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| import matplotlib.pyplot as plt | |
| import torch | |
| from pathlib import Path | |
| import torchvision | |
| import torchvision.transforms as transforms | |
| from loguru import logger | |
| from torch import nn | |
| import click | |
emptymalei
/ gist:01f655987b987ff82253d388234f1781
Created
February 25, 2021 09:06
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| from itertools import combinations | |
| class Graph(object): | |
| """A graph object | |
| """ | |
| def __init__(self, source_nodes, target_nodes, weights=None): | |
| if not isinstance(source_nodes, list): |
emptymalei
/ Dockerfile
Last active
January 21, 2021 16:44
preload data into redis using python script
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| # This is an experiment | |
| # It is not working | |
| FROM redis:4.0.2-alpine | |
| RUN apk add --no-cache python3 py3-pip | |
| RUN pip3 install click | |
| RUN pip3 install redis | |
| RUN mkdir app | |
| COPY . /app |
emptymalei
/ app.py
Last active
January 21, 2021 12:26
demonstrate how fastapi and aiohttp can work together to make the API faster
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| # This script is based on the article: | |
| # https://dev.to/fuadrafid/fastapi-the-good-the-bad-and-the-ugly-20ob | |
| # The task is to gather three subreddit top articles and show them as the return | |
| # If we do this in squential code, this will be much slows than the gather method used here. | |
| from fastapi import FastAPI | |
| import json | |
| import asyncio | |
| import time | |
| import aiohttp |
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| datetime,AT,BE,BG,CY,CZ,DE,DK,EE,ES,FI,FR,GB,GR,HR,HU,IE,IS,IT,LI,LT,LU,LV,MT,NL,NO,PL,PT,RO,SE,SI,SK,Total | |
| 2020-03-20,550.0,309.0,13.0,0.0,172.0,5940.0,36.0,9.0,3431.0,31.0,1861.0,647.0,46.0,23.0,12.0,191.0,80.0,5322.0,0.0,15.0,135.0,15.0,5.0,409.0,129.0,68.0,143.0,17.0,122.0,33.0,16.0,19780.0 | |
| 2020-03-21,453.0,462.0,22.0,9.0,210.0,4185.0,104.0,16.0,2833.0,50.0,1617.0,706.0,31.0,22.0,0.0,126.0,79.0,5986.0,9.0,21.0,139.0,25.0,11.0,534.0,190.0,70.0,235.0,31.0,200.0,22.0,14.0,18412.0 | |
| 2020-03-22,375.0,558.0,36.0,17.0,91.0,3140.0,71.0,23.0,4946.0,71.0,1847.0,1035.0,35.0,80.0,46.0,102.0,64.0,6557.0,2.0,36.0,186.0,13.0,9.0,637.0,184.0,111.0,260.0,59.0,123.0,42.0,41.0,20797.0 | |
| 2020-03-23,607.0,586.0,22.0,11.0,170.0,3311.0,69.0,20.0,3646.0,105.0,1559.0,665.0,94.0,29.0,36.0,121.0,95.0,5560.0,10.0,38.0,128.0,15.0,17.0,573.0,206.0,98.0,320.0,66.0,160.0,31.0,7.0,18375.0 | |
| 2020-03-24,855.0,342.0,16.0,21.0,71.0,4438.0,65.0,26.0,4517.0,74.0,3838.0,967.0,71.0,71.0,20.0,219.0,20.0,4789.0,0.0,36.0,77.0,41.0,17.0,545.0,239.0,115.0, |
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| l = """[{type:c,generated:b,id:"Apps:5ced8eb5-a5e3-4150-9ef6-0caf285caed6",typename:a},{type:c,generated:b,id:"Apps:c8ef7e1c-0c91-4030-a71d-8cdc86c367ed",typename:a},{type:c,generated:b,id:"Apps:91339570-731c-45b1-a6f3-4aa93a7e8af0",typename:a},{type:c,generated:b,id:"Apps:266a1a88-b462-4db2-8782-2e9f0980afda",typename:a},{type:c,generated:b,id:"Apps:68324672-4f6a-46d4-9866-4a29e4780d4f",typename:a},{type:c,generated:b,id:"Apps:3eee0834-b7d9-4c9d-b3c0-9eb06aad9efd",typename:a},{type:c,generated:b,id:"Apps:687f039a-8f7a-4ec3-8b21-ea9f7518bc71",typename:a},{type:c,generated:b,id:"Apps:015ceb04-f38c-4746-bb6b-4b149b7b022a",typename:a},{type:c,generated:b,id:"Apps:13a8c28b-dc85-4211-be0d-c02d5ab29933",typename:a},{type:c,generated:b,id:"Apps:9d5bcd49-9621-456b-9ab0-20c519ebc4c6",typename:a},{type:c,generated:b,id:"Apps:f6a5ebd6-7712-41ba-b8fd-d4d8efa840a0",typename:a},{type:c,generated:b,id:"Apps:bc9c079b-daf6-489c-b1c6-0ccb93e0bf80",typename:a},{type:c,generated:b,id:"Apps:941605ec-ef02-4b52-b8d6-3cb792be2b9d",t |
emptymalei
/ gist:da71c02797e8db6e32cd5c206a129d90
Created
April 2, 2020 10:40
Germany Phrase of the day
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| in der tat! |
emptymalei
/ machine.js
Last active
March 4, 2020 12:53
Generated by XState Viz: https://xstate.js.org/viz
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| // Available variables: | |
| // - Machine | |
| // - interpret | |
| // - assign | |
| // - send | |
| // - sendParent | |
| // - spawn | |
| // - raise | |
| // - actions |
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| lat lon state population | |
| 48.53798784334733 9.049518423658956 Baden-Württemberg 10075500 | |
| 48.94917269695629 11.418027577497131 Bayern 12542000 | |
| 52.95 13.2 Brandenburg 2500000 | |
| 52.502299698009296 13.402948501480669 Berlin 3469000 | |
| 52.765431393186596 9.161108235507873 Niedersachsen 7914000 | |
| 53.54610462404504 10.024470557873288 Hamburg 1788000 | |
| 50.60321670836851 9.028805533680368 Hessen 6066000 | |
| 53.7535394556047 12.549970296944396 Mecklenburg-Vorpommern 1639000 | |
| 53.19920119721645 8.74885429375113 Bremen 661000 |
emptymalei
/ postal-codes.json
Created
February 27, 2020 12:42
— forked from matthewbednarski/postal-codes.json
Global postal codes regex formats
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| [{ "Note": "The first two digits (ranging from 10–43) correspond to the province, while the last two digits correspond either to the city/delivery zone (range 01–50) or to the district/delivery zone (range 51–99). Afghanistan Postal code lookup", "Country": "Afghanistan", "ISO": "AF", "Format": "NNNN", "Regex": "^\\d{4}$" }, { "Note": "With Finland, first two numbers are 22.", "Country": "Åland Islands", "ISO": "AX", "Format": "NNNNN", "Regex": "^\\d{5}$" }, { "Note": "Introduced in 2006, gradually implemented throughout 2007.", "Country": "Albania", "ISO": "AL", "Format": "NNNN", "Regex": "^\\d{4}$" }, { "Note": "First two as in ISO 3166-2:DZ", "Country": "Algeria", "ISO": "DZ", "Format": "NNNNN", "Regex": "^\\d{5}$" }, { "Note": "U.S. ZIP codes (range 96799)", "Country": "American Samoa", "ISO": "AS", "Format": "NNNNN (optionally NNNNN-NNNN or NNNNN-NNNNNN)", "Regex": "^\\d{5}(-{1}\\d{4,6})$" }, { "Note": |