sabetAI

import openai
openai.api_key = os.getenv("OPENAI_API_KEY")

openai.Answer.create(
    search_model="cushman-codex", 
    model="davinci-codex", 
    question="Where is the React component FloatingMenu defined?", 
    examples_context='''public shouldShow: Exclude<FloatingMenuPluginProps['shouldShow'], null> = ({ state }) => {
    const { selection } = state
    const { $anchor, empty } = selection

sabetAI

import os
from argparse import ArgumentParser
import openai
import jsonlines

openai.api_key = os.environ['OPENAI_API_KEY']

# read all typescript files in all subdirectories
def get_all_files(dir, ext):
    all_files = []

Skinner927

"""
To use simply copy ClassPropertyMeta and classproperty into your project
"""


class ClassPropertyMeta(type):
    def __setattr__(self, key, value):
        obj = self.__dict__.get(key, None)
        if type(obj) is classproperty:
            return obj.__set__(self, value)

i-am-tom

{-# LANGUAGE DataKinds               #-}
{-# LANGUAGE PolyKinds               #-}
{-# LANGUAGE TypeOperators           #-}
{-# LANGUAGE UndecidableInstances    #-}
{-# LANGUAGE UnsaturatedTypeFamilies #-}

import GHC.TypeLits
import Prelude hiding (Functor, Semigroup)

type Main = (Fizz <> Buzz) <$> (0 `To` 100)

edolstra

Nix Flake MVP

Goals

• To provide Nix repositories with an easy and standard way to reference other Nix repositories.

• To allow such references to be queried and updated automatically.

• To provide a replacement for nix-channel, NIX_PATH and Hydra

teamdandelion

7
2
1
0
4
1
4
9
5
9

dfrib

// For details, see
// http://stackoverflow.com/questions/40261857/remove-nested-key-from-dictionary
import Foundation

extension Dictionary {       
    subscript(keyPath keyPath: String) -> Any? {
        get {
            guard let keyPath = Dictionary.keyPathKeys(forKeyPath: keyPath) 
                else { return nil }
            return getValue(forKeyPath: keyPath)

deoxxa

{
  "Imei": "354678050021708",
  "Timestamp": 1477343460116,
  "Priority": 0,
  "Gps": {
    "Longitude": 1508431968,
    "Latitude": -323215269,
    "Altitude": 135,
    "Angle": 82,
    "Satellites": 8,

garybernhardt

This document has moved!

It's now here, in The Programmer's Compendium. The content is the same as before, but being part of the compendium means that it's actively maintained.

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats