BAKEZQ zqbake

Usage

Generate TLS certificates for localhost:

pip install trustme-cli
trustme-cli

Run wrk on each endpoint, eg:

Goal

Install working tensorflow or pytorch via standard conda environment workflow.

Basic Setup : Install `pytorch` in a fresh conda environment

The recommended conda-based install process works smoothly:

$ # Create a fresh environment

The initial source comes from sdcuike/issueBlog#4

http://greenteapress.com/wp/

https://papers.nips.cc

https://github.com/PacktPublishing free to download books code by Packet

https://github.com/EbookFoundation/free-programming-books Very immense

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

From - https://github.com/Kunena/Kunena-Forum/wiki/Create-a-new-branch-with-git-and-manage-branches

git checkout -b [name_of_your_new_branch]

Push the branch on github :

git push origin [name_of_your_new_branch]

When you want to commit something in your branch, be sure to be in your branch.

	import numpy as np
	from scipy import signal

	def gaussian_kernel(n, std, normalised=False):
	'''
	Generates a n x n matrix with a centered gaussian
	of standard deviation std centered on it. If normalised,
	its volume equals 1.'''
	gaussian1D = signal.gaussian(n, std)
	gaussian2D = np.outer(gaussian1D, gaussian1D)

	"""
	Python is a dynamic language, and it is relatively easy to dynamically create
	and modify things such as classes and objects. Functions, however, are quite
	challenging to create dynamically.

	One area where we might want to do this is in an RPC library, where a function
	defined on a server needs to be available remotely on a client.

	The naive solution is to simply pass arguments to a generic function that
	accepts `args` and `*kwargs`. A lot of information is lost with this approach,

	#! /bin/sh

	# update glibc to 2.17 for CentOS 6

	wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-2.17-55.el6.x86_64.rpm
	wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-common-2.17-55.el6.x86_64.rpm
	wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-devel-2.17-55.el6.x86_64.rpm
	wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-headers-2.17-55.el6.x86_64.rpm

	sudo rpm -Uvh glibc-2.17-55.el6.x86_64.rpm \

	package main

	import (
	"fmt"
	"sync"
	"time"
	)

	func main() {

	'''
	This script brings up the entire stack of Docker containers, removing the current ones.

	Docker compose was tried for this task and it wasn't customisable enough.
	Docker cloud was tried (with stack files) and was buggy (failed to launch, no logs returned).
	Docker machine was tried, but it can't connect to existing servers only ones it created.
	Rancher was too heavy weight for the task, as the containers are lightweight in DigitalOcean.
	Kubernetes would've been too heavy weight for DigitalOcean.
	It was written in Powershell and worked. But then converting it to Bash was too much effort.
	Powershell for Linux is too much effort to install without a debian package (and none standard)