If the Database property is not specified, the data provider connects to the user's default database.Īfter installing the CData PostgreSQL Connector, follow the procedure below to install the other required modules and start accessing PostgreSQL through Python objects. To connect to PostgreSQL, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. For this article, you will pass the connection string as a parameter to the create_engine function. Create a connection string using the required connection properties. When you issue complex SQL queries from PostgreSQL, the driver pushes supported SQL operations, like filters and aggregations, directly to PostgreSQL and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).Ĭonnecting to PostgreSQL data looks just like connecting to any relational data source.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live PostgreSQL data in Python.
Python connect to postgresql how to#
This article shows how to connect to PostgreSQL with the CData Python Connector and use petl and pandas to extract, transform, and load PostgreSQL data.
With the CData Python Connector for PostgreSQL and the petl framework, you can build PostgreSQL-connected applications and pipelines for extracting, transforming, and loading PostgreSQL data. The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively.
0 kommentar(er)
