lazyUnwrap

README.md

@@ -1,30 +1,43 @@
-# Laziness in Elm
+# DEPRECATED
 
-This package provides the basic primitives for working with laziness in Elm.
+It turned out that many folks were unclear on the difference between laziness
+and delayed computation:
 
+  - **Delayed Computation** is when you have a value like `answer : () -> Int`
+  that you can evaluate later. You only do all the computation when you say
+  `answer ()` at some later time. If you call `answer ()` four times, you do
+  the computation four times.
 
-# Motivating Example
+  - **Laziness** is an optimization on top of delayed computation. It is just
+  like having `answer : () -> Int` but when this function is evaluated for the
+  first time, the results are saved. So if you call `answer ()` four times, you
+  do the computation *one* time.
 
-Maybe you have 100 different graphs you want to show at various times, each
-requiring a decent amount of computation. Here are a couple ways to handle
-this:
+In all the cases in Elm that I have heard of that use this library, folks only
+really needed *delayed computation* and ended up with simpler code when they
+went that way.
 
- 1. Compute everything up front. This will introduce a delay on startup, but
-    it should be quite fast after that. Depending on how much memory is needed
-    to store each graph, you may be paying a lot there as well.
+So in the end, there are two major reasons to stop supporting laziness:
 
- 2. Compute each graph whenever you need it. This minimizes startup cost and
-    uses a minimal amount of memory, but when you are flipping between two
-    graphs you may be running the same computations again and again.
+  1. It is overkill for all the scenarios I have seen in Elm.
+  2. It allows the creation of cyclic data, significantly complicating GC.
 
- 3. Compute each graph whenever you need it and save the result. Again, this
-    makes startup as fast as possible fast, but since we save the result,
-    flipping between graphs becomes much quicker. As we look at more graphs
-    we will need to use more and more memory though.
+With laziness you can create a list like `ones = 1 :: ones` that refers to
+itself. Without laziness, there is no way to create cyclic data in Elm. That
+means we can use a naive reference counting approach to collect garbage if we
+wanted. So although people have dreamed up data structures that use laziness
+in interesting ways, I do not feel these cases are compelling enough to commit
+to the collateral complications.
 
-All of these strategies are useful in general, but the details of your
-particular problem will mean that one of these ways provides the best
-experience. This library makes it super easy to use strategy #3.
+<br>
+
+* * *
+
+What follows is some of content from the old README.
+
+* * *
+
+<br>
 
 
 # Pitfalls

elm-package.json

@@ -1,7 +1,7 @@
 {
-    "version": "1.1.0",
+    "version": "2.0.0",
     "summary": "Basic primitives for working with laziness",
-    "repository": "http://github.com/maxsnew/lazy.git",
+    "repository": "http://github.com/elm-lang/lazy.git",
     "license": "BSD3",
     "source-directories": [
         "src"
@@ -11,7 +11,7 @@
     ],
     "native-modules": true,
     "dependencies": {
-        "elm-lang/core": "2.0.0 <= v < 4.0.0"
+        "elm-lang/core": "5.0.0 <= v < 6.0.0"
     },
-    "elm-version": "0.15.0 <= v < 0.17.0"
+    "elm-version": "0.18.0 <= v < 0.19.0"
 }

src/Lazy.elm

@@ -1,9 +1,9 @@
-module Lazy
-    ( Lazy, force, lazy
+module Lazy exposing
+    ( Lazy
+    , force, lazy
     , map, map2, map3, map4, map5
     , apply, andThen
     )
-    where
 
 {-| This library lets you delay a computation until later.
 
@@ -20,8 +20,14 @@ module Lazy
 import Native.Lazy
 
 
+
+-- PRIMITIVES
+
+
 {-| A wrapper around a value that will be lazily evaluated. -}
-type Lazy a = Lazy (() -> a)
+type Lazy a =
+  Lazy (() -> a)
+
 
 {-| Delay the evaluation of a value until later. For example, maybe we will
 need to generate a very long list and find its sum, but we do not want to do
@@ -59,6 +65,10 @@ force (Lazy thunk) =
   thunk ()
 
 
+
+-- COMPOSING LAZINESS
+
+
 {-| Lazily apply a function to a lazy value.
 
     lazySum : Lazy Int
@@ -128,23 +138,27 @@ pattern match on a value, for example, when appending lazy lists:
 
     cons : a -> Lazy (List a) -> Lazy (List a)
     cons first rest =
-        Lazy.map (Node first) rest
+      Lazy.map (Node first) rest
 
     append : Lazy (List a) -> Lazy (List a) -> Lazy (List a)
     append lazyList1 lazyList2 =
+      let
+        appendHelp list1 =
+          case list1 of
+            Empty ->
+              lazyList2
+
+            Node first rest ->
+              cons first (append rest list2))
+      in
         lazyList1
-          `andThen` \list1 ->
-              case list1 of
-                Empty ->
-                  lazyList2
+          |> Lazy.andThen appendHelp
 
-                Node first rest ->
-                  cons first (append rest list2))
 
 By using `andThen` we ensure that neither `lazyList1` or `lazyList2` are forced
 before they are needed. So as written, the `append` function delays the pattern
 matching until later.
 -}
-andThen : Lazy a -> (a -> Lazy b) -> Lazy b
-andThen a callback =
+andThen : (a -> Lazy b) -> Lazy a -> Lazy b
+andThen callback a =
   lazy (\() -> force (callback (force a)))

src/Native/Lazy.js

@@ -1,25 +1,20 @@
-Elm.Native.Lazy = {};
-Elm.Native.Lazy.make = function(localRuntime) {
+var _elm_lang$lazy$Native_Lazy = function() {
 
-    localRuntime.Native = localRuntime.Native || {};
-    localRuntime.Native.Lazy = localRuntime.Native.Lazy || {};
-    if (localRuntime.Native.Lazy.values) {
-        return localRuntime.Native.Lazy.values;
-    }
-
-    function memoize(thunk) {
-        var value;
-        var isForced = false;
-        return function(tuple0) {
-            if (!isForced) {
-                value = thunk(tuple0);
-                isForced = true;
-            }
-            return value;
-        };
-    }
-
-    return localRuntime.Native.Lazy.values = {
-        memoize: memoize
+function memoize(thunk)
+{
+    var value;
+    var isForced = false;
+    return function(tuple0) {
+        if (!isForced) {
+            value = thunk(tuple0);
+            isForced = true;
+        }
+        return value;
     };
+}
+
+return {
+    memoize: memoize
 };
+
+}();