values | Takes the best of object and array worlds | REST library

Are you using the @react-native-community/netinfo library? You need to refresh this library if you are using it.

After updating or uninstalling and reinstalling the netinfo library it will work.

You can use the std::nextafter function, which, despite its name, can retrieve the next representable value that is arithmetically before a given starting point, by using an appropriate to argument. (Often -Infinity, 0, or +Infinity).

This works portably by definition of nextafter, regardless of what floating-point format your C++ implementation uses. (Binary vs. decimal, or width of mantissa aka significand, or anything else.)

Example: Retrieving the closest value less than 1 for the double type (on Windows, using the clang-cl compiler in Visual Studio 2019), the answer is different from the result of the 1 - ε calculation (which as discussed in comments, is incorrect for IEEE754 numbers; below any power of 2, representable numbers are twice as close together as above it):

You can use itertools.dropwhile:

From the C18 standard in 6.7.2.2:

Each enumerated type shall be compatible with char, a signed integer type, or an unsigned integer type. The choice of type is implementation-defined, but shall be capable of representing the values of all the members of the enumeration.

So yes enum { a } e = 1; is valid. e is a 'integer' type so it can take the value 1. The fact that 1 is not present as an enumeration value is no issue. The enumeration members only give handy identifiers for some of possible values.

The evaluation order of A = B was not specified before c++17, after c++17 B is guaranteed to be evaluated before A, see https://en.cppreference.com/w/cpp/language/eval_order rule 20.

The behaviour of valMap[val] = valMap.size(); is therefore unspecified in c++14, you should use:

Since C++17 the order of evaluation is specified such that the operands of = are evaluated right-to-left and those of << are evaluated left-to-right, matching the associativity of these operators. (But this doesn't apply to all operators, e.g. + and other arithmetic operators.)

So in

Go to your package.json file and delete as many dependencies as you can until the project builds successfully. Then start adding back the dependencies one by one to detect which ones have troubles.

Then you can manually patch those dependencies by acceding them on node_modules/[dependencie]/android/build.gradle and setting androidx.core:core-ktx: or androidx.core:core: to a specific version (1.6.0 in my case).

It looks like GCC's naïveté about store-forwarding stalls is hurting its auto-vectorization strategy here. See also Store forwarding by example for some practical benchmarks on Intel with hardware performance counters, and What are the costs of failed store-to-load forwarding on x86? Also Agner Fog's x86 optimization guides.

(gcc -O3 enables -ftree-vectorize and a few other options not included by -O2, e.g. if-conversion to branchless cmov, which is another way -O3 can hurt with data patterns GCC didn't expect. By comparison, Clang enables auto-vectorization even at -O2, although some of its optimizations are still only on at -O3.)

It's doing 64-bit loads (and branching to store or not) on pairs of ints. This means, if we swapped the last iteration, this load comes half from that store, half from fresh memory, so we get a store-forwarding stall after every swap. But bubble sort often has long chains of swapping every iteration as an element bubbles far, so this is really bad.

(Bubble sort is bad in general, especially if implemented naively without keeping the previous iteration's second element around in a register. It can be interesting to analyze the asm details of exactly why it sucks, so it is fair enough for wanting to try.)

Anyway, this is pretty clearly an anti-optimization you should report on GCC Bugzilla with the "missed-optimization" keyword. Scalar loads are cheap, and store-forwarding stalls are costly. (Can modern x86 implementations store-forward from more than one prior store? no, nor can microarchitectures other than in-order Atom efficiently load when it partially overlaps with one previous store, and partially from data that has to come from the L1d cache.)

Even better would be to keep buf[x+1] in a register and use it as buf[x] in the next iteration, avoiding a store and load. (Like good hand-written asm bubble sort examples, a few of which exist on Stack Overflow.)

If it wasn't for the store-forwarding stalls (which AFAIK GCC doesn't know about in its cost model), this strategy might be about break-even. SSE 4.1 for a branchless pmind / pmaxd comparator might be interesting, but that would mean always storing and the C source doesn't do that.

If this strategy of double-width load had any merit, it would be better implemented with pure integer on a 64-bit machine like x86-64, where you can operate on just the low 32 bits with garbage (or valuable data) in the upper half. E.g.,

I quickly tried out the solution I proposed in the comments: