Devart Launches Python Connectors To Satisfy The Growing Demand For Python Database ToolsBy: Devart There is an exponential growth in Python's popularity among dynamic languages, despite 2023 continuing JavaScript's streak for the eleventh year in a row as the most commonly used programming language. This year, Python has overtaken SQL as the third most commonly used language and JavaScript as the first language for those who are not professional developers or those who are just learning how to code, according to the 2023 Developer Survey by StackOverflow, the largest community for developers. Anton Onufriienko, Head of Devart Business Unit: "Python is now the fastest-growing programming language, showing growth in both high-income and low-income countries across the world, influenced by the rise of data science and machine learning. We're reacting to the demands of Python developers by expanding our product line with the Python Connectors to help programmers around the world stay productive and efficient." Python connectors fully implement the Python Database API Specification v2.0 and are available as wheel packages for Windows, macOS, and Linux. Here is a selection of solutions one can find within the Python connectors. Direct Connection This solution lets you connect to relational and non-relational databases directly through TCP/IP, eliminating the need for database client libraries. A direct connection also increases the speed of data transmission between a Python application and the database server. Standard SQL Syntax in Cloud Connectors These connectors conform to the Python DB API 2.0 specification and fully support the ANSI SQL-92 standard. You can execute SQL statements against your cloud data just like you would normally work with relational databases, including complex queries containing different types of JOINs, ORDER BY and GROUP BY clauses, and aggregate functions. OAuth 2.0 Authorization in Cloud Connectors With OAuth 2.0, you can easily authorise Salesforce, BigCommerce, Zoho CRM, and other cloud applications that accept this authorization framework. Connection Pooling Connection pooling allows you to reduce the cost of opening and closing connections for each operation by maintaining a pool of pre-established connections to a database or a cloud service. SQLite Database Encryption The Python Connector for SQLite supports native SQLite database encryption without requiring you to purchase an encryption extension for SQLite. This functionality is available in the Direct mode, which uses a statically linked SQLite library. xBase Compatibility Python Connector for xBase supports the xBase family of databases, covering the following database formats: Visual FoxPro, FoxPro 2, dBase III – dBase 7, Clipper, Codebase, and HiPer-Six. The connector provides parameters for ignoring corrupted data and metadata errors in DBF tables. Corrupted data is skipped, while intact data is properly retrieved, which lets you access the data you thought were long lost. The solution supports the standard ANSI SQL-92 syntax and offers an internal data indexing mechanism that is way more efficient than native DBF indexes for complex queries. Support for ETL Tools These connectors are compatible with popular Python ETL tools: petl, pandas, and SQLAlchemy. The Python Connectors release includes database and cloud connectors for a variety of data sources, including databases and the cloud.
End
|