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How to create a dashboard in Python with Jupyter Notebook

188 点作者 pplonski86将近 3 年前

12 条评论

lmeyerov将近 3 年前
Awesome to see!<p>We&#x27;ve been encouraging Graphistry users to look at Streamlit for the low-code side (and getting bundled into our next release for public+private pydata GPU dashboarding!) or Databricks dashboards. Then at the expense of significantly more code &#x2F; complexity without going full Flask&#x2F;Django, we generally recommend switching to Dash&#x2F;Voila&#x2F;etc for getting way more control. Mercury seems quite close to the Streamlit&#x2F;Databricks side, which in our experience is right for many pydata dashboarding teams yet most tools don&#x27;t really nail. It may even be on the path to one-upping streamlit on the simplicity side. Good job &amp; will be tracking!
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anigbrowl将近 3 年前
This is great! I have a lot of tools built in notebooks that I&#x27;d like to be able to share with non-technical collaborators, and have been procrastinating building a UI in Flask or Django as I&#x27;m really not interested in front-end stuff. This is a fun and simple way to deploy that won&#x27;t be a distraction from collection and analysis I actually enjoy. I look forward to using it!
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maliker将近 3 年前
When I need to expose jupyter notebooks to non-technical users I put them on colab.research.google.com. It&#x27;s a free, interactive, hosted Jupyter environment. It&#x27;s not as slick as a dashboard, but it just requires an upload instead of maintaining a server.
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sireat将近 3 年前
Mercury looks rather neat for quick dashboards.<p>For dynamic data I build my dashboards with Flask and Plotly. However that is certainly a more involved process to migrate Jupyter notebook Python plots to JS plots.<p>For static data one can just export html(with embedded JS) from Jupyter notebook that uses plotly.<p>The main difference with quick solutions is the level of customizability.
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blagie将近 3 年前
I looked over the web site. A few questions:<p>- Why won&#x27;t the OSS version provide features like history of execution? It seems like those are pretty basic to adoption. I&#x27;m working on an open source project, and it&#x27;d be a nice tool to potentially integrate. The commercial license is of zero interest since it&#x27;s, well, all open-source.<p>- Why don&#x27;t you sell the OSS version as well (e.g. for people who want to support you, or who want support)?<p>- Do you provide consulting services? Are they in the $50&#x2F;hour range (just extrapolating from $200&#x2F;year for up to 4 hours support)<p>- Why Django? I like Django, but it seems like using the same tech stack as Jupyter would make for simpler integration, administration, and lower TCO (plus the universe is going async)<p>- For presentation, the speed is an issue. Regeneration takes a while (I&#x27;m playing with the demo on Hugging Face). It&#x27;s not quite adequate for interactive presentation. I do really like the concept of making presentations in Jupyter.<p>- And on that topic, the biggest gap I have is with interactive front-ends. I&#x27;d like to be able to somehow connect notebooks (both for dashboards and otherwise) for data munging to data visualization frameworks like D3. Jupyter is nice. Observable would be nice if it were open-source. There&#x27;s a mile-high wall between the two.
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crisbal_将近 3 年前
How does this compare to Voila from the Jupyter team? ( <a href="https:&#x2F;&#x2F;voila.readthedocs.io&#x2F;en&#x2F;stable&#x2F;index.html" rel="nofollow">https:&#x2F;&#x2F;voila.readthedocs.io&#x2F;en&#x2F;stable&#x2F;index.html</a> )
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westurner将近 3 年前
Surprised I hadn&#x27;t heard of mplfinance. Similar code for econometric charts with bands and an annotation table with dated events would be useful and probably already exists somewhere. Maybe Predictive Forecasting libraries for time series already have something that could be factored out into a maintained package for such common charts? E.g. seaborn has real nice confidence intervals with matplotlib, too; though the matplotlib native color schemes are colorblind-friendly: &quot;Perceptually Uniform Sequential colormaps&quot; <a href="https:&#x2F;&#x2F;matplotlib.org&#x2F;3.5.0&#x2F;tutorials&#x2F;colors&#x2F;colormaps.html" rel="nofollow">https:&#x2F;&#x2F;matplotlib.org&#x2F;3.5.0&#x2F;tutorials&#x2F;colors&#x2F;colormaps.html</a><p>awesome-jupyter &gt; Rendering&#x2F;Publishing&#x2F;Conversion <a href="https:&#x2F;&#x2F;github.com&#x2F;markusschanta&#x2F;awesome-jupyter#renderingpublishingconversion" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;markusschanta&#x2F;awesome-jupyter#renderingpu...</a> :<p>&gt; <i>ContainDS Dashboards - JupyterHub extension to host authenticated scripts or notebooks in any framework (Voilà, Streamlit, Plotly Dash etc)</i><p>IIRC, ContainDS and Voila spawn per-dashboard and&#x2F;or per-user Jupyter kernels with JupyterHub Spawners and Authenticators; like Binderhub ( <a href="https:&#x2F;&#x2F;mybinder.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;mybinder.org&#x2F;</a> ) but with required login and without repo2docker?<p>Streamlit lists Bokeh, Jupyter Voila, Panel, and Plotly Dash as Alternative dashboard approaches: <a href="https:&#x2F;&#x2F;github.com&#x2F;MarcSkovMadsen&#x2F;awesome-streamlit#alternative" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;MarcSkovMadsen&#x2F;awesome-streamlit#alternat...</a><p>Says here that mljar&#x2F;mercury is dual-licensed AGPL: <a href="https:&#x2F;&#x2F;github.com&#x2F;mljar&#x2F;mercury" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;mljar&#x2F;mercury</a>
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kaa2102将近 3 年前
Mercury is a great find for me as it solves UI&#x2F;UX design &amp; usability concerns for my Python automation projects for non-techninal users.
criddell将近 3 年前
Ever since I read about the Panic status board project [1] I&#x27;ve been looking for similar projects. This one looks pretty cool.<p>[1]: <a href="https:&#x2F;&#x2F;panic.com&#x2F;blog&#x2F;the-panic-status-board&#x2F;" rel="nofollow">https:&#x2F;&#x2F;panic.com&#x2F;blog&#x2F;the-panic-status-board&#x2F;</a>
oneoff786将近 3 年前
My initial reaction is that there’s a ton of lag on the initial gif. Makes me think this is going to be a cumbersome thing to work with. Is it representative of a typical task, whatever that means?
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curiousgal将近 3 年前
Nothing beats R&#x27;s Shiny for making dashboards from my experience.
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urthor将近 3 年前
YMMV, has any technologist found a dashboard useful?<p>I&#x27;ve had a very bad history with dashboards. All I&#x27;ve seen get ordered up by nontechnical leadership, not looked at, and involved endless fiddling with painful corporate applications.<p>The non-technical stakeholders I&#x27;ve had a good relationship with, I vend a SQL script&#x2F;Jupyter Notebook and educate. They&#x27;re happy to up-skill.<p>I&#x27;ve only had dashboards requested by users with a dysfunctional relationship with engineering, in companies where the data is irrelevant.<p>In environments where data <i>matters</i>, fast moving consumer goods, web, etc, stakeholders speak SQL&#x2F;Jupyter. I&#x27;ve seen remarkably non-technological people learn SQL and query read replicas because they <i>need</i> sales aggregates.<p>In environments where data doesn&#x27;t matter, dashboards are requested as a corporate power play.<p>A director who doesn&#x27;t care about your project asks for a dashboard to assert their authority, and remind you your budget can be cancelled.
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