Metadata-Version: 2.1
Name: pybulk
Version: 0.1
Summary: PyBulk is a Python module that to allow simple and fast bulk data insertion into databases
Home-page: https://github.com/MrLpk/pybulk
Author: pengkailiao
Author-email: pengkailiao@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: PyMySQL (>=0.9.3)
Requires-Dist: SQLAlchemy (>=1.3.15)

# pybulk
PyBulk is a Python module that wraps PyMySQL to allow simple and fast bulk data insertion into databases. With PyBulk, you can insert thousands of records into a database table in just a few lines of code.
PyBulk builds on top of the PyMySQL library and connection pool to efficiently reuse connections and minimize latency. It handles all the low-level details of executing multiple INSERT statements while protecting your database from overload.
Some of the main features of PyBulk include:
•Simple API: Insert bulk data with just a few function calls. No complicated setup required.
•Speed: Leverages PyMySQL's connection pool to quickly insert thousands of records.
•Safety: Limits the number of SQL queries executed at a time to protect your database from overload.
•Reliability: Includes error handling and recovery mechanisms to handle transient database errors. Retries failed queries automatically.
•Support for REPLACE INTO: Upsert support allows you to replace existing records in a table or insert new ones.
•Compatibility: Works with MySQL, MariaDB and AWS RDS. Compatible with Python 2 and 3.
PyBulk allows you to focus on your application's logic rather than spending time building infrastructure to handle database load. It is a robust but lightweight solution ideal for batch data processing applications.


