2 مستودعات
Specialized zero-copy mechanisms for transferring data into Python-specific memory structures like DataFrames.
Distinct from Zero-Copy Data Access: Distinct from Zero-Copy Data Access: specifically targets the integration with Python's memory model and data structures.
Explore 2 awesome GitHub repositories matching data & databases · Python Memory Integration. Refine with filters or upvote what's useful.
Connector-X is a high-performance SQL data extraction library and bridge for transferring relational database records into memory-efficient data structures. It functions as a parallel database connector and federated query engine capable of executing and joining queries across multiple remote database connections to aggregate data locally. The project distinguishes itself through a zero-copy approach to data loading, which transfers SQL query results into memory structures without duplicating data. It maximizes throughput by partitioning SQL queries into threads, employing parallel columnar a
Transfers data from relational databases into Python memory structures using a high-performance zero-copy approach.
This is a comprehensive Python programming course and technical curriculum designed to take users from foundational syntax to advanced development patterns. It serves as a multi-disciplinary educational suite covering programming fundamentals, object-oriented design, and data analysis. The project provides specialized guides on professional development techniques, including the use of decorators, generators for memory management, and dunder-method operator overloading. It also includes instructional material on executing parallel tasks through concurrency and multiprocessing to reduce executi
Provides a technical overview of reducing memory consumption using Python generators and lazy evaluation.