Tasdik Rahman tasdikrahman

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

Comprehensions in Python the Jedi way

Beautiful is better than ugly. Explicit is better than implicit.

-- The Zen of Python

I frequently deal with collections of things in the programs I write. Collections of droids, jedis, planets, lightsabers, starfighters, etc. When programming in Python, these collections of things are usually represented as lists, sets and dictionaries. Oftentimes, what I want to do with collections is to transform them in various ways. Comprehensions is a powerful syntax for doing just that. I use them extensively, and it's one of the things that keep me coming back to Python. Let me show you a few examples of the incredible usefulness of comprehensions.

All of the tasks presented in the examples can be accomplished with the extensive standard library available in Python. These solutions would arguably be more terse and efficient in some cases. I don't have anything against the standard library. To me there is a certain

Transforming Code into Beautiful, Idiomatic Python

Notes from Raymond Hettinger's talk at pycon US 2013 video, slides.

The code examples and direct quotes are all from Raymond's talk. I've reproduced them here for my own edification and the hopes that others will find them as handy as I have!

Looping over a range of numbers

for i in [0, 1, 2, 3, 4, 5]:

List of various compiler resources

Notes

🌠 represents a resource that has been fully read and approved
★ represents a resource that has been skimmed and looks good
☠ represents a resource that has been darkf approved.
No symbol represents a resource that I just threw up here (quanity over quality and all of that)
Hopefully all links will eventually move to 🌠 and/or ☠
The Interesting Reads section isn't specifically for compiler development, but might still be interesting to read for a compiler writer

Note: I'm currently taking a break from this course to focus on my studies so I can finally graduate

##Working with ansible-vault

I've been using a lot of Ansible lately and while almost everything has been great, finding a clean way to implement ansible-vault wasn't immediately apparent.

What I decided on was the following: put your secret information into a vars file, reference that vars file from your task, and encrypt the whole vars file using ansible-vault encrypt.

Let's use an example: You're writing an Ansible role and want to encrypt the spoiler for the movie Aliens.

Make it real

Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.

Ship it

Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.

Do it with style

Job search sites

Stack Overflow - http://stackoverflow.com/jobs
Angel List - https://angel.co/jobs
Linked In - https://www.linkedin.com/jobs/
Hasjob - https://hasjob.co/
Github Jobs - https://jobs.github.com/
Hacker News Who is Hiring - http://hnhiring.me/
Hacker Earth - https://www.hackerearth.com/jobs/hiring/

	---
	# ^^^ YAML documents must begin with the document separator "---"
	#
	#### Example docblock, I like to put a descriptive comment at the top of my
	#### playbooks.
	#
	# Overview: Playbook to bootstrap a new host for configuration management.
	# Applies to: production
	# Description:
	# Ensures that a host is configured for management with Ansible.

	Bigdata is like combination of bunch of subjects. Mainly require programming, analysis, nlp, MLP, mathematics.

	To see links, Go : http://www.quora.com/What-are-some-good-sources-to-learn-big-data
	Here are bunch of courses I came accross:

	Introduction to CS Course
	Notes: Introduction to Computer Science Course that provides instructions on coding.
	Online Resources:
	Udacity - intro to CS course,
	Coursera - Computer Science 101