I understand that question sounds weird, so here is a bit of context.
Recently I was disappointed to learn that map reduce in C++20 ranges does not work as one would expect i.e.
const double val = data | transform(...) | accumulate (...);
does not work, you must write it this unnatural way:
const double val = accumulate(data | transform(...));
Details can be found here and here, but it boils down to the fact that accumulate can not disambiguate between 2 different usecases.
So this got me thinking:
If C++20 required that you must use pipe for using ranges, aka you can not write
vector<int> v;
sort(v);
but you must write
vector<int> v
v|sort();
would that would solve problem of ambiguity?
And if so although unnatural to people using std::sort and other STL algorithms I wonder if in the long run that would be a better design choice.
Note:
If this question is too vague feel free to vote to close, but I feel that this is a legitimate design question that can be answered in relatively unbiased way, especially if my understanding of the problem is wrong.
You need to differentiate between range algorithms and range adaptors. Algorithms are functions that perform a generic operation on a range of values. Adaptors are functions which create range views that modify the presentation of a range. Adaptors are chained by the | operator; algorithms are just regular functions.
Sometimes, the same conceptual thing can have an algorithm and adapter form. transform exists as both an algorithm and an adapter. The former stores the transformation into an output range; the latter creates a view range of the input that lazily computes the transformation as requested.
These are different tasks for different needs and uses.
Also, note that there is no sort adapter in C++20. A sort adapter would have to create a view range that somehow mixed around the elements in the source range. It would have to allocate storage for the new sequence of values (even if it's just sorting iterators/pointers/indices to the values). And the sorting would have to be done at construction time, so there would be no lazy operation taking place.
This is also why accumulate doesn't work that way. It's not a matter of "ambiguity"; it's a matter of the fundamental nature of the operation. Accumulation computes a value from a range; it does not compute a new range from an existing one. That's the work of an algorithm, not an adapter.
Some tasks are useful in algorithm form. Some tasks are useful in adapter form (you find very few zip-like algorithms). Some tasks are useful in both. But because these are two separate concepts for different purposes, they have different ways of invoking them.
would that would solve problem of ambiguity?
Yes.
If there's only one way to write something, that one way must be the only possible interpretation. If an algorithm "call" can only ever be a partial call to the algorithm that must be completed with a | operation with a range on the left hand side, then you'd never even have the question of if the algorithm call is partial or total. It's just always partial.
No ambiguity in that sense.
But if you went that route though, you end up with things like:
auto sum = accumulate("hello"s);
Which doesn't actually sum the chars in that string and actually is placeholder that is waiting on a range to accumulate over with the initial value "hello"s.
I'm trying to create a general memoizator for multiple and arbitrary functions.
For each function std::function<ReturnType(Args...)> that we want to memoize, we unordered_map<Args ..., ReturnType> (I'm keeping things simple on purpose).
The big problem comes when our memoized function has some really big argument Args ...: for example let suppose that our function sort a vector of 10 millions numbers and then returns the sorted vector, so something like std::function<vector<double>(vector<double>)>.
As you can imagine, after having inserted less than 100 vectors, we have already filled 8 GBS of memory. Notice that maybe this is given from the combination of huge vectors and the memory required by the sorting algorithm (I didn't investigate on the causes).
So what about if instead of the structure described above, we define unordered_map<UUID(Args ...), ReturnType> (where UUID= Universally Unique Identifier)? We should relax the deterministic feature (so maybe we return a wrong error), but with a very low probability.
The problem is that since I never used UUIDs, I don't know if there are suitable implementations for this application.
So my question is:
There exists a better solution than UUIDs for this problem?
Which UUID implementation is better suitable for this problem?
boost uuid is a possible candidate?
Unfortunately, the problem could be solved for Args ... but not for ReturnType, so there is a solution for memoized result?
Notice that the UUIDs generated for the object x should be the same even in different runs and machines.
Notice that if we have the same UUID for two different objects (and so we return the wrong value) with a really low probability, then it could be acceptable...let's say that this could be a "probabilistic memoizator".
