Alex Findlater adfindlater

## git_token_dockerfile
# RUN git config --global url."https://$GITHUB_TOKEN@github.com/".insteadOf "https://github.com/"

## yaml_to_docker_env_file.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
import argparse
import yaml


def convert_yaml_to_docker_env(
    yaml_path: str, env_path: str = "/tmp/tmp.env", uppercase_keys: bool = False
):
    """Read & convert a YAML file into a docker environment variable file.  This

## qutemacs.py
# qutemacs - a simple, preconfigured Emacs binding set for qutebrowser
#
# The aim of this binding set is not to provide bindings for absolutely
# everything, but to provide a stable launching point for people to make their
# own bindings.
#
# Installation:
#
# 1. Copy this file or add this repo as a submodule to your dotfiles.
# 2. Add this line to your config.py, and point the path to this file:

## sns_sms_shopper.py
import boto3
import time
import requests
from bs4 import BeautifulSoup

colors = ["Savannah"]
URL = "https://shop.lululemon.com/p/womens-outerwear/Scuba-Oversized-12-Zip-Hoodie/?sz=XS%2FS"
sns_arn = ""

while True:

## run_regression.py
# coding=utf-8
#
# Minimal BERT regression model
#
# Code borrowed from huggingface text-classification example (original licence follows):
# https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue.py
#
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.
#

## wiki_vcard_scrape.py
from bs4 import BeautifulSoup
from pprint import pprint

import urllib.request

site = "https://en.wikipedia.org/wiki/Ryder"
hdr = {"User-Agent": "Mozilla/5.0"}
req = urllib.request.Request(site, headers=hdr)
page = urllib.request.urlopen(req)
soup = BeautifulSoup(page.read())

## searchablePDF.py
import pytesseract
import argparse
import os

from pdf2image import convert_from_path
from PyPDF2 import PdfFileMerger
from progressbar import ProgressBar


def create_searchable_pdf(images: list, output_path: str):

## mount_airport.sh
sudo mount -t cifs //10.0.0.1/Data ~/airport -o password=XXX,sec=ntlm,username=YYY,vers=1.0

## peek.py
#!/usr/bin/python3
from __future__ import print_function

import pickle
import codecs
import os.path
import datetime

from rofi import Rofi
from typing import Dict
	#!/usr/bin/python
	# -- coding: utf-8 --
	import argparse
	import yaml


	def convert_yaml_to_docker_env(
	yaml_path: str, env_path: str = "/tmp/tmp.env", uppercase_keys: bool = False
	):
	"""Read & convert a YAML file into a docker environment variable file. This
	# qutemacs - a simple, preconfigured Emacs binding set for qutebrowser
	#
	# The aim of this binding set is not to provide bindings for absolutely
	# everything, but to provide a stable launching point for people to make their
	# own bindings.
	#
	# Installation:
	#
	# 1. Copy this file or add this repo as a submodule to your dotfiles.
	# 2. Add this line to your config.py, and point the path to this file:
	import boto3
	import time
	import requests
	from bs4 import BeautifulSoup

	colors = ["Savannah"]
	URL = "https://shop.lululemon.com/p/womens-outerwear/Scuba-Oversized-12-Zip-Hoodie/?sz=XS%2FS"
	sns_arn = ""

	while True:
	# coding=utf-8
	#
	# Minimal BERT regression model
	#
	# Code borrowed from huggingface text-classification example (original licence follows):
	# https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue.py
	#
	# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
	# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
	#
	from bs4 import BeautifulSoup
	from pprint import pprint

	import urllib.request

	site = "https://en.wikipedia.org/wiki/Ryder"
	hdr = {"User-Agent": "Mozilla/5.0"}
	req = urllib.request.Request(site, headers=hdr)
	page = urllib.request.urlopen(req)
	soup = BeautifulSoup(page.read())
	import pytesseract
	import argparse
	import os

	from pdf2image import convert_from_path
	from PyPDF2 import PdfFileMerger
	from progressbar import ProgressBar


	def create_searchable_pdf(images: list, output_path: str):
	#!/usr/bin/python3
	from __future__ import print_function

	import pickle
	import codecs
	import os.path
	import datetime

	from rofi import Rofi
	from typing import Dict