wave
clearml
| wave | clearml | |
|---|---|---|
| 21 | 20 | |
| 3,867 | 5,279 | |
| 0.9% | 2.1% | |
| 9.1 | 7.7 | |
| 3 days ago | 1 day ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
wave
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Streamlit alternatives but for Rust?
https://streamlit.io/ https://wave.h2o.ai/ https://reflex.dev/
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Launch HN: Pynecone (YC W23) – Web Apps in Pure Python
Looks similar to Nitro https://nitro.h2o.ai/ and Wave https://wave.h2o.ai/ - both open source. Nitro already works with WebAssembly via Pyodide. (Author here)
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Nice GUI
To write web gui in Python, there are some other open source alternatives.
If just want to port simple shell interactive interface to web gui, can check https://github.com/pywebio/PyWebIO
If want to get a production level dashboard by using Python, https://wave.h2o.ai/ <>
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Show HN: Hstream – quick Python web apps (Streamlit alternative using Htmx)
I think the demo site may have been hugged to death. It's not rendering anything for me.
I think it's also worth giving a shoutout to wave in this space; they have quite a few components you can use out-of-the-box https://github.com/h2oai/wave
- PyScript
- Realtime Web Apps and Dashboards for Python
- Realtime Web Apps and Dashboards for Python and R
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[D] What do you use to build UIs for your projects?
H2O Wave : https://wave.h2o.ai
- Creating a web app in Python without knowledge of HTML/CSS/JavaScript
clearml
- FLaNK Stack Weekly 12 February 2024
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clearml VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
- Is there any workflow orchestrator that is Hydra friendly ?
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Show HN: Open-source infra for data scientists
It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products?
It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean?
https://github.com/allegroai/clearml
https://codeocean.com/
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[D] Drop your best open source Deep learning related Project
Hi there. ClearML is our open-source solution which is part of the PyTorch ecosystem. We would really appreciate it if you read our README and starred us if you like what you see!
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code.
- Everything you need to log, share, and version experiments, orchestrate pipelines, and scale within one open-source MLOps solution.
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
MLflow - Open source platform for the machine learning lifecycle
reactpy - It's React, but in Python
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
nicegui - Create web-based user interfaces with Python. The nice way.
kedro-great - The easiest way to integrate Kedro and Great Expectations
dephell - :package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
pglet - Pglet - build internal web apps quickly in the language you already know!
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️