vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

stevenringo

| Title | Description

dypsilon

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

This page is not maintained anymore, please update your bookmarks.

---

fyears

if you are using linux, unix, os x:

pip install -U setuptools
pip install -U pip

pip install numpy
pip install scipy
pip install matplotlib
#pip install PySide

swalkinshaw

Moved to Shopify/graphql-design-tutorial

fernandoaleman

# Start the old vagrant
$ vagrant init centos-6.3
$ vagrant up

# You should see a message like:
#  [default] The guest additions on this VM do not match the install version of
#  VirtualBox! This may cause things such as forwarded ports, shared
#  folders, and more to not work properly. If any of those things fail on
#  this machine, please update the guest additions and repackage the
#  box.

andy-thomason

Genomics - A programmer's guide.

Andy Thomason is a Senior Programmer at Genomics PLC. He has been witing graphics systems, games and compilers since the '70s and specialises in code performance.

https://www.genomicsplc.com

dan-blanchard

For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.

A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s