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from collections import Counter
from argparse import ArgumentParser, FileType
from csv import DictReader, DictWriter
from sys import stdout

parser = ArgumentParser()
parser.add_argument("infile", type=FileType("r", encoding="utf-8"))
parser.add_argument("column_name")
parser.add_argument("-o", "--outfile", type=FileType("w", encoding="utf-8"), default=stdout)
args = parser.parse_args()

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import typing


def convert(it, context: str):
    if isinstance(it, dict):
        return typing.TypedDict(
            context,
            {
                k: convert(v, f"{context.capitalize()}{k.capitalize()}")
                for (k, v) in it.items()

c-w

// define the name of the Azure Databricks notebook to run
val notebookToRun = ???

// define some way to generate a sequence of workloads to run
val jobArguments = ???

// define the number of workers per job
val workersPerJob = ???

import java.util.concurrent.Executors

c-w

#!/usr/bin/env sh
# This docker-entrypoint populates environment variables from docker secrets.
# The docker secrets are assumed to be files in dotenv syntax. The requested
# secrets should be declared in the environment variable DOTENV_SECRETS, with
# multiple secret names separated by a semi-colon.

if [ ! -d /run/secrets ]; then
  exec "$@"
fi

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#!/usr/bin/env python


import re


ARQ_COL = '|'
ARQ_HLINE = '-'
ARQ_HHLINE = '='