Command datagen

Generate datastructures for your types.

With Go installed

$ go get -u github.com/aybabtme/datagen/...

On linux

wget -qO- https://github.com/aybabtme/datagen/releases/download/0.1.5/datagen_Linux_x86_64.tar.gz | tar xvz

On OS X

brew tap aybabtme/homebrew-tap
brew install datagen

Builds upon well tested implementations of datastructures to generate customized implementations for your types. Alike to what you would get with generics, but with code generation instead.

You can use it manually or with go generate.

For more information, invoke the command with the -h flag.

Alike to go generate and other code gen tools, this tool is meant for package authors who wish to generate code. It should not be used as a build step for your users.

Supports

• Heap/Priority queues.
• Sorted maps.
• Sorted sets.
• Queues.

Why

Usability

Having datastructures that are specifically suited for your types is much easier to code against than those relying on interfaces.

For instance, when you need a heap/priority queue:

// this
func main() {
    h := NewIntHeap()
    for i := 20; i > 0; i-- {
        h.Push(i)
    }
}

// vs this (container/heap)
type IntHeap []int

func (h IntHeap) Len() int           { return len(h) }
func (h IntHeap) Less(i, j int) bool { return h[i] < h[j] }
func (h IntHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }

func (h *IntHeap) Push(x interface{}) {
    *h = append(*h, x.(int))
}

func (h *IntHeap) Pop() interface{} {
    old := *h
    n := len(old)
    x := old[n-1]
    *h = old[0 : n-1]
    return x
}

func main() {
    h := new(IntHeap)
    for i := 20; i > 0; i-- {
        h.Push(i)
    }
}

Or if you need a sorted map:

// this
func main() {
    tree := NewSortedStringToStringMap()
    tree.Put("hello", "world")
    k, v, _ := tree.DeleteMin()
    log.Printf("%s, %s", k, v)
}

// vs this (GoLLRB)
type String struct {
    key string
    val string
}

func (s String) Less(than llrb.Item) bool {
    return string(s.key) < string(than.(String).key)
}

func main() {
    tree := llrb.New()
    tree.ReplaceOrInsert(String{key: "hello", val:"world"})
    kv := tree.DeleteMin().(String)
    log.Printf("%s, %s", kv.key, kv.val)
}

Performance

In most case, a code generated datastructure will perform better than one that uses interfaces.

SortedMap

                | Operations  | GoLLRB ns/op | datagen ns/op | delta (smaller is better)

--------------------|-------------|--------------|---------------|--------------------------- []byte:string | Delete | 3119 | 1487 | -52.32% float64: string | Delete | 2684 | 1797 | -33.05% int:string | Delete | 2715 | 1236 | -54.48% string string | Delete | 2830 | 1550 | -45.23% []byte:string | DeleteMin | 1002 | 1026 | +2.40% float64: string | DeleteMin | 1034 | 1256 | +21.47% int:string | DeleteMin | 1045 | 1300 | +24.40% string string | DeleteMin | 977 | 1231 | +26.00% []byte:string | Insert | 3606 | 1228 | -65.95% float64: string | Insert | 2722 | 1006 | -63.04% int:string | Insert | 2736 | 1039 | -62.02% string string | Insert | 3256 | 1121 | -65.57%

SortedSet

       | Operations   | GoLLRB ns/op | datagen ns/op | delta (smaller is better)

-----------|--------------|--------------|---------------|--------------------------- []byte | Delete | 2934 | 1620 | -44.79% float64 | Delete | 2712 | 1599 | -41.04% int | Delete | 2839 | 1003 | -64.67% string | Delete | 2811 | 1271 | -54.78% []byte | DeleteMin | 999 | 1208 | +20.92% float64 | DeleteMin | 1049 | 1048 | -0.10% int | DeleteMin | 1000 | 1013 | +1.30% string | DeleteMin | 999 | 1014 | +1.50% []byte | Insert | 3267 | 1214 | -62.84% float64 | Insert | 2705 | 899 | -66.77% int | Insert | 2720 | 869 | -68.05% string | Insert | 3152 | 1040 | -67.01%

Heap

         | Operations | stdlib ns/op   |  datagen ns/op   | delta  (smaller is better)

-------------|------------|----------------|------------------|--------------------------- []byte | Pop | 1383 | 1323 | -4.34% float64 | Pop | 499 | 548 | +9.82% int | Pop | 507 | 416 | -17.95% string | Pop | 1081 | 1014 | -6.20% []byte | Push | 456 | 361 | -20.83% float64 | Push | 71.2 | 334 | +369.10% int | Push | 70.2 | 255 | +263.25% string | Push | 240 | 231 | -3.75% []byte | various | 9089651 | 8669574 | -4.62% float64 | various | 3697083 | 5099185 | +37.92% int | various | 3686002 | 3685407 | -0.02% string | various | 7612799 | 7007515 | -7.95%

Queue

         | Operations | stdlib ns/op   |  datagen ns/op   | delta  (smaller is better)

-------------|------------|----------------|------------------|--------------------------- []byte | Pop | 72.1 | 60.3 | -16.37% float64 | Pop | 60.1 | 19.5 | -67.55% int | Pop | 79.2 | 20.7 | -73.86% string | Pop | 79.6 | 51.3 | -35.55% []byte | Push | 326 | 175 | -46.32% float64 | Push | 141 | 18.9 | -86.60% int | Push | 218 | 21.7 | -90.05% string | Push | 201 | 56.8 | -71.74% []byte | Serial | 395 | 229 | -42.03% float64 | Serial | 197 | 37.5 | -80.96% int | Serial | 268 | 37.0 | -86.19% string | Serial | 215 | 165 | -23.26% []byte | TickTock | 217 | 38.9 | -82.07% float64 | TickTock | 128 | 32.3 | -74.77% int | TickTock | 152 | 32.1 | -78.88% string | TickTock | 165 | 36.4 | -77.94%

Subpackages

The following packages can be imported and used without code gen. However, their location in the project is subject to change.

• map/redblackbst implements a red black balanced search tree, based on the details provided in Algorithms 4th edition, by Robert Sedgewick and Kevin Wayne. A red black bst is useful as a map that keeps its items in sorted order, while preserving efficient inserts, lookups and deletions.
• set/redblackbst is similar to the map implementation, but stores no data about values.
• heap is a heap implementation inspired from Algorithms 4th edition and the container/heap implementation.
• queue is a queue implementation adapted from github.com/eapachae/queue.

Contributions

See TODO file.

• Code should be gofmt'd.
• Code should have had go vet ran onto it.
• Code should have had golint ran onto it.

If you're not familiar with forks and contributions in Go, the flow differs a bit from other languages.

While you can fork the project, you can't work under that fork's path in your GOPATH. Instead, do the following.

• go get github.com/aybabtme/datagen
• cd $GOPATH/src/github.com/aybabtme/datagen
• Fork this project.
• git remote add my_fork [email protected]:my_username/datagen.git

If this seems odd to you, there's litterature elsewhere about why you need to do this.

Credits

The red black tree and heap implementations are heavily inspired from the Java implementations of Robert Sedgewick.

The heap implementation was inspired, and the comments/tests adapted from container/heap.

The queue implementation was adapted from github.com/eapache/queue, a package by Evan Huus.

Some tests for the red black tree were extracted from GoLLRB, a similar implementation by Petar Maymounkov.