Guillaume Balaine Igosuki

Making a Nice ZSH Environment

Making a Nice ZSH Environment
zshenv

What is this about?

What it changes

Re-frisk Visualize re-frame pattern data or reagent ratom data as a tree structure, watch re-frame events and export state in the debugger
Dirac A Chrome DevTools fork for ClojureScript developers
BinaryAge custom formatters for ClojureScript

Awesome stuff

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

Useful resources

This cheat sheet originated from the forum, credits to Laurent Poulain. We copied it and changed or added a few things.

Evaluation Rules

Call by value: evaluates the function arguments before calling the function
Call by name: evaluates the function first, and then evaluates the arguments if need be

    def example = 2      // evaluated when called
    val example = 2      // evaluated immediately

This is the example that comes with the reagent template converted to use HTML5 based history. This means there are no # in the urls.

I just got this working, so there might be better approaches

The changes are

use goog.history.Html5history instead of goog.History
listen to clicks on the page, extract the path from them, and push them onto the history
listen to history changes, and have secretary do its thing in response

This is my response to an email asking about Domain-Driven Design in golang project.

Thank you for getting in touch. Below you will find my thoughts on how golang works with DDD, changing it. This is merely a perception of how things worked out for us in a single project.

That project has a relatively well-known domain. My colleagues on this project are very knowledgeable, thoughtful and invested in quality design. The story spelled out below is a result of countless hours spent discussing and refining the approach.

Conclusions could be very different, if there was a different project, team or a story-teller.

Short story

General Background and Overview

Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

	# REFERENCES:
	# - https://github.com/puckel/docker-airflow
	# - https://github.com/ImDarrenG/mesos-framework-dev/blob/master/Dockerfile
	# - https://github.com/Stibbons/docker-airflow-mesos

	# Wherever you store your mesos image built from Dockerfile-mesos
	FROM slicelife/mesos:1.4.0 as mesos
	FROM ubuntu:16.04
	# Never prompts the user for choices on installation/configuration of packages
	ENV DEBIAN_FRONTEND noninteractive

	"""
	A deep neural network with or w/o dropout in one file.

	License: Do What The Fuck You Want to Public License http://www.wtfpl.net/
	"""

	import numpy, theano, sys, math
	from theano import tensor as T
	from theano import shared
	from theano.tensor.shared_randomstreams import RandomStreams