Raku mixins have two (or more) natures, combining several values in the same container, or values along with roles. However, there is not, as far as I can tell, a straightforward way to check for "mixinity" in a variable that has not been created by you.
This might be a trick
my $foo = 3 but Stringy;
say $foo.^name ~~ /\+/;# OUTPUT: «｢+｣»
But is there any other property I'm missing that would allow to look this up directly?
I think you're missing the ^roles and ^parents meta-methods:
my $foo = 3 but Stringy;
dd $foo.^roles; # (Stringy, Real, Numeric)
dd $foo.^parents; # (Int,)
TL;DR My unreliable solution[1] is simpler and faster than your unreliable solution[2] and should work for question Y and maybe question X[3]:
sub is-mixin ($object) { $object.^is_mixin =:= 1 }
say is-mixin 3; # False
say is-mixin 3 but 'bar'; # True
Footnotes
[1] "Warning: [role Metamodel::Mixins] is part of the Rakudo implementation, and is not a part of the language specification."
[2] I haven't searched roast but would imagine that the use of + in type names is just a convention, not a part of the language specification.
[3] I found your question to be an example of either the XY problem, per my first comment below it; and/or of terminological confusion, per my second. The rest of this answer explains what I mean.
Is there a straightforward way to check if a container is a mixin?
The word "container" has a technical meaning in Raku. It refers to a value that follows Raku's container protocol. The container protocol applies when a value is followed by = to invoke "assignment".
What you are asking about appears to have nothing to do with such a container, as something distinct from a value. And there's good reason to think that that doesn't matter to you -- that what you are just interested in is testing if a value is a mixin, and the "container" aspect is a red-herring, either because you didn't mean "container" in the usual sense in Raku, or because it doesn't matter anyway because a container is a value, so whatever works for testing a value will work for testing a container.
For example, looking at your "trick":
my $foo = 3 but Stringy;
say $foo.^name ~~ /\+/;# OUTPUT: «｢+｣»
This trick is unrelated to any container aspect using the normal technical use of the word "container" in Raku. You get the same result if you write the following that doesn't involve a container: say (3 but Stringy).^name ~~ /\+/;# OUTPUT: «｢+｣».
So in my solution I've presumed you just meant a value, knowing that it actually doesn't matter whether or not your ultimate focus is on a container.
If I'm wrong about my presumption, and it makes a difference, I urge you to explain the X of what it is you're trying to do rather than just the Y.
Your trick makes your code brittle because it doesn't expect
$foo.^set_name('The Spanish Inquisition');
Of course nobody does :)
You better just ask the Rakudo Metamodel:
say $foo.^is_mixin; # OUTPUT: «1»
Two things to note:
The is_mixin metamethod does not return a Bool
Like the name metamethod it is specific to the Rakudo implementation of Raku
I am trying to achieve an M2M transformation using ATL. So I am transforming a source model (1) to target model (2), I am very new to ATL and I can't find any documentation on how to enable many to many transformations. What I am trying to do is:
transform (1) Source model with a class named "operation", which references another class named "parameter", the reference is named "operationInput" and its cardinality is (0..n) to (2) Target model with a class named "function", which references another class named "Param", the reference is named "functionInput" and its cardinality is (0..n).
So i wrote the following ATL transformation:
rule operation2Function {
from
s: Source!operation
to
t: Target!Function
(
functionInput<-s.operationInput)
}
However, it did not seem to work because the cardinality is many to many , soi tried the following code:
rule operation2Function {
from
s: Source!operation
to
t: Target!Function
(
functionInput<-Source!operation.allInstances() ->select(e | e.oclIsTypeOf(Source!operation)->collect(e| e.operationInput),
)
}
I still don't get the proper result even though I initialized an instance of the source metamodel.
I would appreciate your help on how to enable many to many ((0..n) or (1..n)) transformations.
ATL is a declarative transformation language so you are best just specifying what must happen but not how, so rather than tunnel down imperatively to cope with the multiplicity of function parameters, just write a separate rule that relates 1 parameter to 1 operation input in the context of the parameter's containing function and the operation input's containing operation.
If you really want to transform imperatively you may prefer QVTo.
(allInstances() is almost always the wrong solution. At best inefficient, at worst able to use many wrong contributions.)
