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Python

Epicor Kinetic Python Connector

Read, write, and update Epicor Kinetic with Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Epicor Kinetic!

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CData Drivers now work with AI Coding tools

Python Connector Libraries for Epicor Kinetic Data Connectivity. Integrate Epicor Kinetic with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Epicor Kinetic data with Python and any Python-based applications.

Features

Compatible with Epicor REST Services API v.1 and v.2
Support for atomic and batch update operations
Support for Business Activity Queryies (BAQs)
Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Connect to live Epicor Kinetic data, for real-time data access with the Epicor Kinetic ODBC Driver
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Epicor Kinetic Connector.

Specifications

Python Database API (DB-API) Modules for Epicor Kinetic with bi-directional access.
Write SQL, get Epicor Kinetic data. Access Epicor Kinetic through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Simple command-line based data exploration of Epicor Kinetic SalesOrders, PurchaseOrders, Accounts, and more!
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Epicor Kinetic

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Epicor Kinetic with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Epicor Kinetic from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Epicor Kinetic
  • Query Epicor Kinetic to retrieve or update data
  • Connect your Epicor Kinetic data with Python data tools.


Connecting to Epicor Kinetic in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.epicorkinetic as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM SalesOrders")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("epicorkinetic///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM SalesOrders", engine)

df.plot()
plt.show()

Visualize Epicor Kinetic Data with pandas

The data-centric interfaces of the Epicor Kinetic Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

More than read-only: full update/CRUD support

Epicor Kinetic Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the Epicor Kinetic Connector as easily as interacting with a database table.

AI-assisted development with CData CLI

Build Epicor Kinetic integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Epicor Kinetic schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Epicor Kinetic.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI