Is there a difference between foreach and map? - foreach

Ok this is more of a computer science question, than a question based on a particular language, but is there a difference between a map operation and a foreach operation? Or are they simply different names for the same thing?

Different.
foreach iterates over a list and performs some operation with side effects to each list member (such as saving each one to the database for example)
map iterates over a list, transforms each member of that list, and returns another list of the same size with the transformed members (such as converting a list of strings to uppercase)

The important difference between them is that map accumulates all of the results into a collection, whereas foreach returns nothing. map is usually used when you want to transform a collection of elements with a function, whereas foreach simply executes an action for each element.

In short, foreach is for applying an operation on each element of a collection of elements, whereas map is for transforming one collection into another.
There are two significant differences between foreach and map.
foreach has no conceptual restrictions on the operation it applies, other than perhaps accept an element as argument. That is, the operation may do nothing, may have a side-effect, may return a value or may not return a value. All foreach cares about is to iterate over a collection of elements, and apply the operation on each element.
map, on the other hand, does have a restriction on the operation: it expects the operation to return an element, and probably also accept an element as argument. The map operation iterates over a collection of elements, applying the operation on each element, and finally storing the result of each invocation of the operation into another collection. In other words, the map transforms one collection into another.
foreach works with a single collection of elements. This is the input collection.
map works with two collections of elements: the input collection and the output collection.
It is not a mistake to relate the two algorithms: in fact, you may view the two hierarchically, where map is a specialization of foreach. That is, you could use foreach and have the operation transform its argument and insert it into another collection. So, the foreach algorithm is an abstraction, a generalization, of the map algorithm. In fact, because foreach has no restriction on its operation we can safely say that foreach is the simplest looping mechanism out there, and it can do anything a loop can do. map, as well as other more specialized algorithms, is there for expressiveness: if you wish to map (or transform) one collection into another, your intention is clearer if you use map than if you use foreach.
We can extend this discussion further, and consider the copy algorithm: a loop which clones a collection. This algorithm too is a specialization of the foreach algorithm. You could define an operation that, given an element, will insert that same element into another collection. If you use foreach with that operation you in effect performed the copy algorithm, albeit with reduced clarity, expressiveness or explicitness. Let's take it even further: We can say that map is a specialization of copy, itself a specialization of foreach. map may change any of the elements it iterates over. If map doesn't change any of the elements then it merely copied the elements, and using copy would express the intent more clearly.
The foreach algorithm itself may or may not have a return value, depending on the language. In C++, for example, foreach returns the operation it originally received. The idea is that the operation might have a state, and you may want that operation back to inspect how it evolved over the elements. map, too, may or may not return a value. In C++ transform (the equivalent for map here) happens to return an iterator to the end of the output container (collection). In Ruby, the return value of map is the output sequence (collection). So, the return value of the algorithms is really an implementation detail; their effect may or may not be what they return.

Array.protototype.map method & Array.protototype.forEach are both quite similar.
Run the following code: http://labs.codecademy.com/bw1/6#:workspace
var arr = [1, 2, 3, 4, 5];
arr.map(function(val, ind, arr){
console.log("arr[" + ind + "]: " + Math.pow(val,2));
});
console.log();
arr.forEach(function(val, ind, arr){
console.log("arr[" + ind + "]: " + Math.pow(val,2));
});
They give the exact ditto result.
arr[0]: 1
arr[1]: 4
arr[2]: 9
arr[3]: 16
arr[4]: 25
arr[0]: 1
arr[1]: 4
arr[2]: 9
arr[3]: 16
arr[4]: 25
But the twist comes when you run the following code:-
Here I've simply assigned the result of the return value from the map and forEach methods.
var arr = [1, 2, 3, 4, 5];
var ar1 = arr.map(function(val, ind, arr){
console.log("arr[" + ind + "]: " + Math.pow(val,2));
return val;
});
console.log();
console.log(ar1);
console.log();
var ar2 = arr.forEach(function(val, ind, arr){
console.log("arr[" + ind + "]: " + Math.pow(val,2));
return val;
});
console.log();
console.log(ar2);
console.log();
Now the result is something tricky!
arr[0]: 1
arr[1]: 4
arr[2]: 9
arr[3]: 16
arr[4]: 25
[ 1, 2, 3, 4, 5 ]
arr[0]: 1
arr[1]: 4
arr[2]: 9
arr[3]: 16
arr[4]: 25
undefined
Conclusion
Array.prototype.map returns an array but Array.prototype.forEach doesn't. So you can manipulate the returned array inside the callback function passed to the map method and then return it.
Array.prototype.forEach only walks through the given array so you can do your stuff while walking the array.