I'm new to OCL and currently trying to figure out how to do invariants.
I attached a picture with the diagramm I'm working on.
https://imgur.com/1ucZq5w
The invariants that I'm trying to resolve are :
a) A player has 0 or 2 cards in hand.
Context Player
inv i1: self.card->size()=0 or self.card->size()=2
b) A player, who has not played any rounds, can't have more Game Capital than the maximal Buy-In of the table.
Context Player
inv i2: self.numberOfRounds=0 implies (self.gameCapital < self.Table.maxBuyIn)
c) At every table can be only players that belong to different users
Context Player
inv i3: Player.UserAccount.allInstances().userID->isUnique()
I'm not sure if 'allInstances()' is supposed to go after Player or after PlayerAccount.
And I don't know what I'm supposed to do with the 'At every table' part of the text.
There are two more points that I really don't know how to do.
d) In the deck are 52 cards, which differ from eachother through color or value
e) The inputs of all players that still have cards in the hand are equal when bidDone True.
Can you please tell me if what I've done until now is correct and maybe some advice or solution for d) and e)?
Any help is appreciated!
Seems plausible, but I would recommend sensible names, since a validation tool will tend to report that e.g Constraint Player::i2 is not satisfied for ...
b) looks to have a < / <= bug
c) allInstances takes a type source so "Player." is wrong. allInstances is generally very inefficient to execute so should only be used as a last resort. In your case it is clearly wrong since your scope is "at every Table". You should be using context Table and then reasoning about the players at the table.
d) if you rephrase "differ from" as "is unique with respect to", you can perhaps see how you could use a Tuple of color+value as the basis for uniqueness.
e) no idea what an input is, but it just seems like a cascade of implies clauses.
At my company we've recently been working on a modification to an existing program that used the following logic to perform some database field assignments:
db-buffer1.field1 = if db-buffer1.field1 <> db-buffer2.field2
then db-buffer2.field2
else db-buffer1.field1
I'm not 100% sure of the original programmer's intention here. Can anyone help me understand the value in comparing whether or not the field values are different before deciding whether to assign the new field?
If the comparison is 'false' and we end up assigning db-buffer1.field1 = db-buffer1.field1 do we avoid a write operation on the database?
Also note that this example is part of a larger ASSIGN statement that contains several fields running similar assignment/comparison logic. Does that have any effect on the value of this additional code? (i.e. Do all comparisons in the ASSIGN statement have to succeed in order to avoid a DB write?)
An "IF function" on the right hand side of an expression is a lot like a "ternary operator" in C or Javascript (the "?:" construct).
It only impacts the portion of the ASSIGN that it is part of. When I write code using those I always encase it in parens to make it clear. Like so:
assign
a = ( if x = y then b else c )
z = 2
.
Whether or not a WRITE happens depends a lot on the rest of the code.
Judging only by this snippet you are going to write SOMETHING (at least logically). db-buffer.field1 is going to get a value assigned to it regardless. The IF logic on the right-hand side is just picking if it will be field1 or field2. In the case that boils down to field1 = field1 you might hope that some lower layer will optimize the write out of existence. I don't see your Progress version posted but if it is v9 or better then it may very well be optimized away. (Prior to v9 it would not have been.)
If you really want to "avoid the write" at the application level you should code it like this:
if field1 <> field2 then
assign
field1 = field2
.
This form does not use the IF function, it is just a normal IF ... THEN statement. It is much clearer and it does not depend on optimizations at a lower level. Of course the snippet shown is said to be part of a larger ASSIGN -- so it may or may not be sensible to break it out and write it as I've shown. But it would be worth thinking about.
It appears that the programmer is checking if field1 is not equal to field2 go ahead and update it.
They might as well simply use the following since either way the field is being assigned:
assign db-buffer1.field1 = db-buffer2.field2.
When using the ASSIGN statement (recommended always), from a logical perspective you have to keep in mind that each line is assigned separately.
Tom has a great answer here that gives more information regarding efficiency/history of the ASSIGN statement.
I would be very interested in seeing the rest of the assign statement, but I would also get rid of the if logic in this case as it adds no value, just and extra instruction. As Terry stated above
ASSIGN db-buffer1.field1 = db-buffer2.field2.