I know that this application doesn't make sense in a memoization context (what are the odds that an user asks two times to sort the same 10 millions elements vector?), but it's time and memory expensive (so good for benchmarking and to introduce the memory problem that I stated above), so please don't whip and crucify me because this is an absurd memoization application.
Identifying any object is easy. The address is "object identity" in C++. This is also the reason that even empty classes cannot have zero size.
Now, what you want is value equivalence. That's strictly not in the language domain. It's solidly in the application/library logic domain.
You should consider using something like boost::flyweights. It has precisely this facility, and makes it "easy" to customize the equivalence semantics for your types.
I'm working a bit with typelists defined in Alexandrescu's Modern C++ Design.
In his books, he talks about Appending a type to a typelist, but he doesn't talk about splicing two typelists...
I guess it is possible to splice two typelists using the Append functionnality, but wouldn't it result in a linear-time splicing (whereas std::list::splice is O(1) ). ?
Well, i know that this computation time can be considered as "free" as it is compile-time, but I am curious :)
Thanks !
The typelist concept is usually* closer to the Computer Science notion of a list than the (doubly) linked list that std::list is. The two ideas share a name but have crucial differences.
Since metaprograms are purely functional you can't modify in-place an input typelist the way std::list::splice does: you have to 'generate' the output typelist(s), which would be linear. (Laziness can be used to defer and reduce that cost however; the exact cost paid would then depend on the final algorithm.)
*: I said usually because the Boost.MPL supports things like iterators and views which blurs the line, at least from the user point-of-view.
(For the sake of the argument assume that by "CS" list here I meant the cons cell + the empty list.)
I was browsing the SGI STL documentation and ran into project1st<Arg1, Arg2>. I understand its definition, but I am having a hard time imagining a practical usage.
Have you ever used project1st or can you imagine a scenario?
A variant of project1st (taking a std::pair, and returning .first) is quite useful. You can use it in combination with std::transform to copy the keys from a std::map<K,V> to a std::vector<K>. Similarly, a variant of project2nd can be used to copy the values from a map to a vector<V>.
As it happens, none of the standard algorithms really benefits from project1st. The closest is partial_sum(project1st), which would set all output elements to the first input element. It mainly exists because the STL is heavily founded in mathematical set theory, and there operations like project1st are basic building blocks.
My guess is that if you were using the strategy pattern and had a situation where you needed to pass an identity object, this would be a good choice. For example, there might be a case where an algorithm takes several such objects, and perhaps it is possible that you want one of them to do nothing under some situation.
Parallel programming. Imagine a situation where two processes come up with two valid but different results for a given computation, and you need to force them to be the same. project1st/2nd provides a very convenient way to perform this operation on a whole container, using an appropriate parallel call that takes a functor as an argument.
I assume that someone had a practical use for it, or it wouldn't have been written, but I'm drawing a blank on what it might have been. Presumably its use-case is similar to the identity function that the description mentions, where there's no real need for processing but the syntax requires a functor anyway.
The example on that same page suggests using it with the two-container form of std::transform, but if I'm not mistaken, the way they're using it is functionally identical to std::copy, so I don't see the point.
It looks like a solution in search of a problem to me.
I seem to be seeing more 'for' loops over iterators in questions & answers here than I do for_each(), transform(), and the like. Scott Meyers suggests that stl algorithms are preferred, or at least he did in 2001. Of course, using them often means moving the loop body into a function or function object. Some may feel this is an unacceptable complication, while others may feel it better breaks down the problem.
So... should STL algorithms be preferred over hand-rolled loops?
It depends on:
Whether high-performance is required
The readability of the loop
Whether the algorithm is complex
If the loop isn't the bottleneck, and the algorithm is simple (like for_each), then for the current C++ standard, I'd prefer a hand-rolled loop for readability. (Locality of logic is key.)
However, now that C++0x/C++11 is supported by some major compilers, I'd say use STL algorithms because they now allow lambda expressions — and thus the locality of the logic.
