You can run an Archive Team container on your computer! It'll help crawl the web and putting stuff into archive.org, based on the current projects.
There was a reddit post about installing Arch on NTFS3 partition. Since Windows and Linux doesn't have directories with same names under the /
(C:\
), I thought it's possible, and turned out it was actually possible.
If you are not familiar to Linux, for example you've searched on Google "how to dualboot Linux and Windos" or brbrbr... you mustn't try this. This is not practical.
- UEFI system
- Any Linux live-boot CD/DVD/USB... with Linux kernel newer than 5.15
- Windows installer USB
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Option Explicit | |
Dim objshell,path,DigitalID, Result | |
Set objshell = CreateObject("WScript.Shell") | |
'Set registry key path | |
Path = "HKLM\SOFTWARE\Microsoft\Windows NT\CurrentVersion\" | |
'Registry key value | |
DigitalID = objshell.RegRead(Path & "DigitalProductId") | |
Dim ProductName,ProductID,ProductKey,ProductData |
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""" | |
Reason for publishing this Gist and the use case: | |
In many cases we use functions in libraries that print the variable we want instead of returning it. This Gist shows | |
how to get hold of the printed values from these functions and store in a variable. I found the solution in | |
couple of posts on different forums: | |
* https://stackoverflow.com/questions/1218933/can-i-redirect-the-stdout-in-python-into-some-sort-of-string-buffer | |
* https://wrongsideofmemphis.wordpress.com/2010/03/01/store-standard-output-on-a-variable-in-python/ | |
* https://groups.google.com/forum/#!topic/comp.lang.python/tkK6n1oVKhM | |
* https://bytes.com/topic/python/answers/849106-redirection-standard-output-python-command-python-variable | |
In addition to the trick demonstrated in these posts, I found a case where I would need to store multiple printouts |
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#!/usr/bin/env python2 | |
import requests | |
from tqdm import tqdm | |
import re | |
import os | |
def download_file_from_google_drive(id, destination): | |
URL = 'https://docs.google.com/uc?export=download' | |
session = requests.Session() |
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import numpy as np | |
from sklearn.datasets import load_iris | |
from sklearn.linear_model import LogisticRegression | |
from sklearn.utils import shuffle | |
# get shuffled iris data | |
X, y = load_iris(return_X_y=True) | |
X, y = shuffle(X, y, random_state=0) |
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from collections import Counter | |
import numpy as np | |
from sklearn.metrics import euclidean_distances | |
from pyemd import emd as pyemd | |
def word_movers_distance(a, b, embeddings): | |
"""Word Mover's Distance. | |
A measure of text similarity: earth mover's distance in embedding metric space. |
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