I can't figure out what's the difference between Curly brace and Square bracket in Groovy/Grails
Example :
[bookInstanceList:Book.list()]
and :
{
subject blank: false
content blank: false, maxSize: 2000
}
can any one help me please?
Thank you
Groovy List and Map :
First one is Map.
[] (Square bracket) in groovy is used for making list or map.
Example of List:
[] - An empty list
[1,2,3,4] – A list of integer values
[‘Angular’, ‘Groovy’, ‘Java’] – A list of Strings
[1, 2, [3, 4], 5] – A nested list
Example of Map:
[ : ] – An Empty map.
[key: "value"] - Map with key and values
Groovy Closure :
The second one is groovy DSL. We can use multiple strategies to create DSL but in Grails domain constraint blocks used groovy closures for this. You can find more details about DSL here and closures here.
As pointed out in the comments the first is a Map and the second is a closure.
They aren't the same or similar in any way. You seem to be confused because you assume the closure is some type of name value pair. Which, in this case, it would appear to be because of the constraints DSL.
To further understand how this closure is processed you would need to dig deeper into the constraints DSL and see how it uses such things as missing methods and missing properties. It's not a simple subject to explain briefly.
Related
Curious about the syntax used in this example (https://learn.microsoft.com/en-us/dotnet/fsharp/get-started/get-started-command-line) within the file Library.js
My question, is the getJson function returning multiple values without a tuple?
Any link to F# documentation that explains this syntax would be nice. thanks.
open System.Text.Json
let getJson value =
let json = JsonSerializer.Serialize(value)
value, json
My question, is the getJson function returning multiple values without a tuple?
Yes to the first part, no to the second. The comma on the last line makes these two values a tuple.
You may think from online examples that a tuple is like (1, 2), but it’s just as fine to remove the parentheses if the expression is only on one line. In this case, value, json is the tuple.
Parentheses are used to disambiguate the order of evaluation. For instance, 1, “two”, “three” is a three-tuple of an int and two strings, but 1, (“two”, “three”) is a two-tuple of an int and the 2nd type being another two-tuple of two strings.
The Microsoft Learning link appears to always use parentheses in the examples. This post goes a little further, and has a bit more to say on tuple deconstruction as well: https://fsharpforfunandprofit.com/posts/tuples/.
Here’s more on parentheses (thanks Brent!): if it has a comma, it’s a tuple.
The following is my sample code: https://play.openpolicyagent.org/p/oyY1GOsYaf
Here when I try to evaluate names array, it is showing:
error occurred: 1:1: rego_unsafe_var_error: var names is unsafe
But when I define the same comprehension outside the allow rule definition : https://play.openpolicyagent.org/p/Xv0cF7FM8b, I am able to evaluate the selection
[
"smoke",
"dev"]
could someone help me to point out the difference and if I want to define the comprehention inside the rule is there any syntax I need to follow? Thanks in advance
Note: I am getting the final output as expected in both cases, only issue is with the names array evaluation.
The way the Rego Playground generates a query when evaluating a selection is much more simplistic than one might assume. A query will be generated from your selected text, without taking into account where in the document that text was selected. This means that even if you select a local variable inside a rule body, the query will simply contain that variable name (names, in your case); which will be perceived as a reference to a top-level variable in the document's body, even though a rule-local variable was selected. This is why your first sample returns an error, as there is no top-level variable names in the document; whereas the second sample does, and therefore succeeds.
You can test this quirk by selecting and evaluating the word hello on line 3 here: https://play.openpolicyagent.org/p/n5OPoFnlhx.
package play
# hello
hello {
m := input.message
m == "world"
}
Even though it's just part of a comment, it'll evaluate just as if you had selected the rule name on line 5.
I'm trying to see if I can use Red (or Rebol) to implement a simple DSL. I want to compile my DSL to source code for another language, perhaps Red or C# or both - rather than directly interpreting and executing it.
The DSL has only a couple of simple statements, plus an if/else statement.
Statements can be grouped into rules. A rule would get translated into a function definition, with each statement the equivalent statement in the target language.
The parse capability in Red/Rebol is great and lets me implement a parser very easily - in effect it's basically just the definition of the grammar itself.
However I haven't been able to find any examples of how to take the next steps, specifically handling an if statement and translating it to other source code.
Translating an if statement seems a good example of something minimal but still slightly tricky - because in Red having an else means you need to change the if to an either, rather than just an extra optional else.
Traditionally, during parsing I would build an abstract syntax tree, and then have functions to operate on the AST and generate the new source code. Should I be following this same approach or is there some other more idiomatic way in Red ?
I've experimented with using collect/keep in my parse rules to return a block of nested blocks, which in effect forms the AST. Another approach would be to save data into specific objects representing the different statements etc.
I'm still getting to grips with collect/keep, as to when a new block will be created and what will be kept. I'd also like to keep my parser rules as "clean" as possible, with as little other code intertwined in it. So I'm still not sure how best to add in Red code in round brackets in the parse rules. Adding code too early can cause the Red code to get executed, even if the rule eventually fails. Adding code too late means the code may not be executed in the order you expect, especially when dealing with multi-level statements like if, which can contain other statements.
So, specifically, any help on how to translate my example DSL to Red source code would be appreciated. Also any links to implementing DSLs like this in Red or Rebol would be great ! :)
Here are my parse rules :-
Red [
Purpose: example rules for parsing a simple language
]
SimpleLanguageParser: make object! [
Expr: [string! | integer! | block!]
Data: ['Person.AGE | 'Person.INCOME]
WriteMessageToLog: ['write 'message 'to 'log Expr]
SetData: ['set 'data Data '= Expr]
IfStatement: ['if Expr [any Statement] opt ['else [any Statement]] 'endif]
Statement: [WriteMessageToLog | SetData | IfStatement]
Rule: [
'rule word!
[any Statement]
'endrule
]
AnySimpLeLanguage: [Rule | [any Statement]]
]
SL: function [slInput] [
parse slInput SimpleLanguageParser/AnySimpleLanguage
]
An example of some source in the DSL :-
RULE TooYoung
IF [Person.Age < 15]
WRITE MESSAGE TO LOG "too young to earn an income"
SET DATA Person.Income = 0
ELSE
WRITE MESSAGE TO LOG "old enough"
ENDIF
ENDRULE
Translated to Red source code :-
TooYoung: function [] [
either Person.Age < 15 [
WriteMessageToLog "too young to earn an income"
Person.Income: 0
] [
WriteMessageToLog "old enough"
]
]
The data, ie Person.Age, Person.Income, and the function WriteMessageToLog are all things which would have been previously defined.
Note, for simplicity I've left Expr as block! etc, rather than defining Expr in any more detail in the DSL itself. Also, setting Person.Income in the function doesn't work as coded as it sets a local - but that's ok for now :)
Always nice to see someone digging language-oriented programming, keep it up and welcome to Red! ;)
Specifying correct grammar rules is the trickiest part of the job, and you've already nailed that. What's left is to intersperse your PEG (parsing expression grammar) with set, copy, collect/keep combo and paren! expressions in the right places, and then either create an AST from that or, in simplier cases, emit code directly.
Example
Here's a quickly baked (and definitely buggy!) example of how I'd tackled your task. Basically, it's slightly reworked code of yours, where matched patterns are setted, copyed or collected, and then bounded to specific words, which then just pasted into "template" (compose function inside emit-rule) to produce a Red code.
It's not the only way, I believe. #rebolek might come up with more industrial-strength solution, as he has experience with sophisticated parsers, which I'm lacking :P
Followup
As for if/else dilemma, I followed the approach proposed above -- instead of using opt I wrapped rule for else-branch into block and added an alternative match, which just sets false-block to none.
What to use for AST -- anything that allow to express a hierarchical structure, which is either a block! (though for performance gain you might want to use hash! or map!) or an object!. The advantage of object! is that it provides a context to be bound to, but here we're approaching a realm of so-called Bindology ("scoping" rules of Red language), which is another beast :)
Emitting C# code would be harder, but doable -- you'll need to assemble a string instead of Red code. I think, however, that, as a newcomer, you should stick with parsing directly at block-level (the way you done in your example), because it a lot easier and much expressive.
Another interesting (but much hairy) approach would be to re-define all words used in your DSL-block to work as you want.
Resources
We have a wiki entry about Red/Rebol dialects on github, which you might find if not useful, but interesting to read.
Also, two articles (this and this) in Red blog, I think you skimmed over first one already (if not, you should!).
Last, but not least, an exhaustive review of Parse principles and keywords (which has a couple of wrong parts in it though, so, caveat emptor). It's written for Rebol, but you should adapt examples to Red rather easily.
As a relative newcomer to the language, I do agree that there's a lack of examples and tutorials about DSL development, but we're working on that (at least in our heads) :)
Taking 9214's answer as a starting point, I've coded one possible solution. My approach has been :-
try to keep the parse rules as "clean" as possible
use collect and keep to return a block as the result, rather than trying to build a more complex AST
do some minimal translation in the keeps
the resulting block should be valid Red code
which uses predefined functions, where any more complex processing needs to happen
Most simple statements are easily translated to functions eg WRITE MESSAGE TO LOG becomes SL_WriteMessageToLog which can then do whatever it needs to do.
More complicated statements with structure, eg If/Else become functions which take block parameters which can then process the blocks as required.
For the If/Else complication, I've made this into two separate functions, SL_If and SL_Else. SL_If stores the result of the condition in a sequence, and SL_Else checks the latest result and removes it. This allows for nested If/Elses.
The presence of the final endrule can be checked for to ensure the input was correctly parsed. Once this is removed, we should have a valid function definition.
