What is PLG?
PLG is an open-source platform aimed at helping developers build high-performance Python applications. It includes a set of libraries and tools that allow you to leverage parallelism, distributed computing, and optimized data pipelines.
Some of the key features of PLG include:
- Integrated support for multiprocessing and multithreading to speed up CPU-bound workloads
- Cluster computing capabilities to coordinate jobs across multiple machines
- Managed data streams and pipelines for efficient data processing and ETL tasks
- Integration with common data science libraries like NumPy and Pandas
- Flexible architecture that runs in any Python environment - on laptops, servers, Hadoop, or cloud infrastructure
By handling common parallelism, distributed computing, and data routing challenges, PLG enables developers to focus on their application logic instead of infrastructure. It provides simple APIs for leveraging all available computing resources without the overhead of managing servers, networks, connections, etc.
PLG is suited for data engineering teams, data scientists, and application developers building analytics, machine learning, or computational pipelines in Python. It works on Linux, macOS, and Windows.