devart-bigcommerce-connector 1.3.0

New level of functionality and performance in data access via Python

Python Connector for BigCommerce

Python Connector for BigCommerce is a connectivity solution for accessing BigCommerce from Python applications to read and update data. It fully implements the Python DB API 2.0 specification. The connector is distributed as a wheel package for Windows, macOS, and Linux.

Standard SQL syntax

The connector fully supports the ANSI SQL standard and lets you execute SQL statements against your BigCommerce data just like you would normally work with relational databases. Simple queries are directly converted to BigCommerce API calls and executed on the BigCommerce side.

Connecting

To establish a connection to BigCommerce, import the connector and authenticate using basic or OAuth 2.0 authentication.

Import the connector

First, import the BigCommerce connector module:

import devart.bigcommerce as bigcommerce

Establish a connection

Connect to your BigCommerce store using the connect() module method and obtain a connection object.

You can connect to BigCommerce using either basic authentication or OAuth 2.0 authentication.

Basic authentication

For basic authentication, provide your BigCommerce server URL and authentication credentials:

my_connection = bigcommerce.connect(
    Version="Ver2",    Authentication="Basic",    Server="your_bigcommerce_url",    UserId="your_username",    AuthenticationToken="your_auth_token"
)

Replace the example values with your actual connection values.

OAuth 2.0 authentication

For OAuth 2.0 authentication, provide your OAuth credentials:

my_connection = bigcommerce.connect(
    Version="Ver2",
    Authentication="OAuth",
    StoreId="your_store_hash",
    ClientId="your_client_id",
    AccessToken="your_access_token"
)

Replace the example values with your actual connection values.

Querying data

Once connected to BigCommerce, you can execute SQL queries to retrieve data from your BigCommerce data.

Execute a query

Create a cursor object using the cursor() connection method.

my_cursor = my_connection.cursor()

Execute the SQL statement using the execute() cursor method.

my_cursor.execute("SELECT * FROM employees")

Retrieve the result set using one of the fetch*() cursor methods.

for row in my_cursor.fetchall(): 
    print(row)

Parameterized queries

You can use parameterized queries to pass variable values to your SQL statements. This allows you to reuse the same query with different data and helps to prevent SQL injection attacks.

Pass parameters as a list or tuple to the execute() method:

query = "SELECT Id, Name FROM Contact WHERE Name = ? AND Email = ?"
params = ["Jordan Sanders", "[e-mail]"]
my_cursor.execute(query, params)
results = my_cursor.fetchall()
for row in results:
    print(row)

Each placeholder ? in the query is replaced with a corresponding value from the parameter list.

Ordering and activating the license

You can purchase a license for the connector on the ordering page:
https://www.devart.com/python/bigcommerce/ordering.html

To activate the license, follow the instructions in the documentation:
https://docs.devart.com/python/bigcommerce/activate-a-license.htm

What's new

Python Connector for BigCommerce 1.3

• Added support for Python 3.14