Here's the code :-
Red [
Purpose: example rules for parsing and translating a simple language
]
; some data
Person.AGE: 0
Person.INCOME: 0
; functions to implement some simple SL statements
SL_WriteMessageToLog: function [value] [
print value
]
SL_SetData: function [parmblock] [
field: parmblock/1
value: parmblock/2
if type? value = word! [
value: do value
]
print ["old value" field "=" do field]
set field value
print ["new value" field "=" do field]
]
; hold the If condition results, to be used to determine whether or not to do Else
IfConditionResults: []
SL_If: function [cond stats] [
cond_result: do cond
head insert IfConditionResults cond_result
if cond_result stats
]
SL_Else: function [stats] [
cond_result: first IfConditionResults
remove IfConditionResults
if not cond_result stats
]
; parsing rules
SimpleLanguageParser: make object! [
Expr: [logic! | string! | integer! | block!]
Data: ['Person.AGE | 'Person.INCOME]
WriteMessageToLog: ['write 'message 'to 'log set x Expr keep ('SL_WriteMessageToLog) keep (x)]
SetData: ['set 'data set d Data '= set x Expr keep ('SL_SetData) keep (reduce [d x])]
IfStatement: ['if keep ('SL_If) keep Expr collect [any Statement] opt ['else keep ('SL_Else) collect [any Statement]] 'endif]
Statement: [WriteMessageToLog | SetData | IfStatement]
Rule: [collect [
'rule set fname word! keep (to set-word! fname) keep ('does)
collect [any Statement]
keep 'endrule
]
]
AnySimpLeLanguage: [Rule | [any Statement]]
]
SL: function [slInput] [
parse slInput SimpleLanguageParser/Rule
]
For the example in the original post, the output is :-
TooYoung: does [
SL_If [Person.Age < 15] [
SL_WriteMessageToLog "too young to earn an income"
SL_SetData [Person.Income 0]
]
SL_Else [
SL_WriteMessageToLog "old enough"
]
]
ENDRULE
Thanks for your help to get this far.
Feedback on this approach and solution would be appreciated :)
I want to use erlang datetime values in the standard format {{Y,M,D},{H,Min,Sec}} in a MNESIA table for logging purposes and be able to select log entries by comparing with constant start and end time tuples.
It seems that the matchspec guard compiler somehow confuses tuple values with guard sub-expressions. Evaluating ets:match_spec_compile(MatchSpec) fails for
MatchSpec = [
{
{'_','$1','$2'}
,
[
{'==','$2',{1,2}}
]
,
['$_']
}
]
but succeeds when I compare $2 with any non-tuple value.
Is there a restriction that match guards cannot compare tuple values?
I believe the answer is to use double braces when using tuples (see Variables and Literals section of http://www.erlang.org/doc/apps/erts/match_spec.html#id69408). So to use a tuple in a matchspec expression, surround that tuple with braces, as in,
{'==','$2',{{1,2}}}
So, if I understand your example correctly, you would have
22> M=[{{'_','$1','$2'},[{'==','$2',{{1,2}}}],['$_']}].
[{{'_','$1','$2'},[{'==','$2',{{1,2}}}],['$_']}]
23> ets:match_spec_run([{1,1,{1,2}}],ets:match_spec_compile(M)).
[{1,1,{1,2}}]
24> ets:match_spec_run([{1,1,{2,2}}],ets:match_spec_compile(M)).
[]
EDIT: (sorry to edit your answer but this was the easiest way to get my comment in a readable form)
Yes, this is how it must be done. An easier way to get the match-spec is to use the (pseudo) function ets:fun2ms/1 which takes a literal fun as an argument and returns the match-spec. So
10> ets:fun2ms(fun ({A,B,C}=X) when C == {1,2} -> X end).
[{{'$1','$2','$3'},[{'==','$3',{{1,2}}}],['$_']}]
The shell recognises ets:fun2ms/1. For more information see ETS documentation. Mnesia uses the same match-specs as ETS.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Array slicing in Ruby: looking for explanation for illogical behaviour (taken from Rubykoans.com)
Say you have an array
a = [1,2,3]
why the a.slice(3,6) returns [] while the a.slice(4,6) returns nil?
The documentation lists special cases for when the start index equal to the length of the array:
a = [ "a", "b", "c", "d", "e" ]
# special cases
a[5, 1] #=> []
a[5..10] #=> []
from: http://www.ruby-doc.org/core-1.9.3/Array.html#method-i-slice
So this appears to be the built-in functionality, since the start index is the length of the array the slice method is supposed to return an [], but when you pass the length of the array you get nil. This is probably due to how Ruby is defining ranges within an array.
Because it makes assignment more general
The mechanism is designed this way so slices can work in a highly generalized way on the left-hand side of assignment operators.
It doesn't really matter for #slice exactly because that result cannot be assigned but the same interpretation applies to x[3, 6] and those expressions can be assigned.
It's best to look at the array indices as identifying the spaces between elements, rather than the elements themselves.
This interpretation creates a consistent and useful interface ... for example, code can be written that will handle replacing elements or appending to zero length or populated Arrays, and all without needing special-case tests.