How to Visualize a Social Network in Python with a Graph Database: Flask + Docker + D3.js

• d3

  277 107,634 8.0 Shell

  Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

  

I won't go into much detail about how to use D3.js so if you want to find out more I encourage you to visit their website. In short, we fetch all the nodes and edges from the database and add them to an SVG element. The visual representation of the graph is made by simulating how physical forces act on particles (charge and gravity). You can drag and drop the nodes, hover over them to see the value of their name property, zoom in and out of the graph and move the SVG graphic.

• microblog

  220 4,425 2.3 Python

  The microblogging application developed in my Flask Mega-Tutorial series. This version maps to the 2024 Edition of the tutorial.

In the project root directory create a folder called static with one subfolder called js and another called css. The js folder will contain all of the needed local JavaScript files while the css folder will contain all the CSS stylesheets. In the js folder create a file called index.js and in the css folder one called style.css. Just leave them empty for now. If you want to find out more about web development with Flask I suggest you try out this tutorial. Your current project structure should like this:

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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