linuxster

davidrpugh

Creating a Conda development environment

We recommend that you set up a Python environment for developing quantecon that is separate from the "default" Python environment that you use in your own research. This will allow you to contribute to quantecon without worrying about corrupting the Python environment on which your other work depends.

Below are instructions for building a separate development environment for contributing to the quantecon package using the Conda package management system which comes bundled with the Anaconda Python distribution provided by Continuum Analytics.

Step 1:

Fork and clone a copy of the quant-econ repository on to your local machine.

Step 2:

michaeldorner

import socket
import sys
import time
import struct

host = 'localhost'
port = 8888
buffersize = 1024
N = 1000000
server_address = (host, port) 

application2000

These commands are based on a askubuntu answer http://askubuntu.com/a/581497
To install gcc-6 (gcc-6.1.1), I had to do more stuff as shown below.
USE THOSE COMMANDS AT YOUR OWN RISK. I SHALL NOT BE RESPONSIBLE FOR ANYTHING.
ABSOLUTELY NO WARRANTY.

If you are still reading let's carry on with the code.

sudo apt-get update && \
sudo apt-get install build-essential software-properties-common -y && \
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y && \

wesm

import gc
import os
import time

import numpy as np
import pandas as pd
from pyarrow.compat import guid
import pyarrow as pa
import pyarrow.parquet as pq
import snappy

mrocklin

linar-jether

andyweizhao

#!/bin/bash
## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.3 in ubuntu 18.04

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

fsaintjacques

#!/usr/bin/env bash

set -eu

PWD="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
SRC_DIR=$(realpath "${PWD}/..")
CXX_SRC=${SRC_DIR}/cpp

# The following can be set
: "${CMAKE:=cmake}"

jasonrig

#!/bin/bash
#SBATCH --job-name spark-cluster
#SBATCH --account=qh82
#SBATCH --time=02:00:00
# --- Master resources ---
#SBATCH --nodes=1
#SBATCH --mem-per-cpu=1G
#SBATCH --cpus-per-task=1
#SBATCH --ntasks-per-node=1
# --- Worker resources ---