Documentation on actual runtime stuff, variables, scope, functions, etc...
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doc/runtime.md
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doc/runtime.md
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# Runtime
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Any ginger data-structure can be put into a ginger file. The data itself has no executional meaning on its own, but if
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the data is properly formed it can be parsed by the ginger interpreter and a thread of execution can be started. For
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example, if I put the following in a file called `test.gng`:
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```
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(1 2 3)
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```
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It doesn't have any meaning, it's just a list. However, if you put the following:
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```
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(add 1 2 3)
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```
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and run `ginger test.gng` then a program can be interpreted from the given data. This file describes how given data can
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be formed into a valid program.
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## Eval
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Ginger evaluation is done the same was as other lisp languages: the first item in a list is the function name, the rest
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of the items in the list are arguments to the function. In the example above, `add` is the function name, and `1`, `2`,
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and `3` are arguments to the function.
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Arguments to a function can be functions to be eval'd themselves. An equivalent to the example above would have been:
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```
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(add 1 2 (add 1 2))
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```
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## Doing multiple things
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It's not very useful to only be able to do one thing. A vector of lists is interpreted into sequentially eval'ing each
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item in the vector. For (a trivial) example:
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```
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[ (add 1 2)
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(sub 4 (add 1 2))
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(mul 8 0) ]
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```
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## Variables/Scope
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The above example does a few things, but it repeats itself in the second part (with the `sub`). If we could save the
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result of the addition to a variable that would be awesomesauce. The `=` function does this! It makes it so that the
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first argument is equivalent to the evaluation of the second argument. Variables' first letters must be upper-case, this
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is how they're differentiated from raw string literals. The above could be re-written as:
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```
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[ (= AdditionResult (add 1 2))
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(sub 4 AdditionResult)
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(mul 8 0) ]
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```
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In the above example `AdditionResult` is a valid variable inside of the vector that contains its declaration, and any
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vectors contained within that vector. For example:
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```
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[ (= AdditionResult (add 1 2))
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[ (sub 4 AdditionResult) ;This works
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(mul 8 0) ] ]
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[ (add 4 AdditionResult) ] ;This does not work!
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```
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## Literals
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We've determined that a list is interpreted as a function/arguments set, and an upper-case string is interpreted as a
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variable name which will be de-referenced. What if we want to actually use these structures without eval'ing them? For
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these cases we have the literal function `l`:
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```
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[ (concat (l (1 2 3)) (l (4 5 6))) ; => (1 2 3 4 5 6)
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(println (l "I start with a capital letter and I DONT CARE!!!")) ]
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```
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## Functions
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### Anonymous
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Anonymous functions are declared using the `fn` function. The first argument is a vector of argument names (remember,
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all upper-case!) and the second is a list/vector to be eval'd. Examples:
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```
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[ (= Add3 (fn [Num] (add Num 3)))
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(Add3 4) ; => 7
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(= Add3Sub1
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(fn [Num] [
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(= Added (add Num 3))
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(sub Added 1)
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]))
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(Add3Sub1 4) ] ; => 6
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```
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`fn` returns a function, which can be passed around and assigned like any other value. In the above examples the
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functions are assigned to the `Add3` and `Add3Sub1` variables. Functions can also be passed into other functions as
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arguments:
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```
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;DoTwice takes a function Fun and a number Num. it will call Fun twice on Num and return the result.
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[ (= DoTwice
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(fn [Fun Num]
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(Fun (Fun Num))))
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(DoTwice (fn [Num] (add Num 1)) 3) ] ; => 5
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```
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### Defined
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Defined functions attach the function definition to a string literal (lower-case) in the current scope. They are useful
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as they support more features then an anonymous function, such as inline documentation. These extra features will be
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documented elsewhere. To create a defined function use the `dfn` function:
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```
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[ (dfn add-four-sub-three [Num] [
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(= A (add Num 4))
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(sub A 3) ])
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(add-four-sub-three 4) ] ; => 5
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```
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