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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Odoo, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Odoo-connected Python applications and scripts for visualizing Odoo data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Odoo data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Odoo data in Python. When you issue complex SQL queries from Odoo, the driver pushes supported SQL operations, like filters and aggregations, directly to Odoo and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Accessing and integrating live data from Odoo has never been easier with CData. Customers rely on CData connectivity to:
Users frequently integrate Odoo with analytics tools such as Power BI and Qlik Sense, and leverage our tools to replicate Odoo data to databases or data warehouses.
Connecting to Odoo data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.
To connect, set the Url to a valid Odoo site, User and Password to the connection details of the user you are connecting with, and Database to the Odoo database.
Follow the procedure below to install the required modules and start accessing Odoo through Python objects.
Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:
pip install pandas pip install matplotlib pip install sqlalchemy
Be sure to import the module with the following:
import pandas import matplotlib.pyplot as plt from sqlalchemy import create_engine
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Odoo data.
engine = create_engine("odoo:///?User=MyUser&Password=MyPassword&URL=http://MyOdooSite/&Database=MyDatabase")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT name, email FROM res_users WHERE id = '1'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the Odoo data. The show method displays the chart in a new window.
df.plot(kind="bar", x="name", y="email") plt.show()👁 Odoo data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for Odoo to start building Python apps and scripts with connectivity to Odoo data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("odoo:///?User=MyUser&Password=MyPassword&URL=http://MyOdooSite/&Database=MyDatabase")
df = pandas.read_sql("SELECT name, email FROM res_users WHERE id = '1'", engine)
df.plot(kind="bar", x="name", y="email")
plt.show()
Download a Community License of the Odoo Connector to get started:
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👁 Odoo IconPython Connector Libraries for Odoo Data Connectivity. Integrate Odoo with popular Python tools like Pandas, SQLAlchemy, Dash & petl.