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Dapr (Distributed Application Runtime) is a free and open source runtime system designed to support cloud native and serverless computing. [2] Its initial release supported SDKs and APIs for Java, .NET, Python, and Go, and targeted the Kubernetes cloud deployment system. [3] [4] The source code is written in the Go programming language.
The Kubernetes API can be extended using Custom Resources, which represent objects that are not part of the standard Kubernetes installation. These custom resources are declared using Custom Resource Definitions (CRDs), which is a kind of resource that can be dynamically registered and unregistered without shutting down or restarting a cluster ...
FastAPI is a high-performance web framework for building HTTP-based service APIs in Python 3.8+. [3] It uses Pydantic and type hints to validate , serialize and deserialize data. FastAPI also automatically generates OpenAPI documentation for APIs built with it. [ 4 ]
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.
A commercial PDF editor, markup and collaboration product aimed at engineering and architectural markets. Foxit Reader: Freeware: Highlight text, draw lines, measure distances of PDF documents. Foxit PDF Editor Suite: Free trial: Integrated PDF Editing and eSign anywhere. Optionally, ChatGPT+ gDoc Fusion: Proprietary/Shareware
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.
Apache Flink includes two core APIs: a DataStream API for bounded or unbounded streams of data and a DataSet API for bounded data sets. Flink also offers a Table API, which is a SQL-like expression language for relational stream and batch processing that can be easily embedded in Flink's DataStream and DataSet APIs.
Applications written in Go, PHP, Java, Python, Node.js, .NET, and Ruby are supported by the App Engine, and other languages can be supported at an additional cost. [4] The free version of the service offers a standard environment with limited resources. Fees are charged for additional storage, bandwidth, or instance hours. [5]