datapane
Redash
Our great sponsors
datapane | Redash | |
---|---|---|
30 | 38 | |
1,349 | 24,948 | |
0.4% | 1.2% | |
7.3 | 9.5 | |
7 months ago | 3 days ago | |
Python | Python | |
Apache License 2.0 | BSD 2-clause "Simplified" License |
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.
datapane
- Datapane: Build and share data reports in 100% Python
-
Polars: Company Formation Announcement
If you're looking for an easy way to build an HTML report using Python, you might find Datapane (https://github.com/datapane/datapane) helpful. I'm one of the people building it! We don't support polars (yet, on the roadmap) but we do support pandas so you can convert to a pandas DataFrame and include your data and any plots, etc.
-
JupyterLab 4.0
If you're interested in an easier way to create reports using Python and Plotly/Pandas, you should check out our open-source library, Datapane: https://github.com/datapane/datapane - you can create a standalone, redistributable HTML file in a few lines of Python.
-
Evidence – Business Intelligence as Code
You might be interested in what we're hacking on at Datapane (I'm one of the founders): https://github.com/datapane/datapane.
You can create standalone HTML data reports from Python/Jupyter in ~3 lines of code: https://docs.datapane.com/reports/overview/
-
Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
You can build web apps from Jupyter using Datapane [0]. I'm one of the founders, so let me know if I can help at all.
You can either export a static site [1] (and host on GH pages or S3), or, if you need backend logic, you can add Python functions [2] and serve on your favourite host (we use Fly).
We have specific Jupyter integration to automatically convert your notebook into an app [3].
[0] https://github.com/datapane/datapane
[1] https://docs.datapane.com/reference/reports/#datapane.proces...
[2] https://docs.datapane.com/apps/overview/
[3] https://docs.datapane.com/reports/jupyter-integration/#conve...
- Datapane – Build full-stack data apps in 100% Python
-
Datapane - Build full-stack data apps in 100% Python
Our GitHub is https://github.com/datapane/datapane and you can get started here: https://docs.datapane.com/quickstart/
- Datapane: Build internal analytics products in minutes using Python
-
Datapane - Build internal data products in 100% Python
Thanks a lot! Yes, absolutely, a few people have brought this up and working working on removing the header right now. If I can help at all, feel free to reach us on GH Discussions: https://github.com/datapane/datapane/discussions
- Datapane/datapane: Build full-stack data analytics apps in Python
Redash
- Redash: Connect to data source, easily visualize, dashboard and share your data
- FLaNK Stack 26 February 2024
- Contribuir con proyectos Open Source
-
Auto reloading Odoo with Docker
It seems like there may be an issue with Watchdog on Apple Silicon.
-
Tool or service for querying and exposing database through API
I am looking for service or tool similiar to Metabase or Redash that allows me to add data source - for example Postgres connection, and create raw SQL queries that can be shared or exposed through API. So instead of keeping raw SQL code somewhere, my other service would call this tool e.g. http://microservice/query=1?param1=xx&page=2 and get the results from the DB. These calls are internal only and part of ETL processes, but of course authentication would be required.
-
A PostgreSQL Docker container that automatically upgrades PostgreSQL
Yeah, a lot of the time I'd agree with you.
This container came about for the Redash project (https://github.com/getredash/redash), which has been stuck on PostgreSQL 9.5 (!) for years.
Moving to a new PostgreSQL container version is easy enough for new installations, but rolling that kind of change out to an existing userbase isn't so pretty.
For people familiar with the command line, PostgreSQL, and Docker then no worries.
But a large number of Redash deployments seem to have been done by people not skilled in those things. "We deployed it from the Digital Ocean droplet / AWS image / etc!"
For those situations, something that takes care of the database upgrade process automatically is the better approach. :)
-
Did anyone try Openblocks for multi-tenant client reporting?
I have tried Metabase, Redash beore (both self hosted open source versions), from my experience I find Metabase a bit easy to work with.
-
Best apps for transitioning from Spreadsheets to SQLite?
Regarding visualization tools, sqliteviz has proven to be the best I've found so far. Their web app runs locally but has some trackers, so I run it locally via a simple, static HTTP server. Falcon and Redash seem like overkill for my needs.
-
Chartbrew – create live reporting dashboards from APIs, MongoDB, Firestore, etc.
Redash seems to be dead or at least in hibernation. There hasn't been a release in over a year.
https://github.com/getredash/redash/issues/5891
-
Real Time Data Infra Stack
redash
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
dash - Data Apps & Dashboards for Python. No JavaScript Required.
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
superset - Apache Superset is a Data Visualization and Data Exploration Platform
bokeh - Interactive Data Visualization in the browser, from Python
Druid - Apache Druid: a high performance real-time analytics database.