Package managers visualization

Related tags

Data Visualizationpm
Overview

Software Galaxies

This repository combines visualizations of major software package managers.

All visualizations are available here: http://anvaka.github.io/pm/#/

Please read operating manual - it is short and describes basic navigation principles.

Repository was create for my talk at CascadiaJS 2015

After conference update - video - slides

Friends, you are awesome! I can't express how much I appreciate all your kind words and warm feedback. It really means a world for me. Thank you!

Individual Visualizations

Each graph is indexed individually, and data is pushed to gh-pages branch of galactic-data.

Bower


indexer | demo

PHP Composer


indexer | demo

Ruby gems


indexer | demo

npm


indexer | demo

Go


indexer | demo

R language


indexer | demo

Debian


indexer | demo

Arch Linux


indexer | demo

Arch Linux + AUR


indexer | demo

NuGet


indexer | demo

Homebrew


indexer | demo

PyPI


indexer | demo

Fedora


indexer | demo

Rust Crates


indexer | demo

Elm


indexer | demo

local development

git clone https://github.com/anvaka/pm
cd pm
npm i
npm start

This will start local development sever with auto-rebuild.

Your own graphs

This section has detailed instructions about how to use the tool with your own graphs. Before you read any further, if your graph is smaller than 10k nodes, consider using ngraph.pixel or VivaGraph both should be able to provide interactive layout.

If you have an interesting graph but don't have JavaScript experience, please feel free to reach out to me and I'll try to make visualization for you (my email is [email protected]).

Otherwise, if you want to hack on your own, please keep reading.

Graph

First, you will need a graph in ngraph.graph format. The ngraph.graph has detailed documentation about how to create graph, but it also has several loaders from popular graph formats (e.g. dot, gexf)

Layout

Now that you have a graph we need to compute the layout.

If your graph is smaller than 200k nodes, consider using ngraph.offline.layout. This module was created exactly for the purpose of the pm project, it is well documented, and should be easy to get started with. You can also read layout.js of all[gems|go|bower] packages to see more examples.

If your graph is much larger than 200k nodes, then consider using ngraph.native - this module is harder to work with (as it requires C++ knowledge), but it is much faster.

The secret GitHub visualization is using ngraph.native.

Data format

Once layout is computed, we are ready to visualize. Just save the graph using ngraph.tobinary and store it along with latest positions file (produced by layout) into a folder.

The folder structure should look like this:

.
└── my-pm-data-server
    └── my-graph
        ├── manifest.json
        └── version-1
            ├── labels.json         /* this file is produced by ngraph.tobinary */
            ├── links.bin           /* this file is produced by ngraph.tobinary */
            └── positions.bin       /* this file is produced by ngraph.native   */

The file manifest.json describes what version of the graph are available and has the following content:

{
  "all": ["version-1"],
  "last": "version-1"
}

Inside my-pm-data-server we launch a web server. I personally prefer http-server. Once it is installed globally (npm i http-server -g), you can launch it like this:

http-server --cors -p 9090

This will start a local data server at http://127.0.0.1:9090/

Update the config.js in this repository to point to your data server, and your graph should be accessible at

http://127.0.0.1:8081/#/galaxy/my-graph

Note

The galactic-data follows the same data structure as described above. Use it for the reference if you need an example

The secret visualization

The last shown visualization was secret GitHub followers visualization. It shows all GitHub users who has more than two followers.

The visualization has more than 1,100,000 nodes, and renders at 60 fps when flying around. The FPS drops when you hover-over nodes to 20-30, This is because we are doing hit-testing, to find what's under cursor.

With this many nodes, it runs well in the browser. Unfortunately it requires more than 1GB of RAM. Which may or may not crash your phone browser - sorry about this.

With all warnings said, here are the links:

Feedback

Please do not hesitate to provide your feedback or bug fixes. Even if it is something small like fixing a typo - I'd be glad to hear from you!