the most 'visible' difference is that map accumulates the result in a new collection, while foreach is done only for the execution itself.
but there are a couple of extra assumptions: since the 'purpose' of map is the new list of values, it doesn't really matters the order of execution. in fact, some execution environments generate parallel code, or even introduce some memoizing to avoid calling for repeated values, or lazyness, to avoid calling some at all.
foreach, on the other hand, is called specifically for the side effects; therefore the order is important, and usually can't be parallelised.

Short answer: map and forEach are different. Also, informally speaking, map is a strict superset of forEach.
Long answer: First, let's come up with one line descriptions of forEach and map:
forEach iterates over all elements, calling the supplied function on each.
map iterates over all elements, calling the supplied function on each, and produces a transformed array by remembering the result of each function call.
In many languages, forEach is often called just each. The following discussion uses JavaScript only for reference. It could really be any other language.
Now, let's use each of these functions.
Using forEach:
Task 1: Write a function printSquares, which accepts an array of numbers arr, and prints the square of each element in it.
Solution 1:
var printSquares = function (arr) {
arr.forEach(function (n) {
console.log(n * n);
});
};
Using map:
Task 2: Write a function selfDot, which accepts an array of numbers arr, and returns an array wherein each element is the square of the corresponding element in arr.
Aside: Here, in slang terms, we are trying to square the input array. Formally put, we are trying to compute it's dot product with itself.
Solution 2:
var selfDot = function (arr) {
return arr.map(function (n) {
return n * n;
});
};
How is map a superset of forEach?
You can use map to solve both tasks, Task 1 and Task 2. However, you cannot use forEach to solve the Task 2.
In Solution 1, if you simply replace forEach by map, the solution will still be valid. In Solution 2 however, replacing map by forEach will break your previously working solution.
Implementing forEach in terms of map:
Another way of realizing map's superiority is to implement forEach in terms of map. As we are good programmers, we'll won't indulge in namespace pollution. We'll call our forEach, just each.
Array.prototype.each = function (func) {
this.map(func);
};
Now, if you don't like the prototype nonsense, here you go:
var each = function (arr, func) {
arr.map(func); // Or map(arr, func);
};
So, umm.. Why's does forEach even exist?
The answer is efficiency. If you are not interested in transforming an array into another array, why should you compute the transformed array? Only to dump it? Of course not! If you don't want a transformation, you shouldn't do a transformation.
So while map can be used to solve Task 1, it probably shouldn't. For each is the right candidate for that.
Original answer:
While I largely agree with #madlep 's answer, I'd like to point out that map() is a strict super-set of forEach().
Yes, map() is usually used to create a new array. However, it may also be used to change the current array.
Here's an example:
var a = [0, 1, 2, 3, 4], b = null;
b = a.map(function (x) { a[x] = 'What!!'; return x*x; });
console.log(b); // logs [0, 1, 4, 9, 16]
console.log(a); // logs ["What!!", "What!!", "What!!", "What!!", "What!!"]
In the above example, a was conveniently set such that a[i] === i for i < a.length. Even so, it demonstrates the power of map().
Here's the official description of map(). Note that map() may even change the array on which it is called! Hail map().
Hope this helped.
Edited 10-Nov-2015: Added elaboration.

Here is an example in Scala using lists: map returns list, foreach returns nothing.
def map(f: Int ⇒ Int): List[Int]
def foreach(f: Int ⇒ Unit): Unit
So map returns the list resulting from applying the function f to each list element:
scala> val list = List(1, 2, 3)
list: List[Int] = List(1, 2, 3)
scala> list map (x => x * 2)
res0: List[Int] = List(2, 4, 6)
Foreach just applies f to each element:
scala> var sum = 0
sum: Int = 0
scala> list foreach (sum += _)
scala> sum
res2: Int = 6 // res1 is empty

If you're talking about Javascript in particular, the difference is that map is a loop function while forEach is an iterator.
Use map when you want to apply an operation to each member of the list and get the results back as a new list, without affecting the original list.
Use forEach when you want to do something on the basis of each element of the list. You might be adding things to the page, for example. Essentially, it's great for when you want "side effects".
Other differences: forEach returns nothing (since it is really a control flow function), and the passed-in function gets references to the index and the whole list, whereas map returns the new list and only passes in the current element.

