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In this version all tables are read into memory upon "connecting" to the database and "touched" tables are written out upon checkpoint. Each table is represented as a separate file in the destination directory, and there is a "data definition" file as well (a list of data definition declarations).
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
Django (/ ˈ dʒ æ ŋ ɡ oʊ / JANG-goh; sometimes stylized as django) [5] is a free and open-source, Python-based web framework that runs on a web server. It follows the model–template–views (MTV) architectural pattern.
DuckDB is an open-source column-oriented relational database management system (RDBMS). [1] It is designed to provide high performance on complex queries against large databases in embedded configuration, [2] such as combining tables with hundreds of columns and billions of rows.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]
A lookup table, which contains, as keys, the case values and, as values, the part under the case statement. (In some languages, only actual data types are allowed as values in the lookup table. In other languages, it is also possible to assign functions as lookup table values, gaining the same flexibility as a real switch statement.
This simple control table directs program flow according to the value of the single input variable. Each table entry holds a possible input value to be tested for equality (implied) and a relevant subroutine to perform in the action column. The name of the subroutine could be replaced by a relative subroutine number if pointers are not supported
Airflow is written in Python, and workflows are created via Python scripts. Airflow is designed under the principle of "configuration as code". While other "configuration as code" workflow platforms exist using markup languages like XML, using Python allows developers to import libraries and classes to help them create their workflows.