First, as a true C++ developer, I installed Ubuntu 18.04 and compiled omnicore from sources, but after that I realized that Windows omnicore-0.9.0 client can be downloaded and run directly on my Windows 10 machine.
I found omnicore-qt.exe in the unpacked files and run it:
In my app I display prices that I receive from Binance STORJ/BTC trade stream (green color):
At 10/20/2020:
And std::vector is not constexpr yet:
And there is no text formatting also.
Coroutines:
std::chrono::days:
It is possible to do this in QML:
Item
{
property var refreshChart: function () {}
Component.onCompleted:
{
refreshChart = function ()
{
console.log("Hello!")
}
}
}
Getting All Isolated Margin Symbols in PHP:
$api_key = "*****";
$secret = "*****";
$opt = [
"http" => [
"method" => "GET",
"header" => "User-Agent: Mozilla/4.0 (compatible; PHP Binance API)\r\nX-MBX-APIKEY: {$api_key}\r\n"
]
];
$context = stream_context_create($opt);
$params['timestamp'] = number_format(microtime(true)*1000,0,'.','');
$query = http_build_query($params, '', '&');
$signature = hash_hmac('sha256', $query, $secret);
$endpoint = "https://api.binance.com/sapi/v1/margin/isolated/allPairs?{$query}&signature={$signature}";
$res = file_get_contents($endpoint, false, $context);
echo $res;
Consider the declaration of a class that contains a lambda function or a reference to it:
#include <utility>
template <class Func>
struct Holder
{
Holder(Func && func) : m_func(std::forward<Func>(func))
{
}
Func m_func;
};
template <class Func>
auto MakeHolder(Func && func)
{
return Holder<Func>(std::forward<Func>(func));
}
There is a new Seller information option in Google AdMob that may affect the advertising revenue. I set it up in Google AdMob Console on Settings page as follows:
See some link about this.
Hi guys!
For those how are interested in what I am doing now I provided my app screenshots with ‘Find Peaks’ button that runs ZScore algorithm on a cryptocurrency market data (follow the this link for the algorithm source code in C++).
Honestly I am not quite enough understand yet how it works, because I run it first time today, but at least there is some correlation between input parameters and the results. The lesser the threshold and the longer the lag the lesser peaks are found. Increasing the influence also reduces the peak count.
I succeeded with building my app for iOS and my first step in publishing the app in App Store was opening generated .xcodeproj file in XCode, but XCode froze displaying rotating progress indicator and wait cursor.
