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py2exe is a Python extension which converts Python scripts (.py) into Microsoft Windows executables (.exe). These executables can run on a system without Python installed. [3] It is the most common tool for doing so.
Docker Compose is a tool for defining and running multi-container Docker applications. [29] It uses YAML files to configure the application's services and performs the creation and start-up process of all the containers with a single command.
All web applications, both traditional and Web 2.0, are operated by software running somewhere. This is a list of free software which can be used to run alternative web applications. Also listed are similar proprietary web applications that users may be familiar with. Most of this software is server-side software, often running on a web server.
In a similar approach to Fedora CoreOS, Azure Linux only has the basic packages needed to support and run containers. Common Linux tools are used to add packages and manage security updates . Updates are offered either as RPM packages or as complete disk images that can be deployed as needed.
Miscellaneous improvements: improved documentation, better testing, run/release scripts, improved packaging, Docker container for systemds, support for lambda expressions, bug fixes. Removed MapReduce compiler and runtime backend, pydml parser, Java-UDF framework, script-level debugger.
For the duration of an orchestration task, a process running the module communicates with the controlling machine with a JSON-based protocol via its standard input and output. [18] When Ansible is not managing a node, it does not consume resources on the node because no daemons are run or software installed. [17]
Fooocus is an open source generative artificial intelligence program that allows users to generate images from a text prompt. [3] [4] It uses Stable Diffusion as the base model for its image capabilities as well as a collection of default settings and prompts to make the image generation process more streamlined.
DAGs can be run either on a defined schedule (e.g. hourly or daily) or based on external event triggers (e.g. a file appearing in Hive [5]). Previous DAG-based schedulers like Oozie and Azkaban tended to rely on multiple configuration files and file system trees to create a DAG, whereas in Airflow, DAGs can often be written in one Python file. [6]