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.
The server is written in Go, which is weird, why are they calling it a Python app?
CygnusRFI is an easy-to-use open-source Radio Frequency Interference (RFI) analysis tool, based on Python and GNU Radio Companion (GRC) that is conveniently applicable to any ground station/radio telescope working with a GRC-supported software-defined radio (SDR). In addition to data acquisition, CygnusRFI also carries out automated analysis of the recorded data, producing a series of averaged spectra covering a wide range of frequencies of interest. CygnusRFI is built for ground station operators, radio astronomers, amateur radio operators and anyone who wishes to get an idea of how "radio-quiet" their environment is, using inexpensive instruments like SDRs.
The CLI tool is used to set up scanning runs. Data is graphed as output.
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.
Pyrgg is an easy-to-use synthetic random graph generator written in Python which supports various graph file formats including DIMACS .gr files. Pyrgg has the ability to generate graphs of different sizes and is designed to provide input files for broad range of graph-based research applications, including but not limited to testing, benchmarking and performance-analysis of graph processing frameworks. Pyrgg target audiences are computer scientists who study graph algorithms and graph processing frameworks.
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.
Graphs for dump1090 (based on dump1090-tools by mutability). Message rate, aircraft seen, tracks seen, range, signal strength... front end to rrdtool and collectd.
Analyze spectrograms created by rtl_power.
Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing.
Comes with Python embedded to interact with the data.
Versions for multiple OSes are available. Might be worth grabbing the .appimage to save time.l
WOPR is a simple markup language for creating rich terminal reports, presentations and infographics.
Has an HTTP interface to pump data into as well as command line pipes.
Someone fed ROM dumps from a couple of Atari games into distellamap and generated maps of function calls, with sprite dumps. Amazing, how simple games were back then...
An application which generates 2D or 3D plots of numerical data in the form of dots, waves, fields, or other visual modes. Requires libSDL.
An opensource tool for the visualization of extremely large datasets, like twitter maps or email databases.
Python module for studying networks of data. Nodes can be anything, edges can be arbitrary kinds of data.
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