TheSkorm

#https://www.python.org/ftp/python/3.3.0/python-3.3.0.msi
#http://pycurl.sourceforge.net/download/pycurl-7.19.5.1.win32-py3.3.exe
import pycurl
from io import BytesIO
import json
buffer = BytesIO()
c = pycurl.Curl()
c.setopt(c.URL, 'https://hooks.slack.com/services/XXXXXXXX')
post_data = {"text": "This is a line of text in a channel.\nAnd this is another line of text."}
postfields = json.dumps(post_data)

TheSkorm

#!/usr/bin/env python

"""
The MIT License (MIT)

Copyright (c) 2015 Maker Musings

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights

TheSkorm

/**
 * This sample demonstrates a simple driver  built against the Alexa Lighting Api.
 * For additional details, please refer to the Alexa Lighting API developer documentation 
 * https://developer.amazon.com/public/binaries/content/assets/html/alexa-lighting-api.html
 */
var https = require('https');
var REMOTE_CLOUD_BASE_PATH = '/';
var REMOTE_CLOUD_HOSTNAME = 'www.amazon.com';

var https = require('https');

TheSkorm

/**
 * This sample demonstrates a simple driver  built against the Alexa Lighting Api.
 * For additional details, please refer to the Alexa Lighting API developer documentation 
 * https://developer.amazon.com/public/binaries/content/assets/html/alexa-lighting-api.html
 */
var https = require('https');
var REMOTE_CLOUD_BASE_PATH = '/';
var REMOTE_CLOUD_HOSTNAME = 'www.amazon.com';

var https = require('https');

TheSkorm

# Automatically generated LIRC file
#
# Creating tool: IrScrutinizer version 0.1.0pre
# Creating user: bengt
# CreateDate: Sun Sep 01 21:47:20 CEST 2013
#
#
# Export from IrScrutinizer
#
begin remote

TheSkorm

results = {"b": 956}

queue = a.split("\n")

while queue:
	test = queue.pop(0)
	(operation, resultant) = test.split(" -> ")
	spaces = operation.count(" ")
	print test
	process=True

TheSkorm

f = open('Downloads/input.txt', 'r')
chars=0
memory=0
for line in f:
	print bytes(line[:-1])
	print len(bytes(line[:-1]))
	print len(line.decode('string_escape'))-3
	memory += len(bytes(line[:-1]))
	chars += len(line.decode('string_escape'))-3

TheSkorm

// This script can be run in AWS Lambda and simply just searches for all cards on a list and turns them into a checklist on a predefined card.
// Any checklist items that are checked off will also remove the cards
// The checklist can be deleted and will be created again with all the remaining cards.

var Trello = require("trello");
var trello = new Trello("", "");

board = '';
list_check = '';
check_list_id = "";

TheSkorm

// npm install irc  requests  slack-client  tail

Slack = require('slack-client');

slackToken = '' 
autoReconnect = true  
autoMark = true  
 
slack = new Slack(slackToken, autoReconnect, autoMark)
 

TheSkorm

default_feed_rate                            5400             # Default rate ( mm/minute ) for G1/G2/G3 moves
default_seek_rate                            5400             # Default rate ( mm/minute ) for G0 moves
mm_per_arc_segment                           0.5              # Arcs are cut into segments ( lines ), this is the length for
                                                              # these segments.  Smaller values mean more resolution,
                                                              # higher values mean faster computation
#mm_per_line_segment                         0.5              # Lines can be cut into segments ( not useful with cartesian
                                                              # coordinates robots ).
delta_segments_per_second                    100              # for deltas only same as in Marlin/Delta, set to 0 to disable
                                                              # and use mm_per_line_segment