ktmud

import {
  chakra,
  keyframes,
  CSSObject,
  ChakraProps,
  useToken,
} from '@chakra-ui/react';

export type FlashingDotsProps = Pick<ChakraProps, 'width' | 'height'> & {
  /**

ktmud

import pkgutil

from aiohttp import web

ALLOWED_METHODS = ["GET", "POST"]

def load_route_handlers(path, mod):
    routes = []
    for method in ALLOWED_METHODS:
        if hasattr(mod, method):

ktmud

import os

from .app import start_cli_service


env = (os.environ.get("env") or "prod").lower()
is_dev = env == "dev" or env == "local"
port, autoreload_observer = start_cli_service(autoreload=is_dev)
if autoreload_observer:
    # move autoreload observer to the foreground so process won't exit

ktmud

import sqlalchemy as sa
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()


class Model(Base):
    __tablename__ = "model"
    id = sa.Column("id", primary_key=True)
    bbb = sa.Column("bbb")

ktmud

export type FlashingDotsProps = {
  /**
   * Size of each dot
   */
  dotSize?: number;
  /**
   * Animation duration.
   */
  duration?: number;
  /**

ktmud

def remove_duplicates(
    items: Iterable[InputType], key: Optional[Callable[[InputType], Any]] = None
) -> List[InputType]:
    """Remove duplicate items in an iterable."""
    if not key:
        return list(dict.fromkeys(items).keys())
    seen = set()
    result = []
    for item in items:
        item_key = key(item)

ktmud

#!/usr/bin/env python3
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0

ktmud

import {
  ReactNode,
  HTMLAttributes,
  CSSProperties,
  HTMLProps,
  MutableRefObject,
  FunctionComponent,
} from 'react';

declare module 'react-syntax-highlighter' {

ktmud

from enum import Enum, IntEnum
from typing import Any, Dict, Optional

from flask import jsonify
from flask_babel import gettext as _, ngettext
from superset.typing import FlaskResponse


class SupersetErrorCode(IntEnum):
    # Generic Superset errors

ktmud

Easy parallel python with concurrent.futures

As of version 3.3, python includes the very promising concurrent.futures module, with elegant context managers for running tasks concurrently. Thanks to the simple and consistent interface you can use both threads and processes with minimal effort.

For most CPU bound tasks - anything that is heavy number crunching - you want your program to use all the CPUs in your PC. The simplest way to get a CPU bound task to run in parallel is to use the ProcessPoolExecutor, which will create enough sub-processes to keep all your CPUs busy.

We use the context manager thusly:

with concurrent.futures.ProcessPoolExecutor() as executor: