README.md in mini_kraken-0.2.04 vs README.md in mini_kraken-0.3.00
- old
+ new
@@ -2,38 +2,38 @@
[](https://travis-ci.org/famished-tiger/mini_kraken)
[](https://badge.fury.io/rb/mini_kraken)
[](https://github.com/famished-tiger/mini_kraken/blob/master/LICENSE.txt)
### What is __mini_kraken__ ?
-A library containing an implementation of the [miniKanren](http://minikanren.org/)
-relational programming language in Ruby.
-*miniKanren* is a small language for relational (logic) programming.
-Based on the reference implementation, in Scheme from the "The Reasoned Schemer" book.
+A library containing an implementation in Ruby of the [miniKanren](http://minikanren.org/)
+ language.
+*miniKanren* is a small language for relational (logic) programming as defined in the "The Reasoned Schemer" book.
Daniel P. Friedman, William E. Byrd, Oleg Kiselyov, and Jason Hemann: "The Reasoned Schemer", Second Edition,
ISBN: 9780262535519, (2018), MIT Press.
### Features
- Pure Ruby implementation, not a port from another language
- Object-Oriented design
- No runtime dependencies
+- Test suite patterned on the examples from the reference book.
### miniKanren Features
- [X] ==
- [X] run\*
- [X] fresh
- [X] conde
- [X] conj2
- [X] disj2
- [X] defrel
-- [X] caro
+- [X] caro
+- [X] cdro
### TODO
- [ ] Occurs check
-List-centric relations from Chapter 2
-- [ ] cdro
+List-centric relations from Chapter 2
- [ ] conso
- [ ] nullo
- [ ] pairo
- [ ] singletono
@@ -63,11 +63,11 @@
```ruby
require 'mini_kraken' # Load MiniKraken library
extend(MiniKraken::Glue::DSL) # Add DSL method to self (object in context)
-result = run_star('q', equals(q, :pea))
+result = run_star('q', unify(q, :pea))
puts result # => (:pea)
```
The two first lines in the above code snippet are pretty standard:
- The first line loads the `mini_kraken` library.
@@ -77,15 +77,15 @@
The aim of a `miniKanren` program is to find one or more solutions involving the given logical variable(s)
and satisfying one or more goals to the `run_star method.
In our example, the `run_star` method instructs `MiniKraken` to find all solutions,
knowing that each successful solution:
- binds a value to the provided variable `q` and
-- meets the goal `equals(q, :pea)`.
+- meets the goal `unify(q, :pea)`.
-The goal `equals(q, :pea)` succeeds because the logical variable `q` is _fresh_ (that is,
+The goal `unify(q, :pea)` succeeds because the logical variable `q` is _fresh_ (that is,
not yet bound to a value) and will be bound to the symbol `:pea` as a side effect
- of the goal `equals`.
+ of the goal `unify`.
So the above program succeeds and the only found solution is obtained by binding
the variable `q` to the value :pea. Hence the result of the `puts` method.
### Example 2
@@ -95,36 +95,36 @@
require 'mini_kraken' # Load MiniKraken library
extend(MiniKraken::Glue::DSL) # Add DSL method to self (object in context)
# Following miniKanren program fails
- result = run_star('q', [equals(q, :pea), equals(q, :pod)])
+ result = run_star('q', [unify(q, :pea), unify(q, :pod)])
puts result # => ()
```
In this example, we learn that `run_star` can take multiple goals placed in an array.
-The program fails to find a solution since it is not possible to satisfy the two `equals` goals simultaneously.
+The program fails to find a solution since it is not possible to satisfy the two `unify` goals simultaneously.
In case of failure, the `run_star` returns an empty list represented as `()` in the output.
### Example 3
The next example shows the use two logical variables.
```ruby
# In this example and following, one assumes that DSL is loaded as shown in Example 1
-result = run_star(['x', 'y'], [equals(:hello, x), equals(y, :world)])
+result = run_star(['x', 'y'], [unify(:hello, x), unify(y, :world)])
puts result # => ((:hello :world))
```
This time, `run_star` takes two logical variables -`x` and `y`- and successfully finds the solution `x = :hello, y = :world`.
### Example 4
The next example shows the use of `disj2` goals.
```ruby
result = run_star(['x', 'y'],
[
- disj2(equals(x, :blue), equals(x, :red)),
- disj2(equals(y, :sea), equals(:mountain, y))
+ disj2(unify(x, :blue), unify(x, :red)),
+ disj2(unify(y, :sea), unify(:mountain, y))
])
puts result # => ((:blue :sea) (:blue :mountain) (:red :sea) (:red :mountain))
```
Here, `run_star` takes two logical variables and two `disj2` goals.