1. go get github.com/jadekler/git-go-logictree
2. go run $GOPATH/src/github.com/jadekler/git-go-logictree/main.go
3. Navigate to localhost:8080 in your browser

To test locally, simply run go test -v ./... from the project root.

Note: Useful testing command: printf "$(go test $GOPATH/src/github.com/jadekler/git-go-logictree/app/home | sed 's/::/\\n/g')" && echo;

This program is a pretty simple lexical analyzer that accepts human-readable conditions, such as 'age greater than 5', and translates it to mysql-queryable language. The basic case is fairly simple, but the more advanced cases, such as '(age is greater than 5 or number of pets is less than 2) and age is less than 9', require a bit more work. The intermediary step between human-readable conditions and mysql conditions is implemented as a tree. Additionally, the human-readable conditions are stored in mysql as a left-right hierarchy tree (which represents nested sets). See more detail on the tree and nested sets below.

The setup for this app is: human-readable on the front, golang tree in the middle, mysql nested sets in the back. Here is a basic overview of how the stages interact:

Below are the explanation for each stage.

The front end is represented as a set of parenthesis, equality conditions, and logical conditions. Combined, they look like this:

Each block is draggable - by clicking the 'Save Re-ordering' button on the page, the re-ordered conditions are saved in mysql. The conditions will also be converted to a mysql query and executed against a dummy users table, with results displayed at the bottom of the page.

We use a tree as an intermediary between the human-readable conditions on the front and interactions with mysql, including saving the conditions, executing the conditions, and converting the conditions (via tree) into human-readable conditions for the front. The tree is a simple n-child tree that is generally traversed post-order. The branches are logical conditions, and the leaves are equality conditions. For instance, (A OR B) would be represented as OR being the branch and A and B being two children of OR, and so on. See below a larger example (taken from the app):

The general idea behind storing a tree in mysql as nested sets is well explained here. The basic idea, however, is that each condition is a set, and each child (in the aforementioned tree) is a set within the set that is its parent condition. Once we have so ordered our sets, we can assign lefts and rights to them as below:

In mysql, this becomes:

condition, left, right
----------------------
AND, 1, 24
OR, 2, 17
AND, 3, 14
age = 4, 4, 5
age = 5, 6, 7
age = 6, 8, 9
age = 7, 10, 11
age = 8, 12, 13
age = 1, 15, 16
OR, 18, 23
age = 2, 19, 20
age = 3, 21, 22

Please shoot any questions or feedback over to jadekler@gmail.com.