voronaam

#!/usr/bin/env python3

import argparse
import random

LADDER_PLAYERS = 1000
LADDER_GAMES = 1000000
TOURNAMENTS = 20

def win_probability(race1, race2, imbalance, rematch):

voronaam

macro_rules! assert_impls {(
    #[rustc_on_unimplemented(message = $message:expr $(,)?)]
    $T:ty : $($trait:tt)+
) => (const _: () = {
    #[allow(unused)]
    use __poormans_specialization::Fallback as _;
    mod __poormans_specialization {
        pub(super)
        struct Wrapper<T : ?::core::marker::Sized>(T);
    

voronaam

#!/usr/bin/env python3
from Xlib import display
from time import sleep
from os import system

# My screen setup has a vertical display with a large dead zone:
#
#             +----------------+
#             |                |
#    DEAD     |                |

voronaam

package processor

import (
	"fmt"
	"time"

	"github.com/Jeffail/benthos/v3/lib/log"
	"github.com/Jeffail/benthos/v3/lib/metrics"
	"github.com/Jeffail/benthos/v3/lib/processor"
	"github.com/Jeffail/benthos/v3/lib/types"

voronaam

package org.sample;


import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.Mode;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import org.openjdk.jmh.annotations.Param;

voronaam

#!/usr/bin/env python3

"""nhl-rank.py: An utility to rank games by a team in a certain year without revealing the results.
   The data source and its copyright: https://sportsdatabase.com/
"""

__author__ = "Lex Vorona"


import sys, getopt

voronaam

package org.sample;

/**
 * Results:
 * Benchmark                Mode  Cnt  Score    Error  Units
 * MyBenchmark.testChain    avgt  200  0.019 ±  0.001  us/op
 * MyBenchmark.testNoChain  avgt  200  0.019 ±  0.001  us/op
 */

import org.openjdk.jmh.annotations.Benchmark;

voronaam

package org.eclipse.mat.ui.snapshot.actions;

import java.io.BufferedOutputStream;
import java.io.BufferedWriter;
import java.io.DataOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.OutputStreamWriter;
import java.io.PrintWriter;
import java.util.HashSet;

voronaam

package com.test;

import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.TimeUnit;

import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Measurement;

voronaam

/**
 * This is a benchmark to gauge if there is any performance hit into using Option.apply() in Scala.
 * Use JMH to build it: http://blog.vorona.ca/measuring-scala-performance-with-jmh.html
 */

package org.sample

import org.openjdk.jmh.annotations._
import java.util.concurrent.TimeUnit