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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.
Dask is an open-source Python library for parallel computing. Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
PyTorch defines a class called Tensor (torch.Tensor) to store and operate on homogeneous multidimensional rectangular arrays of numbers. PyTorch Tensors are similar to NumPy Arrays, but can also be operated on a CUDA -capable NVIDIA GPU. PyTorch has also been developing support for other GPU platforms, for example, AMD's ROCm [26] and Apple's ...
Apache Superset is an open-source software application for data exploration and data visualization able to handle data at petabyte scale . The application started as a hack-a-thon project by Maxime Beauchemin (creator of Apache Airflow ) while working at Airbnb and entered the Apache Incubator program in 2017. [ 1 ]
PyCharm Edu. PyCharm is an integrated development environment (IDE) used for programming in Python. It provides code analysis, a graphical debugger, an integrated unit tester, integration with version control systems, and supports web development with Django. PyCharm is developed by the Czech company JetBrains and built on their IntelliJ platform.
Linux is a Unix-like computer operating system assembled under the model of free and open-source software development and distribution. Most Linux distributions, as collections of software based around the Linux kernel and often around a package management system, provide complete LAMP setups through their packages.
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [73] and metaobjects). [74] Many other paradigms are supported via extensions, including design by ...
Core Python Programming is a textbook on the Python programming language, written by Wesley J. Chun. The first edition of the book was released on December 14, 2000. [1] The second edition was released several years later on September 18, 2006. [2] Core Python Programming is mainly targeted at higher education students and IT professionals. [3]