pedrovhb

import inspect
from typing import Dict, Any

import snoop

snoop.install(columns=())


class _SnoopMeta(type):
    def __new__(mcs, name: str, bases: tuple, dct: Dict[str, Any]) -> Any:

pedrovhb

{ pkgs, stdenv, lib, fetchFromGitHub, fetchpatch

, cmake, pkgconfig

, exiv2, mpv, opencv4
# , qtbase
# , qtimageformats
# , qtsvg
}:
# { pkgs ? import <nixpkgs> { } }:

pedrovhb

import json
import os

import httpx
import typing
from httpx import AsyncClient
import tiktoken

API_BASE_URL = "https://api.openai.com"
OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]

pedrovhb

#! /usr/bin/env python

import re
import subprocess
import textwrap

RE_LOGITECH_ID = rb"Logitech MX Ergo[\s\-\w]+id=(\d+).*pointer"


def set_ergo_scroll() -> None:

pedrovhb

from __future__ import annotations
from dataclasses import dataclass
from typing import Tuple, List, Union
import cairo
from abc import ABC, abstractmethod

@dataclass
class HasPosition(ABC):
    x: float
    y: float

pedrovhb

#!/usr/bin/env nix-shell
#! nix-shell -i bash -p ffmpeg slop

set -e

output_file="$HOME/Videos/recording_$(date +%Y_%m_%d__%H_%M_%S).mp4"
qp=23

usage() {
  echo "Usage: $(basename $0) [OPTIONS]"

pedrovhb

Hallucinate code responses

Your task is to simulate an interpreter for the Python programming language. You should do your best to provide meaningful responses to each prompt, but you will not actually execute code or access the internet in doing so. You should infer what the result of a function is meant to be even if the function has not been defined. To do so, you should take into account the name of the function and, if provided, its docstring, parameter names, type annotations, and partial implementation. The response to the prompt should be formatted as if transformed into a string by the repr method - for instance, a return value of type dict would look like {"foo": "bar"}, and a float would look like 3.14. If a meaningful value cannot be produced, you should respond with NoMeaningfulValue(<explanation>). You should output only the return value, and include no additional explanation in natural language.

Here are some example prompts, and acceptable responses:

Prompt: sound_of("

pedrovhb

from __future__ import annotations
import asyncio
from asyncio import Queue
from typing import NamedTuple, AsyncIterable, AsyncIterator, Any, Callable

import dearpygui.dearpygui as dpg
from loguru import logger


class ButtonEvent(NamedTuple):

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pedrovhb

import asyncio
import random
import math
import time
from collections import deque
from datetime import datetime
from queue import Queue
from typing import AsyncIterator, Iterable, Any, Coroutine

from astream.closeable_queue import CloseableQueue