Consider a lookup function with the following signature, which needs to return an integer for a given string key:
int GetValue(string key) { ... }
Consider furthermore that the key-value mappings, numbering N, are known in advance when the source code for function is being written, e.g.:
// N=3
{ "foo", 1 },
{ "bar", 42 },
{ "bazz", 314159 }
So a valid (but not perfect!) implementation for the function for the input above would be:
int GetValue(string key)
{
switch (key)
{
case "foo": return 1;
case "bar": return 42;
case "bazz": return 314159;
}
// Doesn't matter what we do here, control will never come to this point
throw new Exception();
}
It is also known in advance exactly how many times (C>=1) the function will be called at run-time for every given key. For example:
C["foo"] = 1;
C["bar"] = 1;
C["bazz"] = 2;
The order of such calls is not known, however. E.g. the above could describe the following sequence of calls at run-time:
GetValue("foo");
GetValue("bazz");
GetValue("bar");
GetValue("bazz");
or any other sequence, provided the call counts match.
There is also a restriction M, specified in whatever units is most convenient, defining the upper memory bound of any lookup tables and other helper structures that can be used by the GetValue (the structures are initialized in advance; that initialization is not counted against the complexity of the function). For example, M=100 chars, or M=256 sizeof(object reference).
The question is, how to write the body of GetValue such that it is as fast as possible - in other words, the aggregate time of all GetValue calls (note that we know the total count, per everything above) is minimal, for given N, C and M?
The algorithm may require a reasonable minimal value for M, e.g. M >= char.MaxValue. It may also require that M be aligned to some reasonable boundary - for example, that it may only be a power of two. It may also require that M must be a function of N of a certain kind (for example, it may allow valid M=N, or M=2N, ...; or valid M=N, or M=N^2, ...; etc).
The algorithm can be expressed in any suitable language or other form. For runtime performance constrains for generated code, assume that the generated code for GetValue will be in C#, VB or Java (really, any language will do, so long as strings are treated as immutable arrays of characters - i.e. O(1) length and O(1) indexing, and no other data computed for them in advance). Also, to simplify this a bit, answers which assume that C=1 for all keys are considered valid, though those answers which cover the more general case are preferred.
Some musings on possible approaches
The obvious first answer to the above is using a perfect hash, but generic approaches to finding one seem to be imperfect. For example, one can easily generate a table for a minimal perfect hash using Pearson hashing for the sample data above, but then the input key would have to be hashed for every call to GetValue, and Pearson hash necessarily scans the entire input string. But all sample keys actually differ in their third character, so only that can be used as the input for the hash instead of the entire string. Furthermore, if M is required to be at least char.MaxValue, then the third character itself becomes a perfect hash.
For a different set of keys this may no longer be true, but it may still be possible to reduce the amount of characters considered before the precise answer can be given. Furthermore, in some cases where a minimal perfect hash would require inspecting the entire string, it may be possible to reduce the lookup to a subset, or otherwise make it faster (e.g. a less complex hashing function?) by making the hash non-minimal (i.e. M > N) - effectively sacrificing space for the sake of speed.
It may also be that traditional hashing is not such a good idea to begin with, and it's easier to structure the body of GetValue as a series of conditionals, arranged such that the first checks for the "most variable" character (the one that varies across most keys), with further nested checks as needed to determine the correct answer. Note that "variance" here can be influenced by the number of times each key is going to be looked up (C). Furthermore, it is not always readily obvious what the best structure of branches should be - it may be, for example, that the "most variable" character only lets you distinguish 10 keys out of 100, but for the remaining 90 that one extra check is unnecessary to distinguish between them, and on average (considering C) there are more checks per key than in a different solution which does not start with the "most variable" character. The goal then is to determine the perfect sequence of checks.
You could use the Boyer search, but I think that the Trie would be a much more effiecent method. You can modify the Trie to collapse the words as you make the hit count for a key zero, thus reducing the number of searches you would have to do the farther down the line you get. The biggest benefit you would get is that you are doing array lookups for the indexes, which is much faster than a comparison.
You've talked about a memory limitation when it comes to precomputation - is there also a time limitation?
I would consider a trie, but one where you didn't necessarily start with the first character. Instead, find the index which will cut down the search space most, and consider that first. So in your sample case ("foo", "bar", "bazz") you'd take the third character, which would immediately tell you which string it was. (If we know we'll always be given one of the input words, we can return as soon as we've found a unique potential match.)
