elgehelge

import requests

parameters = {'action': 'query',
              'generator': 'categorymembers',
              'gcmtitle': 'Category:Marvel_Comics_superheroes',
              'prop': 'revisions',
              'rvprop': 'content',
              # The API starts returning dictionaries without the 'revisions' key when requesting more than 50.
              # Not sure why, and can't find any documentation.
              'gcmlimit': 50,

elgehelge

// Step 1: Put this code in a bookmark.
// Step 2: Click the bookmark everytime you need access to an academic article.
// Step 3: Profit!?
javascript: var a=window.location+''; var x=a.indexOf('//'); var p; if(x == -1) { p = a.indexOf('/'); } else { p = a.indexOf('/',x+2); } window.location = a.substring(0,p)+".globalproxy.cvt.dk"+a.substring(p);

elgehelge

import requests

data = {
    'apikey'   : "9a128231f9bd4d82ac7d28cc74bde19d”,
    'user_data': {
		'name' : "John Doe",
		'email' : "johndoe@gmail.com”
		'address' : "123 John st. 12345 Doe”
		'phone' : "12345678”
		'device ID' : "12345ab6cde789f”

elgehelge

Keybase proof

I hereby claim:

• I am elgehelge on github.
• I am elgehelge (https://keybase.io/elgehelge) on keybase.
• I have a public key ASBPGJHydoH7L_5-JDHSCzpS8YgiMCVM2eG4e_-9TQ8arAo

To claim this, I am signing this object:

elgehelge

#!/bin/sh

# Next time I find myself running this, it is time to upgrade and get some inspiration: https://medium.com/@webprolific/getting-started-with-dotfiles-43c3602fd789

# Show hidden files
defaults write com.apple.finder AppleShowAllFiles YES

# Homebrew (cask included)
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

elgehelge

"""Script to illustrate usage of tf.estimator.Estimator in TF v1.5"""
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data as mnist_data
from tensorflow.contrib import slim

# Show debugging output
tf.logging.set_verbosity(tf.logging.DEBUG)

# Set default flags for the output directories

elgehelge

"""Script to illustrate inference of a trained tf.estimator.Estimator.
NOTE: This is dependent on mnist_estimator.py which defines the model.
mnist_estimator.py can be found at:
https://gist.github.com/elgehelge/faf200e2b36edfb1b1a77ec65f74ecab
"""
import numpy as np
import skimage.io
import tensorflow as tf

from mnist_estimator import get_estimator

elgehelge

import tensorflow as tf


# Data source
def data_generator(start, end):
    for x, y in zip(range(start, end), range(start, end)):
        print(x, y)
        yield x, y

elgehelge

import numpy as np
import tensorflow as tf
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense

batch_size = 1
data_size = 1


def generator():

elgehelge

#!/bin/bash

# Usage:   `source login_aws_mfa.sh <account id> <name> <mfa code>`
# Example: `source login_aws_mfa.sh 454099695756 john 123456`

{
  AWS_ACCESS_KEY_ID= && \
  AWS_SECRET_ACCESS_KEY= && \
  AWS_SESSION_TOKEN= && \
  token=$(aws sts get-session-token --serial-number arn:aws:iam::$1:mfa/$2 --token-code $3) && \