Jwely

from typing import Tuple
import numpy as np


class MineSweeper(object):

    def __init__(self, shape: Tuple, n_mines: int):
        """

Jwely

/* create some database and administrator account, for example. */
create user dummy_admin;
alter user dummy_admin with password 'dummy_pass';
create database "dummy_dbase" owner dummy_admin;
\c "dummy_dbase"
create extension if not exists postgis;
create extension if not exists fuzzystrmatch;
create extension if not exists postgis_tiger_geocoder;
create extension if not exists postgis_topology;
\c postgres

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from contextlib import contextmanager

@contextmanager
def manage_something(something):
  """ this is the general structure of a contextmanager """
  try:
    # prepare the something
    yield something
    
  except Exception as e:

Jwely

from queue import Queue
import threading
import os
from datetime import datetime
import time


def updater():
    for i in range(10):
        time.sleep(1)

Jwely

from PIL import Image


class AmbiguousArgs(BaseException):
    pass


def remove_png_alpha(image_path, overwrite=False, color=(255, 255, 255), out_path=None):
    """
    Removes the alpha layer form an input png (probably works with other filetypes as well)

Jwely

import ftplib
import os
import re

"""
MIT license: 2017 - Jwely

Example usage:
``` python
import ftplib

Jwely

__author__ = 'Jwely'


class Butt():

    def __init__(self):
        self.times_farted = 0

    def fart(self, times):
        self.times_farted += times

Jwely

# super barebones list to csv

list = ["some", "kind", "of", "data"]

with open("myfile.csv", "w+") as f:
    for item in list:
        f.write(str(item) + "\n")
    
# same deal but with lists of lists
list_of_lists = [["bob", "20"],

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#!/usr/bin/env python
# in the input expression
#from osgeo import gdal, gdalconst, gdalnumeric
import gdal
import gdalconst
import gdalnumeric
import numpy
import os
import math  # imported so it is available to the users expression evaluation

Jwely

__author__ = 'Jwely' 

import numpy

# in order to handle Nodata values, we must use floats, not integer datatypes.
array = numpy.array([0, 5, 6, 3, 0, 11, 5, 2, 3, 6, 4, 1, 2, 5, 12], "float32")

# mask this array, where all "0" values are masked
# see also: https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html
masked_array = numpy.ma.masked_equal(array, 0)