Now assuming that there isn't a single index which will get you down to a unique string, you need to determine the character to look at after that. In theory you precompute the trie to work out for each branch what the optimal character to look at next is (e.g. "if the third character was 'a', we need to look at the second character next; if it was 'o' we need to look at the first character next) but that potentially takes a lot more time and space. On the other hand, it could save a lot of time - because having gone down one character, each of the branches may have an index to pick which will uniquely identify the final string, but be a different index each time. The amount of space required by this approach would depend on how similar the strings were, and might be hard to predict in advance. It would be nice to be able to dynamically do this for all the trie nodes you can, but then when you find you're running out of construction space, determine a single order for "everything under this node". (So you don't end up storing a "next character index" on each node underneath that node, just the single sequence.) Let me know if this isn't clear, and I can try to elaborate...
How you represent the trie will depend on the range of input characters. If they're all in the range 'a'-'z' then a simple array would be incredibly fast to navigate, and reasonably efficient for trie nodes where there are possibilities for most of the available options. Later on, when there are only two or three possible branches, that becomes wasteful in memory. I would suggest a polymorphic Trie node class, such that you can build the most appropriate type of node depending on how many sub-branches there are.
None of this performs any culling - it's not clear how much can be achieved by culling quickly. One situation where I can see it helping is when the number of branches from one trie node drops to 1 (because of the removal of a branch which is exhausted), that branch can be eliminated completely. Over time this could make a big difference, and shouldn't be too hard to compute. Basically as you build the trie you can predict how many times each branch will be taken, and as you navigate the trie you can subtract one from that count per branch when you navigate it.
That's all I've come up with so far, and it's not exactly a full implementation - but I hope it helps...
Is a binary search of the table really so awful? I would take the list of potential strings and "minimize" them, the sort them, and finally do a binary search upon the block of them.
By minimize I mean reducing them to the minimum they need to be, kind of a custom stemming.
For example if you had the strings: "alfred", "bob", "bill", "joe", I'd knock them down to "a", "bi", "bo", "j".
Then put those in to a contiguous block of memory, for example:
char *table = "a\0bi\0bo\0j\0"; // last 0 is really redundant..but
char *keys[4];
keys[0] = table;
keys[1] = table + 2;
keys[2] = table + 5;
keys[3] = table + 8;
Ideally the compiler would do all this for you if you simply go:
keys[0] = "a";
keys[1] = "bi";
keys[2] = "bo";
keys[3] = "j";
But I can't say if that's true or not.
Now you can bsearch that table, and the keys are as short as possible. If you hit the end of the key, you match. If not, then follow the standard bsearch algorithm.
The goal is to get all of the data close together and keep the code itty bitty so that it all fits in to the CPU cache. You can process the key from the program directly, no pre-processing or adding anything up.
For a reasonably large number of keys that are reasonably distributed, I think this would be quite fast. It really depends on the number of strings involved. For smaller numbers, the overhead of computing hash values etc is more than search something like this. For larger values, it's worth it. Just what those number are all depends on the algorithms etc.
This, however, is likely the smallest solution in terms of memory, if that's important.
This also has the benefit of simplicity.
Addenda:
You don't have any specifications on the inputs beyond 'strings'. There's also no discussion about how many strings you expect to use, their length, their commonality or their frequency of use. These can perhaps all be derived from the "source", but not planned upon by the algorithm designer. You're asking for an algorithm that creates something like this:
inline int GetValue(char *key) {
return 1234;
}
For a small program that happens to use only one key all the time, all the way up to something that creates a perfect hash algorithm for millions of strings. That's a pretty tall order.
Any design going after "squeezing every single bit of performance possible" needs to know more about the inputs than "any and all strings". That problem space is simply too large if you want it the fastest possible for any condition.
An algorithm that handles strings with extremely long identical prefixes might be quite different than one that works on completely random strings. The algorithm could say "if the key starts with "a", skip the next 100 chars, since they're all a's".
But if these strings are sourced by human beings, and they're using long strings of the same letters, and not going insane trying to maintain that data, then when they complain that the algorithm is performing badly, you reply that "you're doing silly things, don't do that". But we don't know the source of these strings either.