Owner
Andrei Kashcha
I love graphs
Andrei Kashcha
Getting started with Python, Dash and Plot.ly for the Data Dashboards team

data_dashboards Getting started with Python, Dash and Plot.ly for the Data Dashboards team Getting started MacOS users: # Install the pyenv version ma

Department for Levelling Up, Housing and Communities 1 Nov 08, 2021
Movies-chart - A CLI app gets the top 250 movies of all time from imdb.com and the top 100 movies from rottentomatoes.com

movies-chart This CLI app gets the top 250 movies of all time from imdb.com and

3 Feb 17, 2022
Eulera Dashboard is an easy and intuitive way to get a quick feel of what’s happening on the world’s market.

an easy and intuitive way to get a quick feel of what’s happening on the world’s market ! Eulera dashboard is a tool allows you to monitor historical

Salah Eddine LABIAD 4 Nov 25, 2022
3D-Lorenz-Attractor-simulation-with-python

3D-Lorenz-Attractor-simulation-with-python Animação 3D da trajetória do Atrator de Lorenz, implementada em Python usando o método de Runge-Kutta de 4ª

Hevenicio Silva 17 Dec 08, 2022
Smarthome Dashboard with Grafana & InfluxDB

Smarthome Dashboard with Grafana & InfluxDB This is a complete overhaul of my Raspberry Dashboard done with Flask. I switched from sqlite to InfluxDB

6 Oct 20, 2022
Yata is a fast, simple and easy Data Visulaization tool, running on python dash

Yata is a fast, simple and easy Data Visulaization tool, running on python dash. The main goal of Yata is to provide a easy way for persons with little programming knowledge to visualize their data e

Cybercreek 3 Jun 28, 2021
Main repository for Vispy

VisPy: interactive scientific visualization in Python Main website: http://vispy.org VisPy is a high-performance interactive 2D/3D data visualization

vispy 3k Jan 03, 2023
This is a place where I'm playing around with pandas to analyze data in a csv/excel file.

pandas-csv-excel-analysis This is a place where I'm playing around with pandas to analyze data in a csv/excel file. 0-start A very simple cheat sheet

Chuqin 3 Oct 05, 2022
Some examples with MatPlotLib library in Python

MatPlotLib Example Some examples with MatPlotLib library in Python Point: Run files only in project's directory About me Full name: Matin Ardestani Ag

Matin Ardestani 4 Mar 29, 2022
A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews

hvPlot A high-level plotting API for the PyData ecosystem built on HoloViews. Build Status Coverage Latest dev release Latest release Docs What is it?

HoloViz 697 Jan 06, 2023
GDSHelpers is an open-source package for automatized pattern generation for nano-structuring.

GDSHelpers GDSHelpers in an open-source package for automatized pattern generation for nano-structuring. It allows exporting the pattern in the GDSII-

Helge Gehring 76 Dec 16, 2022
This tool is designed to help administrators get an overview of their Active Directory structure.

This tool is designed to help administrators get an overview of their Active Directory structure. In the group view you can see all elements of an AD (OU, USER, GROUPS, COMPUTERS etc.). In the user v

deexno 2 Oct 30, 2022
ecoglib: visualization and statistics for high density microecog signals

ecoglib: visualization and statistics for high density microecog signals This library contains high-level analysis tools for "topos" and "chronos" asp

1 Nov 17, 2021
The Timescale NFT Starter Kit is a step-by-step guide to get up and running with collecting, storing, analyzing and visualizing NFT data from OpenSea, using PostgreSQL and TimescaleDB.

Timescale NFT Starter Kit The Timescale NFT Starter Kit is a step-by-step guide to get up and running with collecting, storing, analyzing and visualiz

Timescale 102 Dec 24, 2022
又一个云探针

ServerStatus-Murasame 感谢ServerStatus-Hotaru,又一个云探针诞生了(大雾 本项目在ServerStatus-Hotaru的基础上使用fastapi重构了服务端,部分修改了客户端与前端 项目还在非常原始的阶段,可能存在严重的问题 演示站:https://stat

6 Oct 19, 2021
A site that displays up to date COVID-19 stats, powered by fastpages.

https://covid19dashboards.com This project was built with fastpages Background This project showcases how you can use fastpages to create a static das

GitHub 1.6k Jan 07, 2023
JSNAPY example: Validate NAT policies

JSNAPY example: Validate NAT policies Overview This example will show how to use JSNAPy to make sure the expected NAT policy matches are taking place.

Calvin Remsburg 1 Jan 07, 2022
matplotlib: plotting with Python

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Check out our home page for more inform

Matplotlib Developers 16.7k Jan 08, 2023
A python visualization of the A* path finding algorithm

A python visualization of the A* path finding algorithm. It allows you to pick your start, end location and make obstacles and then view the process of finding the shortest path. You can also choose

Kimeon 4 Aug 02, 2022
Smoking Simulation is an app to simulate the spreading of smokers and non-smokers, their interactions and population during certain amount of time.

Smoking Simulation is an app to simulate the spreading of smokers and non-smokers, their interactions and population during certain

Bohdan Ruban 5 Nov 08, 2022