johnathaningle

from enum import IntEnum
import sys
from typing import Any, Dict, List, Optional
import boto3
from boto3.dynamodb.conditions import Key, Attr
from uuid import UUID, uuid4
from datetime import datetime
from decimal import Decimal
import json
from statistics import mean

johnathaningle

import json
from datetime import datetime
from random import randint

if __name__ == "__main__":
    item = {
        "Name": f"Trip: {datetime.now()}",
        "Distance": randint(1, 100),
        "Time": str(datetime.now()),
        "Speed": randint(11, 19)

johnathaningle

import json

#sources:
#https://www.fiaformulae.com/en/results/race-results/?championship=2022019&race=20190208
#https://www.motogp.com/en/Results+Statistics
#https://www.formula1.com/en/results.html/2020/races.html
motorsport_data = {
    "f1": {
        "mercedes": {
            "valtteri bottas": [

johnathaningle

import json
from typing import List, Optional, Tuple

def lambda_handler(event, context):
    message = "Unable to calculate the cube root"
    result = get_cuberoots(event)
    if result is not None:
        message = str(result)
    debug_log(context)
    return {

johnathaningle

from enum import Enum
from typing import Any, List, Optional
import boto3
from datetime import datetime
import random
from botocore.exceptions import ClientError
import logging
import botocore
from uuid import uuid4

johnathaningle

# ##### BEGIN GPL LICENSE BLOCK #####
#
#  This program is free software; you can redistribute it and/or
#  modify it under the terms of the GNU General Public License
#  as published by the Free Software Foundation; either version 2
#  of the License, or (at your option) any later version.
#
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

johnathaningle

name: torch
channels:
  - pytorch
  - defaults
dependencies:
  - _pytorch_select=1.1.0=cpu
  - blas=1.0=mkl
  - ca-certificates=2020.1.1=0
  - certifi=2019.11.28=py36_1
  - cffi=1.14.0=py36h7a1dbc1_0

johnathaningle

import plotly.graph_objs as go
import pandas as pd
import numpy as np

df = pd.read_csv("Real Estate Data YOY .csv")
print(df.head())

i = 0
cols = [col for col in df.columns]
cols =  cols[1:]

johnathaningle

johnathaningle

using SixLabors.ImageSharp;
using SixLabors.ImageSharp.Formats.Jpeg;
using SixLabors.ImageSharp.PixelFormats;
using SixLabors.ImageSharp.Processing;
using System;
using System.IO;

namespace ImageSharpConsole
{
    class Program