ForEach tries to apply a function such as writing to db etc on each element of the RDD without returning anything back.
But the map() applies some function over the elements of rdd and returns the rdd. So when you run the below method it won't fail at line3 but while collecting the rdd after applying foreach it will fail and throw an error which says
File "<stdin>", line 5, in <module>
AttributeError: 'NoneType' object has no attribute 'collect'
nums = sc.parallelize([1,2,3,4,5,6,7,8,9,10])
num2 = nums.map(lambda x: x+2)
print ("num2",num2.collect())
num3 = nums.foreach(lambda x : x*x)
print ("num3",num3.collect())

Related

Check if a list contains any element of another list in Dart

I have an array:
const list1 = [0, 1, 2];
How do I check if other arrays contain any of the target array elements?
For example:
[2, 3] //returns true;
[2, 3, 4] //returns true;
[3, 4] //returns false;
Using list1.indexWhere(list2.contains) should be fine for small lists, but for large lists, the asymptotic runtime complexity would be O(m * n) where m and n are the sizes of the lists.
A different way to pose the problem of checking if a list contains any element of another list is to check if the set-intersection of two lists is non-empty. The direct way to implement that would be:
var contains = list1.toSet().intersection(list2.toSet()).isNotEmpty;
Since the default Set implementation is a LinkedHashSet, lookups would be O(1), and computing the intersection would be linear with respect to one of the Sets. However, converting each List to a Set would take linear time, making the whole operation take O(m + n).
That's asymptotically efficient, but it computes the entire intersection just to determine whether it's empty or not, which is wasteful. You can do a bit better by using .any to stop earlier and noting that .any doesn't benefit from the receiving object being a Set:
var set2 = list2.toSet();
var contains = list1.any(set2.contains);
Note that if you can use Sets in the first place instead of Lists, then the conversion cost would disappear and make the operation O(m).
final contains = list1.indexWhere((e) => list2.contains(e)) > -1
Explanation
indexWhere returns an index of an element where the test function returned true.
contains returns true if the given element is presented in the array.

Dart - When To Use Collection-For-In vs .Map() on Collections

Both the collection-for-in operation and .map() method can return some manipulation of elements from a previous collection. Is there ever any reason to prefer using one over the other?
var myList = [1,2,3];
var alteredList1 = [for(int i in myList) i + 2]; //[3,4,5]
var alteredList2 = myList.map((e) => e + 2).toList(); //[3,4,5]
Use whichever is easier and more readable.
That's a deliberately vague answer, because it depends on what you are doing.
Any time you have something ending in .toList() I'd at least consider making it into a list literal. If the body of the map or where is simple, you can usually rewrite it directly to a list literal using for/in (plus if for where).
And then, sometimes it gets complicated, you need to use the same variable twice, or the map computation uses a while loop, or something else doesn't just fit into the list literal syntax.
Then you can either keep the helper function and do [for (var e in something) helperFunction(e)] or just do something.map((e) { body of helper function }).toList(). In many cases the latter is then more readable.
So, consider using a list literal if your iterable code ends in toList, but if the literal gets too convoluted, don't feel bad about using the .map(...).toList() approach.
Readability is all that really matters.
Not an expert but personally I prefer the first method. Some reasons:
You can include other elements (independent from the for loop) in the same list:
var a = [1, 2, 3];
bool include5 = true;
var b = [
1,
for (var i in a) i + 1,
if (include5) 5,
];
print(b); // [1, 2, 3, 4, 5]
Sometimes when mapping models to a list of Widgets the .map().toList() method will produce a List<dynamic>, implicit casting won't work. When you come across such an error just avoid the second method.

Creating an 'add' computation expression

I'd like the example computation expression and values below to return 6. For some the numbers aren't yielding like I'd expect. What's the step I'm missing to get my result? Thanks!
type AddBuilder() =
let mutable x = 0
member _.Yield i = x <- x + i
member _.Zero() = 0
member _.Return() = x
let add = AddBuilder()
(* Compiler tells me that each of the numbers in add don't do anything
and suggests putting '|> ignore' in front of each *)
let result = add { 1; 2; 3 }
(* Currently the result is 0 *)
printfn "%i should be 6" result
Note: This is just for creating my own computation expression to expand my learning. Seq.sum would be a better approach. I'm open to the idea that this example completely misses the value of computation expressions and is no good for learning.
There is a lot wrong here.
First, let's start with mere mechanics.
In order for the Yield method to be called, the code inside the curly braces must use the yield keyword:
let result = add { yield 1; yield 2; yield 3 }
But now the compiler will complain that you also need a Combine method. See, the semantics of yield is that each of them produces a finished computation, a resulting value. And therefore, if you want to have more than one, you need some way to "glue" them together. This is what the Combine method does.
Since your computation builder doesn't actually produce any results, but instead mutates its internal variable, the ultimate result of the computation should be the value of that internal variable. So that's what Combine needs to return:
member _.Combine(a, b) = x
But now the compiler complains again: you need a Delay method. Delay is not strictly necessary, but it's required in order to mitigate performance pitfalls. When the computation consists of many "parts" (like in the case of multiple yields), it's often the case that some of them should be discarded. In these situation, it would be inefficient to evaluate all of them and then discard some. So the compiler inserts a call to Delay: it receives a function, which, when called, would evaluate a "part" of the computation, and Delay has the opportunity to put this function in some sort of deferred container, so that later Combine can decide which of those containers to discard and which to evaluate.
In your case, however, since the result of the computation doesn't matter (remember: you're not returning any results, you're just mutating the internal variable), Delay can just execute the function it receives to have it produce the side effects (which are - mutating the variable):
member _.Delay(f) = f ()
And now the computation finally compiles, and behold: its result is 6. This result comes from whatever Combine is returning. Try modifying it like this:
member _.Combine(a, b) = "foo"
Now suddenly the result of your computation becomes "foo".
And now, let's move on to semantics.
The above modifications will let your program compile and even produce expected result. However, I think you misunderstood the whole idea of the computation expressions in the first place.
The builder isn't supposed to have any internal state. Instead, its methods are supposed to manipulate complex values of some sort, some methods creating new values, some modifying existing ones. For example, the seq builder1 manipulates sequences. That's the type of values it handles. Different methods create new sequences (Yield) or transform them in some way (e.g. Combine), and the ultimate result is also a sequence.
In your case, it looks like the values that your builder needs to manipulate are numbers. And the ultimate result would also be a number.
So let's look at the methods' semantics.
The Yield method is supposed to create one of those values that you're manipulating. Since your values are numbers, that's what Yield should return:
member _.Yield x = x
The Combine method, as explained above, is supposed to combine two of such values that got created by different parts of the expression. In your case, since you want the ultimate result to be a sum, that's what Combine should do:
member _.Combine(a, b) = a + b
Finally, the Delay method should just execute the provided function. In your case, since your values are numbers, it doesn't make sense to discard any of them:
member _.Delay(f) = f()
And that's it! With these three methods, you can add numbers:
type AddBuilder() =
member _.Yield x = x
member _.Combine(a, b) = a + b
member _.Delay(f) = f ()
let add = AddBuilder()
let result = add { yield 1; yield 2; yield 3 }
I think numbers are not a very good example for learning about computation expressions, because numbers lack the inner structure that computation expressions are supposed to handle. Try instead creating a maybe builder to manipulate Option<'a> values.
Added bonus - there are already implementations you can find online and use for reference.
1 seq is not actually a computation expression. It predates computation expressions and is treated in a special way by the compiler. But good enough for examples and comparisons.

maps,filter,folds and more? Do we really need these in Erlang?

