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Use pandas to Visualize Alfresco Data in Python

The CData Python Connector for Alfresco enables you use pandas and other modules to analyze and visualize live Alfresco data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Alfresco, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Alfresco-connected Python applications and scripts for visualizing Alfresco data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Alfresco data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Alfresco data in Python. When you issue complex SQL queries from Alfresco, the driver pushes supported SQL operations, like filters and aggregations, directly to Alfresco and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Alfresco Data

Connecting to Alfresco 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 to Alfresco, the following connection properties must be supplied: User, Password, and InstanceUrl. User and Password correspond to the login credentials that you use to access Alfresco in a web browser. InstanceUrl corresponds to the Alfresco instance you will be querying. For instance, if you expect your queries to hit https://search-demo.dev.alfresco.me/alfresco/api/-default-/public/search/versions/1/sql, you should supply search-demo.dev.alfresco.me for InstanceUrl.

Follow the procedure below to install the required modules and start accessing Alfresco through Python objects.

Install Required Modules

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

Visualize Alfresco Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Alfresco data.

engine = create_engine("alfresco:///?User=MyUsername& Password=MyPassword& Format=Solr& InstanceUrl=api-explorer.alfresco.com")

Execute SQL to Alfresco

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT DBID, Column1 FROM Alfresco WHERE Column2 = 'MyFilter'", engine)

Visualize Alfresco Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Alfresco data. The show method displays the chart in a new window.

df.plot(kind="bar", x="DBID", y="Column1")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the Alfresco Python Connector to start building Python apps and scripts with connectivity to Alfresco data. Reach out to our Support Team if you have any questions.



Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("alfresco:///?User=MyUsername& Password=MyPassword& Format=Solr& InstanceUrl=api-explorer.alfresco.com")
df = pandas.read_sql("SELECT DBID, Column1 FROM Alfresco WHERE Column2 = 'MyFilter'", engine)

df.plot(kind="bar", x="DBID", y="Column1")
plt.show()