The basic idea of this exercise is to learn to create images using Go. To do this, we will explore a couple different packages as well as a few different image formats.

First up we are going to use the image package in the standard library to create pretty much any image you want. I will be creating some bar charts using a data slice of integers between 0 and 100, like the one below:

data := []int{10, 33, 73, 64}

Go also provides us with an image/draw package that can be used for quite a bit. Try using it to recreated some of the images you made in the past exercise step.

SVGs have some pretty awesome advantages over PNGs. For starters, we can stop thinking about pixels and start working with things like rectangles, lines, text, etc. We can also create images that scale infinitely without losing quality.

Anthony Starks created an awesome library for building SVGs in Go called svgo. Try using it to recreate some of the images you created in the past two steps, but this time try improving them. Maybe add some font labels or something else that was a little trickier to do with the image package.

A PNG of the image we will be creating can be found in the demo.svg file in this repo and is shown below in PNG format.

Use an svgdef file to learn about svgo

They say a picture is worth a thousand words; in this case I suspect it is worth more. Along with great docs, svgo has a single image that show you what types of shapes and lines can be created with each function call. Rather than having to experiment, we can just scan the image and quickly figure out which fits our needs. You can find that image in the repo, or here: https://raw.githubusercontent.com/ajstarks/svgo/master/svgdef.png

Use a tool like rsvg-convert to convert an SVG into a PNG

You can use a tool like rsvg-covnert to convert your SVG into a PNG if you need a PNG as the final result.

SVGo example refactor

@ajstarks provided an example refactor with SVGo here: https://gist.github.com/ajstarks/8b1c24545264c20625073faa5e079a59 The refactor shows how you can adjust the bar width and separation. Also, added variables to allow you to adjust aspects of the plot, and improve readability. (Thanks Anthony!)