Mirhossein Mousavi mirhmousavi

Less Cheatsheet

less {filename}

Signal	Value	Action	Comment
SIGHUP	1	Term	Hangup detected on controlling terminal or death of controlling process
SIGINT	2	Term	Interrupt from keyboard
SIGQUIT	3	Core	Quit from keyboard
SIGILL	4	Core	Illegal Instruction
SIGABRT	6	Core	Abort signal from abort(3)
SIGFPE	8	Core	Floating point exception
SIGKILL	9	Term	Kill signal
SIGSEGV	11	Core	Invalid memory reference
SIGPIPE	13	Term	Broken pipe: write to pipe with no readers

Class names are CamelCase.

Methods and variables are snake_case.

Methods with a ? suffix will return a boolean.

Create a new repository, or reuse an existing one.

Generate a new SSH key:

ssh-keygen -t rsa -C "[email protected]"

Copy the contents of the file ~/.ssh/id_rsa.pub to your SSH keys in your GitHub account settings (https://github.com/settings/keys).

Test SSH key:

The use of __main__.py to create executables

myprojectfolder/
    |_ __main__.py
    |_ __init__.py

Being __main__.py:

print("Hello")

	import time
	import sys


	animation = "\|/-\\"

	for i in range(100):
	time.sleep(0.1)
	sys.stdout.write("\r" + animation[i % len(animation)])
	sys.stdout.flush()

	#
	# CORS header support
	#
	# One way to use this is by placing it into a file called "cors_support"
	# under your Nginx configuration directory and placing the following
	# statement inside your location block(s):
	#
	# include cors_support;
	#
	# As of Nginx 1.7.5, add_header supports an "always" parameter which

	While I was working on a personal project, I decided to compare foreach vs array_map to iterate over a large set of items.

	So to support my decision, I ran a benchmark on both foreach and array_map.

	With a simple array of 1,000,000 objects, I iterate over them with foreach and array_map. And surprisingly, foreach ran in 0.24sec average, while array_map took over 3.30sec.

	Also array_map ran out of memory, I had to do an ini_set("memory_limit","512M"); to at least get some results.

	My system:
	Macbook

	/* Useful celery config.

	app = Celery('tasks',
	broker='redis://localhost:6379',
	backend='redis://localhost:6379')

	app.conf.update(
	CELERY_TASK_RESULT_EXPIRES=3600,
	CELERY_QUEUES=(
	Queue('default', routing_key='tasks.#'),

	import selenium
	import time
	from selenium import webdriver

	browser = webdriver.PhantomJS("phantomjs")
	browser.get("https://twitter.com/StackStatus")
	print browser.title

	pause = 3