PyFlow – Visual scripting framework for Python – NodeRED alternative?

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  • PyFlow

    Visual scripting framework for python - https://wonderworks-software.github.io/PyFlow

  • Ryven

    Flow-based visual scripting for Python

  • Interesting, came across https://ryven.org/ recently which looks in the same domain.

    Any practical use cases of either being used?

    Huge fan of NodeRED, always thought the paradigm could be leveraged for other heavy workflow applications

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • openapi-generator

    OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)

  • Very interesting.

    I recently learned about OpenAPI generator [], which uses a spec-first approach to generate boilerplate for several frameworks, including Flask and FastAPI.

    I would like to build or find a no code / visual tool that lets you build a JSON Schema file, and then generates boilerplate for you. I want to move on from rigid cookiecutter tools that make you go through 15 or so steps and force you to start over if you make the tiniest mistake.

    https://github.com/OpenAPITools/openapi-generator

  • imgui-node-editor

    Node Editor built using Dear ImGui

  • It looks nice. If UI performance is a concern, one could move the GUI part to C++ and do some quick pybind11 Python bindings for better performance.

    I've used this C++ ImGui node editor with similar features for some hacky synthesizer gui using this library: https://github.com/thedmd/imgui-node-editor

  • debug-toolkit

    A modern code-injection framework for Python. Like Pyrasite but Kubernetes-aware.

  • Very cool.

    We're designing an automations engine for Kubernetes ("Zapier/IFTTT for devops") and have thought about adding a UI for automating stuff visually. So far, simple YAML configurations have won out and we're still debating the benefits of a UI.

    Does anyone have experience using tools like this at scale or for technical domains? (E.g. devops.) Would love to hear a convincing case why a UI is better than YAML. You can see the configuration we currently offer at http://robusta.dev/

  • denoflow

    Configuration as Code, use YAML to write automated workflows that run on Deno, with any Deno modules, Typescript/Javascript codes

  • I'm doing something[0] similar with Deno, currently it configures workflows based on yaml files, but my goal is to make a gui tool to help generate yaml config files. My work is still very early stage, currently it can use any remote Deno module or typescript/javascript to execute steps and fetch and filter source data.

    The Deno runtime is great for workflows because Deno is lightweight and can import modules using arbitrary URLs.

    [0]: https://github.com/denoflow/denoflow

  • integration

    HACS gives you a powerful UI to handle downloads of all your custom needs.

  • If you write it in Python and add it as HomeAssistant plugin (http://hacs.xyz) I think you will get a lot of users, and help from the community building it further

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  • DearPyGui

    Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies

  • DearPyGui is built with C++ ImGui and includes a node editor [1]. It’s actively maintained and I’ve found it a joy to work with.

    [1] https://github.com/hoffstadt/DearPyGui#node-editor

  • hetida-designer

    hetida designer is a graphical composition tool for analytical workflows based on the Python data science stack.

  • Shameless Plug: We are working on a similar tool: https://github.com/hetida/hetida-designer

    We have no GUI programming in the broader sense, in our case nodes are simply run one after another (DAG).

    Our tool is a web application and workflows can be triggered / executed via API, which allows for automatisation. Workflows can be nested and are tagged with a version tag making production runs reproducible. It is very much taylored to (simple) Data Science use cases with the goal to make the Python data science stack accessible for Business Experts (or power users), maybe collaborating with Data Scientists.

    It is actively developed, and our industrial customers happily use it, however it is still in early development state.

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