I’m going to go against the grain here and advocate that using STL algorithms with functors makes code much easier to understand and maintain, but you have to do it right. You have to pay more attention to readability and clearity. Particularly, you have to get the naming right. But when you do, you can end up with cleaner, clearer code, and paradigm shift into more powerful coding techniques.
Let’s take an example. Here we have a group of children, and we want to set their “Foo Count” to some value. The standard for-loop, iterator approach is:
for (vector<Child>::iterator iter = children.begin();
iter != children.end();
++iter)
{
iter->setFooCount(n);
}
Which, yeah, it’s pretty clear, and definitely not bad code. You can figure it out with just a little bit of looking at it. But look at what we can do with an appropriate functor:
for_each(children.begin(), children.end(), SetFooCount(n));
Wow, that says exactly what we need. You don’t have to figure it out; you immediately know that it’s setting the “Foo Count” of every child. (It would be even clearer if we didn’t need the .begin() / .end() nonsense, but you can’t have everything, and they didn’t consult me when making the STL.)
Granted, you do need to define this magical functor, SetFooCount, but its definition is pretty boilerplate:
class SetFooCount
{
public:
SetFooCount(int n) : fooCount(n) {}
void operator () (Child& child)
{
child.setFooCount(fooCount);
}
private:
int fooCount;
};
In total it’s more code, and you have to look at another place to find out exactly what SetFooCount is doing. But because we named it well, 99% of the time we don’t have to look at the code for SetFooCount. We assume it does what it says, and we only have to look at the for_each line.
What I really like is that using the algorithms leads to a paradigm shift. Instead of thinking of a list as a collection of objects, and doing things to every element of the list, you think of the list as a first class entity, and you operate directly on the list itself. The for-loop iterates through the list, calling a member function on each element to set the Foo Count. Instead, I am doing one command, which sets the Foo Count of every element in the list. It’s subtle, but when you look at the forest instead of the trees, you gain more power.
So with a little thought and careful naming, we can use the STL algorithms to make cleaner, clearer code, and start thinking on a less granular level.
The std::foreach is the kind of code that made me curse the STL, years ago.
I cannot say if it's better, but I like more to have the code of my loop under the loop preamble. For me, it is a strong requirement. And the std::foreach construct won't allow me that (strangely enough, the foreach versions of Java or C# are cool, as far as I am concerned... So I guess it confirms that for me the locality of the loop body is very very important).
So I'll use the foreach only if there is only already a readable/understandable algorithm usable with it. If not, no, I won't. But this is a matter of taste, I guess, as I should perhaps try harder to understand and learn to parse all this thing...
Note that the people at boost apparently felt somewhat the same way, for they wrote BOOST_FOREACH:
#include <string>
#include <iostream>
#include <boost/foreach.hpp>
int main()
{
std::string hello( "Hello, world!" );
BOOST_FOREACH( char ch, hello )
{
std::cout << ch;
}
return 0;
}
See : http://www.boost.org/doc/libs/1_35_0/doc/html/foreach.html
That's really the one thing that Scott Meyers got wrong.
If there is an actual algorithm that matches what you need to do, then of course use the algorithm.
But if all you need to do is loop through a collection and do something to each item, just do the normal loop instead of trying to separate code out into a different functor, that just ends up dicing code up into bits without any real gain.
There are some other options like boost::bind or boost::lambda, but those are really complex template metaprogramming things, they do not work very well with debugging and stepping through the code so they should generally be avoided.
As others have mentioned, this will all change when lambda expressions become a first class citizen.
The for loop is imperative, the algorithms are declarative. When you write std::max_element, it’s obvious what you need, when you use a loop to achieve the same, it’s not necessarily so.
Algorithms also can have a slight performance edge. For example, when traversing an std::deque, a specialized algorithm can avoid checking redundantly whether a given increment moves the pointer over a chunk boundary.
However, complicated functor expressions quickly render algorithm invocations unreadable. If an explicit loop is more readable, use it. If an algorithm call can be expressed without ten-storey bind expressions, by all means prefer it. Readability is more important than performance here, because this kind of optimization is what Knuth so famously attributes to Hoare; you’ll be able to use another construct without trouble once you realize it’s a bottleneck.