Maps, filters, folds and more : http://learnyousomeerlang.com/higher-order-functions#maps-filters-folds
The more I read ,the more i get confused.
Can any body help simplify these concepts?
I am not able to understand the significance of these concepts.In what use cases will these be needed?
I think it is majorly because of the syntax,diff to find the flow.
The concepts of mapping, filtering and folding prevalent in functional programming actually are simplifications - or stereotypes - of different operations you perform on collections of data. In imperative languages you usually do these operations with loops.
Let's take map for an example. These three loops all take a sequence of elements and return a sequence of squares of the elements:
// C - a lot of bookkeeping
int data[] = {1,2,3,4,5};
int squares_1_to_5[sizeof(data) / sizeof(data[0])];
for (int i = 0; i < sizeof(data) / sizeof(data[0]); ++i)
squares_1_to_5[i] = data[i] * data[i];
// C++11 - less bookkeeping, still not obvious
std::vec<int> data{1,2,3,4,5};
std::vec<int> squares_1_to_5;
for (auto i = begin(data); i < end(data); i++)
squares_1_to_5.push_back((*i) * (*i));
// Python - quite readable, though still not obvious
data = [1,2,3,4,5]
squares_1_to_5 = []
for x in data:
squares_1_to_5.append(x * x)
The property of a map is that it takes a collection of elements and returns the same number of somehow modified elements. No more, no less. Is it obvious at first sight in the above snippets? No, at least not until we read loop bodies. What if there were some ifs inside the loops? Let's take the last example and modify it a bit:
data = [1,2,3,4,5]
squares_1_to_5 = []
for x in data:
if x % 2 == 0:
squares_1_to_5.append(x * x)
This is no longer a map, though it's not obvious before reading the body of the loop. It's not clearly visible that the resulting collection might have less elements (maybe none?) than the input collection.
We filtered the input collection, performing the action only on some elements from the input. This loop is actually a map combined with a filter.
Tackling this in C would be even more noisy due to allocation details (how much space to allocate for the output array?) - the core idea of the operation on data would be drowned in all the bookkeeping.
A fold is the most generic one, where the result doesn't have to contain any of the input elements, but somehow depends on (possibly only some of) them.
Let's rewrite the first Python loop in Erlang:
lists:map(fun (E) -> E * E end, [1,2,3,4,5]).
It's explicit. We see a map, so we know that this call will return a list as long as the input.
And the second one:
lists:map(fun (E) -> E * E end,
lists:filter(fun (E) when E rem 2 == 0 -> true;
(_) -> false end,
[1,2,3,4,5])).
Again, filter will return a list at most as long as the input, map will modify each element in some way.
The latter of the Erlang examples also shows another useful property - the ability to compose maps, filters and folds to express more complicated data transformations. It's not possible with imperative loops.
They are used in almost every application, because they abstract different kinds of iteration over lists.
map is used to transform one list into another. Lets say, you have list of key value tuples and you want just the keys. You could write:
keys([]) -> [];
keys([{Key, _Value} | T]) ->
[Key | keys(T)].
Then you want to have values:
values([]) -> [];
values([{_Key, Value} | T}]) ->
[Value | values(T)].
Or list of only third element of tuple:
third([]) -> [];
third([{_First, _Second, Third} | T]) ->
[Third | third(T)].
Can you see the pattern? The only difference is what you take from the element, so instead of repeating the code, you can simply write what you do for one element and use map.
Third = fun({_First, _Second, Third}) -> Third end,
map(Third, List).
This is much shorter and the shorter your code is, the less bugs it has. Simple as that.
You don't have to think about corner cases (what if the list is empty?) and for experienced developer it is much easier to read.
filter searches lists. You give it function, that takes element, if it returns true, the element will be on the returned list, if it returns false, the element will not be there. For example filter logged in users from list.
foldl and foldr are used, when you have to do additional bookkeeping while iterating over the list - for example summing all the elements or counting something.
The best explanations, I've found about those functions are in books about Lisp: "Structure and Interpretation of Computer Programs" and "On Lisp" Chapter 4..

How can Scala understand function calls in different formats?

I realize the following function calls are all same, but I do not understand why.
val list = List(List(1), List(2, 3), List(4, 5, 6))
list.map(_.length) // res0 = List(1,2,3) result of 1st call
list map(_.length) // res1 = List(1,2,3) result of 2nd call
list map (_.length) // res2 = List(1,2,3) result of 3rd call
I can understand 1st call, which is just a regular function call because map is a member function of class List
But I can not understand 2nd and 3rd call. For example, in the 3rd call, how can Scala compiler know "(_.length)" is parameter of "map"? How can compiler know "map" is a member function of "list"?
The only difference between variant 2 and 3 is the blank in front of the parenthesis? This can only be a delimiter - list a and lista is of course different, but a opening parens is a new token, and you can put a blank or two or three in front - or none. I don't see how you can expect a difference here.
In Java, there is no difference between
System.out.println ("foo");
// and
System.out.println("foo");
too.
This is the operator notation. The reason it works is the same reason why 2 + 2 works.
The space is used to distinguish between words -- listmap(_.length) would make the compiler look for listmap. But if you write list++list, it will work too, as will list ++ list.
So, one you are using operator notation, the space is necessary to separate words, but otherwise may be present or not.

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