mzaks

fn compare(s1: DTypePointer[DType.uint8], s2: DTypePointer[DType.uint8], count: Int)->Int:
  var result = 0
  var i = 0
  while i < count:
    var s1i = s1[i]
    var s2i = s2[i]
    var smaller = s1i < s2i
    var bigger = s1i > s2i
    i += 1 + count * int(smaller or bigger)
    result = -1 * int(smaller) + 1 * int(bigger)

mzaks

trait Hashable:
    fn __hash__[H: Hasher](self, inout hasher: H):
        ...

trait Hasher:
    fn __init__(inout self):
        ...
    fn update(inout self, bytes: DTypePointer[DType.uint8], n: Int):
        ...
    fn finish[dt: DType = DType.uint64](owned self) -> Scalar[dt]:

mzaks

import matplotlib.pyplot as plt

def _normalized_experience(data: dict[str, list[int | list[int]]]) -> tuple[int, dict[str, list[int]]]:
    """Returns a tuple with latest year and an experience dict with normalised years list"""
    latest_year = 0
    result = {}
    for topic, years in data.items():
        normalised_years = []
        for entry in years:
            if isinstance(entry, list):

mzaks

#!/bin/bash

function check_out_remote_module() (
    rurl="$1"
    shift
    declare -a paths
    declare -a module_names
    for var in "$@" 
    do
        IFS="="

mzaks

from Bit import bit_length
from String import String
from Vector import DynamicVector, UnsafeFixedVector 
from List import VariadicList

struct FibyTree[T: AnyType, cmp: fn(T, T)->Int, to_str: fn(T) -> String]:
    alias Union = 0
    alias Intersection = 1
    alias Difference = 2
    alias SymetricDifference = 3

mzaks

from DType import DType
from Functional import vectorize
from Pointer import DTypePointer
from String import String, ord
from TargetInfo import dtype_simd_width

alias simd_width_u8 = dtype_simd_width[DType.ui8]()

let dna = "CAAGAACCAAGATAACACTCATCGTTTACTTCTTACCCGTGCCAATTCGTATTACAAACGAAACCGTGTGGGCCATGTTCGTTATCCGAGGCCCCTTCAATTACTCGTCACTAGTGACCGTCGCTACTATGCCGTGTCCATGATATTACATCAAGACAATGAGATACGAAACGACAGCTGTTCCTACGCCTCGCGAGGGGTTCTACCCCTGAGCCGTGGGAACAGGCCGTCCGACGATCTTCAAGTGTTAAAGCTAGAAAACTTGATCAGAGAACAGTGACAATCCGGTGCAATTAGGGCGCTTCTAGCAAAGTCTTGACGGTTGACATGCTATTCTACCGGCGCAGGTTGCTTGAATGCGCGGGAGTTTTAAGCTCCTCTGTCACGCCATGCCCCCTGCAGTAGCTCACCAGCAAGAAGTTGGCTTAATATACCTGGTAGGAACGTTTGGTTAAACTTCTTTCCCTCTTCTTATACCGATGACACCTACCAATTACGGTCGGCCCGCCCGTGATCCAAACAGGCCTTAATCTTCCAATAATTCAATATGTGTGTGGCTTACAGGAGTCGAATATTTATAAGTGCATTCCTGCCTTCGCTGTTGCGATTTATAGCATCTTATGGTGGCGCAGGGCAACACTTAAAAGGGAGCCAACATGAGTTTCTAGCGTCAGGCACTGCCCTGAGGTAAAGGAATACCTGTTCGATACTATGAGGCGAGATCGCCCCACCTTAAAACAGAAAGACGGTAACGGTCCCTAGCCATTTCCTTATTGCGTACGAGATTATGGAACGCTT

mzaks

#include <stdio.h>
#include <libc.h>

typedef struct {
    int *marking;
    int *takes;
    int *puts;
    int transition_count;
    int place_count;
} PetriNet;

mzaks

      func barBellNet() -> PetriNet {
        let totoalWeightInGram = Place(name: "tototalWeightInGram")
        let barBellSelected = Place(name: "BarBellSelected")
        let barBellNotSelected = Place(name: "BarBellNotSelected", initNumberOfTokens: 1)
        let barBell10Kg = Place(name: "10KgBarBell", initNumberOfTokens: 1)
        let barBell15Kg = Place(name: "15KgBarBell", initNumberOfTokens: 1)
        let barBell17_5Kg = Place(name: "17.5_KgBarBell", initNumberOfTokens: 1)
        let barBell20Kg = Place(name: "20_KgBarBell", initNumberOfTokens: 1)
        let weight0_5kg = Place(name: "0.5_KgWeight", initNumberOfTokens: 4)
        let weight1kg = Place(name: "1_KgWeight", initNumberOfTokens: 4)

mzaks

      func ticTacToeNet() -> PetriNet {
        let xTurn = Place(name: "xTurn", initNumberOfTokens: 1)
        let oTurn = Place(name: "oTurn")
        let xWin = Place(name: "xWin")
        let oWin = Place(name: "oWin")
        
        let e1 = Place(name: "e1", initNumberOfTokens: 1)
        let e2 = Place(name: "e2", initNumberOfTokens: 1)
        let e3 = Place(name: "e3", initNumberOfTokens: 1)
        let e4 = Place(name: "e4", initNumberOfTokens: 1)

mzaks

1. Motivation
This format is designed to allow users pack data together for random access and with space efficiency in mind.

2. Internal structure
IndexedData (further referenced as idata) can be split up in two general regions: manifest and data.
Manifest region contains information needed to identify the number of elements in data region. 
Plus it contains data neded to extract a signle element out of the data region.
Optionaly it can contain a validation key, which can be used to ensure that the data at hand is in fact idata.
The data region contains all data items linearly concatenaited to each other.