So, you need to pick a problem space to target the algorithm. We have all sorts of algorithms that ostensibly do the same thing because they address different constraints and work better in different situations.
Hashing is expensive, laying out hashmaps is expensive. If there's not enough data involved, there are better techniques than hashing. If you have large memory budget, you could make an enormous state machine, based upon N states per node (N being your character set size -- which you don't specify -- BAUDOT? 7-bit ASCII? UTF-32?). That will run very quickly, unless the amount of memory consumed by the states smashes the CPU cache or squeezes out other things.
You could possibly generate code for all of this, but you may run in to code size limits (you don't say what language either -- Java has a 64K method byte code limit for example).
But you don't specify any of these constraints. So, it's kind of hard to get the most performant solution for your needs.
What you want is a look-up table of look-up tables.
If memory cost is not an issue you can go all out.
const int POSSIBLE_CHARCODES = 256; //256 for ascii //65536 for unicode 16bit
struct LutMap {
int value;
LutMap[POSSIBLE_CHARCODES] next;
}
int GetValue(string key) {
LutMap root = Global.AlreadyCreatedLutMap;
for(int x=0; x<key.length; x++) {
int c = key.charCodeAt(x);
if(root.next[c] == null) {
return root.value;
}
root = root.next[c];
}
}
I reckon that it's all about finding the right hash function. As long as you know what the key-value relationship is in advance, you can do an analysis to try and find a hash function to meet your requrements. Taking the example you've provided, treat the input strings as binary integers:
foo = 0x666F6F (hex value)
bar = 0x626172
bazz = 0x62617A7A
The last column present in all of them is different in each. Analyse further:
foo = 0xF = 1111
bar = 0x2 = 0010
bazz = 0xA = 1010
Bit-shift to the right twice, discarding overflow, you get a distinct value for each of them:
foo = 0011
bar = 0000
bazz = 0010
Bit-shift to the right twice again, adding the overflow to a new buffer:
foo = 0010
bar = 0000
bazz = 0001
You can use those to query a static 3-entry lookup table. I reckon this highly personal hash function would take 9 very basic operations to get the nibble (2), bit-shift (2), bit-shift and add (4) and query (1), and a lot of these operations can be compressed further through clever assembly usage. This might well be faster than taking run-time infomation into account.
Have you looked at TCB . Perhaps the algorithm used there can be used to retrieve your values. It sounds a lot like the problem you are trying to solve. And from experience I can say tcb is one of the fastest key store lookups I have used. It is a constant lookup time, regardless of the number of keys stored.
Consider using Knuth–Morris–Pratt algorithm.
Pre-process given map to a large string like below
String string = "{foo:1}{bar:42}{bazz:314159}";
int length = string.length();
According KMP preprocessing time for the string will take O(length).
For searching with any word/key will take O(w) complexity, where w is length of the word/key.
You will be needed to make 2 modification to KMP algorithm:
key should be appear ordered in the joined string
instead of returning true/false it should parse the number and return it
Wish it can give a good hints.
Here's a feasible approach to determine the smallest subset of chars to target for your hash routine:
let:
k be the amount of distinct chars across all your keywords
c be the max keyword length
n be the number of keywords
in your example (padded shorter keywords w/spaces):
"foo "
"bar "
"bazz"
k = 7 (f,o,b,a,r,z, ), c = 4, n = 3
We can use this to compute a lower bound for our search. We need at least log_k(n) chars to uniquely identify a keyword, if log_k(n) >= c then you'll need to use the whole keyword and there's no reason to proceed.
Next, eliminate one column at a time and check if there are still n distinct values remaining. Use the distinct chars in each column as a heuristic to optimize our search:
2 2 3 2
f o o .
b a r .
b a z z
Eliminate columns with the lowest distinct chars first. If you have <= log_k(n) columns remaining you can stop. Optionally you could randomize a bit and eliminate the 2nd lowest distinct col or try to recover if the eliminated col results in less than n distinct words. This algorithm is roughly O(n!) depending on how much you try to recover. It's not guaranteed to find an optimal solution but it's a good tradeoff.
Once you have your subset of chars, proceed with the usual routines for generating a perfect hash. The result should be an optimal perfect hash.