bsidhom

#!/usr/bin/env python3

def main():
    print("powerset:")
    for subset in powerset([0, 1, 2, 3]):
        print(subset)
    print()
    print("combinations:")
    for subset in combinations([0, 1, 2, 3, 4, 5], 3):
        print(subset)

bsidhom

#!/usr/bin/env python3

from abc import ABC, abstractmethod
from enum import Enum
from typing import Any, Callable, ForwardRef, Generic, TypeAlias, TypeVar, cast


class RecordSeparator(Enum):
    VALUE = "RecordSeparator"

bsidhom

#!/usr/bin/env python3

import argparse

from typing import Callable, Generator, TypeVar


def main():
    parser = argparse.ArgumentParser(
        "Generates necklace-related sequences using the FKM algorithm as described by \"Combinatorial Generation\" by Frank Ruskey. See https://web.archive.org/web/20221203232527/https%3A%2F%2Fpage.math.tu-berlin.de%2F~felsner%2FSemWS17-18%2FRuskey-Comb-Gen.pdf"

bsidhom

-- To use this, invoke wrk with the lua script option, e.g.:
--  env WRK_OUTPUT_CSV='timing.csv' wrk -s log_data.lua 'http://localhost:8000/'
done = function(summary, latency, requests)
  -- Unfortunately, writing output to stdout is not a good option because it
  -- gets intermingled with other `wrk` output. The maintainer is not amenable
  -- to suppressing this (see -- https://github.com/wg/wrk/issues/245).
  -- Similarly, we cannot write to stdout safely because _actual_ error messages
  -- are also logged there. Instead, we write to a file (or stdout by default,
  -- for human-readability purposes).
  filename = os.getenv("WRK_OUTPUT_CSV")

bsidhom

create table j as select json(column0) as j from read_csv_auto('eventlog.json', delim='\0');
.mode list
.header off
.once 'schema.json'
select json_group_object(event, structure) from (select j->>'Event' as event, json_group_structure(j) as structure from j group by event);

bsidhom

#!/usr/bin/env python3

import asyncio
import json
import sys


async def main():
    reader, writer = await asyncio.open_connection("127.0.0.1", 8888)
    messages = ["One", 2, {"thr": "ee"}, ["4"], [5, 6]]

bsidhom

#!/usr/bin/env python3

import argparse
import asyncio
import codecs
import contextlib
import json
import sys
import threading

bsidhom

let range = (start, end, step) => {
  return {
    *[Symbol.iterator]() {
      for (let n = start; n < end; n += step) {
        yield n;
      }
    },
  };
};

bsidhom

// Taken from https://stackoverflow.com/a/9382383
let decycle;
decycle = (obj, stack = []) => {
  if (!obj || typeof obj !== 'object') {
    return obj;
  }
  if (stack.includes(obj)) {
    return null;
  }
  let s = stack.concat([obj]);

bsidhom

# Usage: jq --stream --null-input --from-file stream_array.jq
#
# Or, as a one-liner:
# jq --stream -n 'def end_array_or_object: length == 1 and (first | length == 1); def outer_primitive: length == 2 and (first | length == 0); def end_element: length > 0 and (last | (end_array_or_object or outer_primitive)); foreach (inputs | del(.[0][0])) as $path ([]; if end_element then [$path] else . + [$path] end; if end_element then fromstream(.[]) else empty end)'

# This is useful for processing large JSON files/indefinite streams of elements
# that happen to be wrapped in an outer array.
# The process is:
# - Stream the path elements (via  `jq --stream`)
# - Remove the leading path element from all entries. This effectively drops the