Edit, preview and share Mermaid charts/diagrams. Edit and preview flowcharts, sequence diagrams, gantt diagrams in real time. Save the result as a .svg file. Get a link to a viewer of the diagram so that you can share it with others. Get a link to edit the diagram so that someone else can tweak it and send a new link back
Hyperdiv is a framework for rapidly developing reactive browser UI apps in Python, with built-in components, terse immediate-mode syntax, and minimal tool boilerplate. Hyperdiv includes the Shoelace component system, markdown support via Mistune, charts via Chart.js, support for reading/writing browser local storage, and forms whose validation logic is implemented in Python.
After playing with some of the demo apps, this looks like a pretty cool library.
Legend has it that once upon a time a networking instructor named Bob taught a class of students a method of subnetting any address using a special chart. This was known as the Bob Maneuver. These students, being the smart type that networking students usually are, added a row to the top of the chart and the Enhanced Bob Maneuver was born. The chart and instructions on how to use it follow. With practice, you should be able to subnet any address and come up with an IP plan in under a minute. After all, it's just math!
A JavaScript based diagramming and charting tool that renders Markdown-inspired text definitions to create and modify diagrams dynamically. Live editor: Load the page in your browser and start keying in Markdown; you'll see the diagram take shape. Can pull data from a large number of different applications.
Github: https://github.com/mermaid-js/mermaid
Live demo: https://mermaid.live/
Smashing, the spiritual successor to Dashing, is a Sinatra based framework that lets you build excellent dashboards. It looks especially great on TVs. Use premade widgets, or fully create your own with scss, html, and coffeescript. Has a REST API to push data to the dashboard. Drag and drop interface for building a dashboard.
Install the gem. Run it to create a new dashboard ("project"). Run bundle. Start the server for the project.
Bloxs is a simple python package that helps you display information in an attractive way (formed in blocks). Perfect for building dashboards, reports and apps in the notebook.
It works with Jupyter Notebook, Google Colab, Deepnote, Kaggle Notebook, and Mercury.
A sparkline generator implemented as a shell script.
Just run spark and pass it a list of numbers (comma-delimited, spaces, whatever you'd like) and it generates a text-mode bar graph, where the heights are relative to one another but reflect the numbers given. It's designed to be used in conjunction with other scripts that can output in that format.
Github: https://github.com/holman/spark
Dynamic web based reports/dashboards in Python. Write a little bit of code to define the dashboard and populate the layout, and treat the rest like Python. Seems pretty straightforward. Has a built-in DSL to make defining some parts of a dashboard easier to do. Also has a CLI tool that you can use to interactively build dashboards without having to stop and start the server again and again. Even has a REST API that can be used to update the page's widgets in the background, so you can push instead of pull.
A curated list of amazingly awesome dashboards/visualization resources.
H2O Wave is a software stack for building beautiful, low-latency, realtime, browser-based applications and dashboards entirely in Python without using HTML, Javascript, or CSS. H2O Wave excels at capturing information from multiple sources and broadcasting them live over the web, letting you build and deploy realtime analytics with dramatically less effort.
The server is written in Go, which is weird, why are they calling it a Python app?
A data visualization framework written in CSS. Uses the semantic HTML5 tags to identify data to process, the data goes inside the HTML markup in the form of tables. No Javascript is needed to pull data out of APIs for processing (unless you want to roll that way, I guess). The core CSS file can be downloaded and put to use more or less immediately.
Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create beautiful charts. It features a chart builder, editable dashboards, embedable charts, query & requests editor, and team capabilities. Can pull data from MySQL, Postgres, MongoDB, and any API that returns JSON documents. Interactive graph and chart builder.
Written in node.js. Requires MySQL on the back-end.
If you use the service (https://chartbrew.com/) there's a free tier.
The Image-Charts API returns a chart image in response to a URL GET or POST request. The API can generate many kinds of charts, from pie or line charts to bar charts and radars. All the information about the chart that you want, such as chart data, size, colors, and labels, are part of the URL.
To make the simplest chart possible, all your URL needs to specify is the chart type, data, and size. You can type this URL directly in your browser, or point to it with an <img> tag in your web page.
A Python framework for doing graphical data analysis without needing to know Javascript. Visualizations are updated in realtime as they are interacted with. You'll have to write some code to set it up, it would appear mostly to get the data into the application to begin with.
Docs: https://dash.plotly.com/
Here's a tutorial for how to use it: https://mymasterdesigner.com/2021/12/13/visualization-dashboards-with-python-dash/
Gallery of Dash dashboards: https://dash.gallery/Portal/
A CSS file that lets you develop various types of plots and graphs without having to resort to Javascript.
An application which generates 2D or 3D plots of numerical data in the form of dots, waves, fields, or other visual modes. Requires libSDL.