It depends, if the algorithm doesn't take a functor, then always use the std algorithm version. It's both simpler for you to write and clearer.
For algorithms that take functors, generally no, until C++0x lambdas can be used. If the functor is small and the algorithm is complex (most aren't) then it may be better to still use the std algorithm.
I'm a big fan of the STL algorithms in principal but in practice it's just way too cumbersome. By the time you define your functor/predicate classes a two line for loop can turn into 40+ lines of code that is suddenly 10x harder to figure out.
Thankfully, things are going to get a ton easier in C++0x with lambda functions, auto and new for syntax. Checkout this C++0x Overview on Wikipedia.
I wouldn't use a hard and fast rule for it. There are many factors to consider, like often you perform that certain operation in your code, is just a loop or an "actual" algorithm, does the algorithm depend on a lot of context that you would have to transmit to your function?
For example I wouldn't put something like
for (int i = 0; i < some_vector.size(); i++)
if (some_vector[i] == NULL) some_other_vector[i]++;
into an algorithm because it would result in a lot more code percentage wise and I would have to deal with getting some_other_vector known to the algorithm somehow.
There are a lot of other examples where using STL algorithms makes a lot of sense, but you need to decide on a case by case basis.
I think the STL algorithm interface is sub-optimal and should be avoided because using the STL toolkit directly (for algorithms) might give a very small gain in performance, but will definitely cost readability, maintainability, and even a bit of writeability when you're learning how to use the tools.
How much more efficient is a standard for loop over a vector:
int weighted_sum = 0;
for (int i = 0; i < a_vector.size(); ++i) {
weighted_sum += (i + 1) * a_vector[i]; // Just writing something a little nontrivial.
}
than using a for_each construction, or trying to fit this into a call to accumulate?
You could argue that the iteration process is less efficient, but a for _ each also introduces a function call at each step (which might be mitigated by trying to inline the function, but remember that "inline" is only a suggestion to the compiler - it may ignore it).
In any case, the difference is small. In my experience, over 90% of the code you write is not performance critical, but is coder-time critical. By keeping your STL loop all literally inline, it is very readable. There is less indirection to trip over, for yourself or future maintainers. If it's in your style guide, then you're saving some learning time for your coders (admit it, learning to properly use the STL the first time involves a few gotcha moments). This last bit is what I mean by a cost in writeability.
Of course there are some special cases -- for example, you might actually want that for_each function separated to re-use in several other places. Or, it might be one of those few highly performance-critical sections. But these are special cases -- exceptions rather than the rule.
IMO, a lot of standard library algorithms like std::for_each should be avoided - mainly for the lack-of-lambda issues mentioned by others, but also because there's such a thing as inappropriate hiding of details.
Of course hiding details away in functions and classes is all part of abstraction, and in general a library abstraction is better than reinventing the wheel. But a key skill with abstraction is knowing when to do it - and when not to do it. Excessive abstraction can damage readability, maintainability etc. Good judgement comes with experience, not from inflexible rules - though you must learn the rules before you learn to break them, of course.
OTOH, it's worth considering the fact that a lot of programmers have been using C++ (and before that, C, Pascal etc) for a long time. Old habits die hard, and there is this thing called cognitive dissonance which often leads to excuses and rationalisations. Don't jump to conclusions, though - it's at least as likely that the standards guys are guilty of post-decisional dissonance.
I think a big factor is the developer's comfort level.
It's probably true that using transform or for_each is the right thing to do, but it's not any more efficient, and handwritten loops aren't inherently dangerous. If it would take half an hour for a developer to write a simple loop, versus half a day to get the syntax for transform or for_each right, and move the provided code into a function or function object. And then other developers would need to know what was going on.
A new developer would probably be best served by learning to use transform and for_each rather than handmade loops, since he would be able to use them consistently without error. For the rest of us for whom writing loops is second nature, it's probably best to stick with what we know, and get more familiar with the algorithms in our spare time.
Put it this way -- if I told my boss I had spent the day converting handmade loops into for_each and transform calls, I doubt he'd be very pleased.