| # The following construct evaluates "$@" and saves output on stdout in the | |
| # parameter stdout, output on stderr in the parameter stderr, and return value | |
| # in the parameter return. | |
| # | |
| # The idea was based on http://stackoverflow.com/a/18086548/1944784, but this | |
| # implementation is completely race-condition-free. The implementation was | |
| # refined during my exchange with Mathias Fredriksson @mafredri, in | |
| # https://github.com/mafredri/zsh-async/issues/1. See mainly | |
| # https://github.com/mafredri/zsh-async/issues/1#issuecomment-121468958, where | |
| # the advantage of this implementation is explained. |
Inspired to do some spring cleaning today, I reviewed my archived gists to see if there's anything noteworthy. I was pleasantly surprised to find a few nuggets buried amongst random error logs and git diffs.
Some of them are interesting technical guides that took hours to write, and it's a shame that they've rotted away in obscurity. Several others were picked up by google, and turns out they even got a few comments and a bunch of stars.
| /** | |
| * USB HID Keyboard scan codes as per USB spec 1.11 | |
| * plus some additional codes | |
| * | |
| * Created by MightyPork, 2016 | |
| * Public domain | |
| * | |
| * Adapted from: | |
| * https://source.android.com/devices/input/keyboard-devices.html | |
| */ |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from matplotlib.colors import ListedColormap | |
| from sklearn.cross_validation import train_test_split | |
| from sklearn.preprocessing import StandardScaler | |
| from sklearn.datasets import make_moons, make_circles, make_classification | |
| from sklearn.svm import SVC | |
| h = .02 # step size in the mesh |
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| Provider | Type | RAM | Cores | Storage | Transfer | Network | Price |
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| # how to separate items in a list from separators | |
| parsley.makeGrammar(''' | |
| a_list = ('a':it ','? -> it)* | |
| ''', {})('a,a,a').a_list() | |
| # result is ['a', 'a', 'a'] | |
| # strict comma-delimeted items (at least one item) | |
| parsley.makeGrammar(''' | |
| a_list = 'a':first (',' 'a')*:rest -> [first] + rest |
| import numpy as np | |
| import pandas as pd | |
| from collections import defaultdict | |
| from scipy.stats import hmean | |
| from scipy.spatial.distance import cdist | |
| from scipy import stats | |
| import numbers | |
| def weighted_hamming(data): |
