wave
great_expectations
| wave | great_expectations | |
|---|---|---|
| 21 | 15 | |
| 3,864 | 9,479 | |
| 0.8% | 1.0% | |
| 9.1 | 9.9 | |
| 11 days ago | 4 days 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
great_expectations
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Data Quality at Scale with Great Expectations, Spark, and Airflow on EMR
Great Expectations (GE) is an open-source data validation tool that helps ensure data quality.
- Looking for Unit Testing framework in Database Migration Process
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Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
GE is arguably the most well known OSS alternative to Soda Core. The third option is deequ, originally developed and released in OSS by AWS. Our community has told us that Soda Core is different because it’s easy to get going and embed into data pipelines. And it also allows some of the check authoring work to be moved to other members of the data team. I'm sure there are also scenarios where Soda Core is not the best option. For example, when you only use Pandas dataframes or develop in Scala.
- Greatexpectations - Always know what to expect from your data.
- Greatexpectations – Always know what to expect from your data
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Package for drift detection
great_expectations: https://github.com/great-expectations/great_expectations
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[D] Do you use data engineering pipelines for real life projects?
For example I just found "Great Expectations" and "Kedro", "Flyte" and I was wondering at which point in time and project complexity should we choose one of these tools instead of the ancient cave man way?
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Data pipeline suggestions
Testing: GreatExpectations
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
- [P] Deepchecks: an open-source tool for high standards validations for ML models and data.
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
reactpy - It's React, but in Python
kedro-great - The easiest way to integrate Kedro and Great Expectations
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
nicegui - Create web-based user interfaces with Python. The nice way.
re_data - re_data - fix data issues before your users & CEO would discover them 😊
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!
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models