makoc

def decode(msg):
    text = []
    for i in range(0, len(msg), 2):
        text.append(unrot(msg[i: i + 2]))
    return str.join('', text)


def unrot(pair, key=ord('x')):
    offset = 0
    for c in 'cdefgh':

makoc

Generating Authy passwords on other authenticators

---

There is an increasing count of applications which use Authy for two-factor authentication. However many users who aren't using Authy, have their own authenticator setup up already and do not wish to use two applications for generating passwords.

Since I use 1Password for all of my password storing/generating needs, I was looking for a solution to use Authy passwords on that. I couldn't find any completely working solutions, however I stumbled upon a gist by Brian Hartvigsen. His post had a neat code with it to generate QR codes for you to use on your favorite authenticator.

His method is to extract the secret keys using Authy's Google Chrome app via Developer Tools. If this was not possible, I guess people would be reverse engineering the Android app or something like that. But when I tried that code, nothing appeared on the screen. My guess is that Brian used the

makoc

# conda install h5py pytables

__import__('tables')  # <-- import PyTables; __import__ so that linters don't complain
import h5py

# now h5py "supports" blosc

def blosc_opts(complevel=9, complib='blosc:lz4', shuffle=True):
    shuffle = 2 if shuffle == 'bit' else 1 if shuffle else 0
    compressors = ['blosclz', 'lz4', 'lz4hc', 'snappy', 'zlib', 'zstd']

makoc

import numpy as np
from numpy import asarray, add, rollaxis, sort, arange

def percentile(a, q, limit=None, interpolation='linear', axis=None,
               out=None, overwrite_input=False):
    """
    Compute the qth percentile of the data along the specified axis.

    Returns the qth percentile of the array elements.

makoc

import numpy as np
from collections import defaultdict as _dd

def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toend=True):
    """Create a view of `array` which for every point gives the n-dimensional
    neighbourhood of size window. New dimensions are added at the end of
    `array` or after the corresponding original dimension.
    
    Parameters
    ----------

makoc

"""Impressive little thing how einsum + stride_tricks can beat numpys build in C functions
for correlate (for large data). (ok depending on the implementation of np.correlate, the
comparison is not fair, but still rather impressive that you can get comparable speeds)
"""

import numpy as np
import stride_tricks as st # stride_tricks.py gist

a = np.random.random((100,100,100)).ravel()
stamp = np.random.random((3,3,3)).ravel()

makoc

def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toend=True):
    """Create a view of `array` which for every point gives the n-dimensional
    neighbourhood of size window. New dimensions are added at the end of
    `array` or after the corresponding original dimension.
    
    Parameters
    ----------
    array : array_like
        Array to which the rolling window is applied.
    window : int or tuple

makoc

Keybase proof

I hereby claim:

• I am makoc on github.
• I am makoc (https://keybase.io/makoc) on keybase.
• I have a public key whose fingerprint is 89F7 155E C20B F864 E29E 21DF A27F 66F7 7A73 B7EF

To claim this, I am signing this object: