilities are the two required dependencies for this library and are installed automatically with the above command. A database driver (e.g. psycopg2, pymysql, aiosqlite) must be installed separately.

Quick Start

The following shows a Flask endpoint that will accept both DataTables and Editor requests:

from flask import Flask, request, jsonify
from sqlalchemy import create_engine
from datatables_server import Editor, Field

app = Flask(__name__)
engine = create_engine("postgresql+psycopg2://user:pass@localhost/mydb")

@app.route("/api/staff", methods=["GET", "POST", "PUT", "DELETE"])
def staff():
    with engine.connect() as db:
        editor = (
            Editor(db, "staff", "id")
            .field(Field("first_name"))
            .field(Field("last_name"))
            .field(Field("position"))
            .field(Field("salary"))
        )
        response = editor.process(request.values.to_dict(flat=True))
    return jsonify(response)

Similarly, if your table is readonly, the DataTable and Column classes can be used (this will support DataTables' client-side or server-side processing modes):

from flask import Flask, request, jsonify
from sqlalchemy import create_engine
from datatables_server import DataTable, Column

app = Flask(__name__)
engine = create_engine("postgresql+psycopg2://user:pass@localhost/mydb")

@app.route("/api/staff", methods=["GET"])
def staff():
    with engine.connect() as db:
        table = (
            DataTable(db, "staff", "id")
            .column(Column("first_name"))
            .column(Column("last_name"))
            .column(Column("position"))
            .column(Column("salary"))
        )
        response = table.process()
    return jsonify(response)

Documentation

For full documentation, please refer to the DataTables site.

License

MIT — see LICENSE for full text.