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#!/usr/bin/python
from __future__ import print_function

#
# A simple CGI script useful for debugging GitHub web hooks
# https://developer.github.com/webhooks/
#

import hashlib, hmac, json, os, sys, traceback
from subprocess import Popen, PIPE, STDOUT

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#!/usr/bin/env bash

#set -x

package="fastai"
ver="1.0.14"

# is_pip_ver_available "1.0.14"
# returns 1 if yes, 0 otherwise
function is_pip_ver_available() {

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import pathlib, PIL, random, os, gzip
import numpy as np

def load_mnist(path, kind='train'):

    """Load MNIST data from `path`"""
    labels_path = os.path.join(path, '%s-labels-idx1-ubyte.gz' % kind)
    images_path = os.path.join(path, '%s-images-idx3-ubyte.gz' % kind)

    with gzip.open(labels_path, 'rb') as lbpath:

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# usage:
# pypi_module_version_is_available("Pillow", "5.4.0")

import subprocess
def pypi_module_version_is_available(module, version):
    "Check whether module==version is available on pypi"
    # returns True/False (or None if failed to execute the check)

    # using a hack that when passing "module==" w/ no version number to pip
    # it "fails" and returns all the available versions in stderr

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import tracemalloc, threading, torch, time, pynvml
from fastai.utils.mem import *
from fastai.vision import *

if not torch.cuda.is_available(): raise Exception("pytorch is required")

def preload_pytorch():
    torch.ones((1, 1)).cuda()
    
def gpu_mem_get_used_no_cache():

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import sys, re
from io import StringIO

# When any function contains print() calls that get overwritten, like progress bars,
# a special care needs to be applied, since under pytest -s captured output (capsys
# or contextlib.redirect_stdout) contains any temporary printed strings, followed by
# \r's. This helper function ensures that the buffer will contain the same output
# with and without -s in pytest, by turning:
# foo bar\r tar mar\r final message
# into:

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import torch
def consume_gpu_ram(n): return torch.ones((n, n)).cuda()
def consume_gpu_ram_256mb(): return consume_gpu_ram(2**13)

def b2mb(x): return int(x/2**20)
class TorchTracemalloc():

    def __enter__(self):
        self.begin = torch.cuda.memory_allocated()

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import os,requests,platform,json,subprocess
import tarfile
from zipfile import ZipFile

debug=False
os_type=platform.system().lower()
machine_type=platform.machine().lower()

if debug:print(f'Your OS and Machine Type is {os_type} and {machine_type}')

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import sys
def str2func(name):
    "Convert a string of a fully qualified function, class or module into its python object"
    if isinstance(name, str):
        subpaths = name.split('.')
    else:
        return None
    
    module = subpaths.pop(0)
    if module in sys.modules:

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Here is a support letter I have just sent to github [2019-02-22]:

--------------------->8---------------->8-------------------->8------------------
Hi,

I contacted you some 6 months ago and it doesn't look like this is of a
priority, but it's of a huge priority to tens of thousands of projects that now
require PR submitters to sign CLA before their PR can be accepted.

You probably don't realize that if I looked at the PR changes and the user then