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*, *::before, *::after { | |
box-sizing: border-box; | |
} | |
* { | |
margin: 0; | |
padding: 0; | |
font: inherit; | |
} |
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div:empty { | |
outline: 2px solid deeppink; | |
height: 1em; | |
} | |
:empty:not(img, picture, button, input) { | |
display: none; | |
} | |
/* https://youtube.com/shorts/zoJkZ7GC1s4?feature=share */ |
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.container { | |
width: min(100% - 2rem, 600px); | |
margin-inline: auto; | |
} | |
/* https://youtube.com/shorts/SGlpOnIgk1w */ |
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import re | |
with open(rootdir + "something in japanese.html", encoding='utf-8', errors='ignore') as reader: | |
for line in reader: | |
words = re.findall(r"[一-龯ぁ-んァ-ン!:/・()ー]*", line) | |
for word in words: | |
if word: | |
print(word) |
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[^@ \t\r\n]+@[^@ \t\r\n]+\.[^@ \t\r\n]+ | |
[^@ \\t\\r\\n] matches for anything other than @, space, tab, new lines repetitions of a non-whitespace character. | |
https://ihateregex.io/expr/email/ (04/17/2022) | |
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(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\]) |
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Regex for matching ALL Japanese common & uncommon Kanji (4e00 – 9fcf) ~ The Big Kahuna! | |
([一-龯]) | |
Regex for matching Hirgana or Katakana | |
([ぁ-んァ-ン]) | |
Regex for matching Non-Hirgana or Non-Katakana | |
([^ぁ-んァ-ン]) | |
Regex for matching Hirgana or Katakana or basic punctuation (、。’) |
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first create a spatial lite db file. the sqlite file will be more than twice as large as the GDB directory. | |
ogr2ogr -f SQlite db.sqlite -f OpenFileGDB -overwrite tlgdb_2019_a_us_areawater.gdb |
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# this is mor than 100 years of global weather data 110GB | |
wget https://www.ncei.noaa.gov/data/global-hourly/archive/csv/{1901..2020}.tar.gz |
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from torch.utils.data import TensorDataset, DataLoader | |
import torch | |
# Check for a GPU | |
train_on_gpu = torch.cuda.is_available() | |
if not train_on_gpu: | |
print('No GPU found. Please use a GPU to train your neural network.') | |
def batch_data(words, sequence_length, batch_size): |
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