samolisov

# The solution is based upon this answer:
# https://stackoverflow.com/questions/19050461/cmake-add-target-for-invoking-clang-analyzer
function(add_clang_static_analysis target)
    get_target_property(SRCs ${target} SOURCES)
    add_library(${target}_analyze OBJECT EXCLUDE_FROM_ALL ${SRCs})
    if (MSVC)
        list(APPEND ANALYZER_OPTIONS --analyze)
        list(APPEND ANALYZER_OPTIONS "SHELL:/clang:-Xanalyzer /clang:-analyzer-opt-analyze-headers")
        list(APPEND ANALYZER_OPTIONS "SHELL:/clang:-Xanalyzer /clang:-analyzer-output=html")
        # see output in <build/<file>.plist directories

samolisov

#include <iostream>
#include <map>
#include <string>
#include <sstream>
#include <variant>
#include <vector>

struct JSONValue;
class JSONStringVisitor;
class JSONSerializer;

samolisov

import bisect

# See Cormen et al, chapter 18 B-Trees. The implementation uses the 'bisect' module to implement
# a binary search (O(lg n)) through nodes.

def main():
    def allocme():
        nonlocal blocks
        idx = len(blocks)
        blocks.append(None)

samolisov

import heapq

def main():
    freqmap = {'a':45, 'b':13, 'c':12, 'd':16, 'e':9, 'f':5}
    char_to_code = huffman(freqmap)
    print(char_to_code)
    print(invert_dictionary(char_to_code))
    print()

    # see https://en.wikipedia.org/wiki/Letter_frequency#Relative_frequencies_of_letters_in_other_languages

samolisov

package psamolysov.algo.intro.maxsubarray;

import java.util.LinkedHashMap;
import java.util.Map;

public class LongestLinearSubstringer {

    public static String findLongestKCharSubstring(String str, int k) {
        if (str == null || str.length() < k) {
            return str;

samolisov

#Conditionally import wlstModule only when script is executed with jython
if __name__ == '__main__': 
    from wlstModule import *#@UnusedWildImport

def configureCluster(clusterName, isUnicast):
    cluster = getMBean('/Clusters/' + clusterName)
    if cluster == None:
        print 'Creating cluster ' + clusterName
        cluster = create(clusterName, 'Cluster')