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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 |
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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) |
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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": [ |
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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 { |
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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 |
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# ##### 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 |
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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 |
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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:] |
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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 |
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