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Setting your machine#


Every team will settle on a specific setup with their tech mentors. This setup will determine, for example:

  • which Python version to use
  • versioning via virtual environments
  • maintaining package dependencies
  • continuous testing tools
  • your version control workflow.

Today, we're not doing that. We're making sure that everybody has some basic tools they will need for the tutorials and the beginning of the fellowship, and that you can log into the server and database.

Getting help

Work through the prerequisites below, making sure that all the software you installed works.

Affix three kinds of post-it notes to your laptop:

  • one with your operating system, e.g. Ubuntu 18.04
  • if you get an app working (e.g. ssh), write its name on a green post-it and stick it to your screen
  • if you tried - but the app failed - write its name on a red post-it

If you're stuck with a step, ask a person with a corresponding green post-it (and preferrably your operating system) for help.

The tech mentors will hover around and help with red stickers.

You will need a few credentials for training accounts. We'll post them up front.


The notes below aren't self-explanatory and will not cover all (or even the majority) of errors you might encounter. Make good use of the people in the room!

Getting a terminal environment on a Windows Computer

You're going to want to access the terminal. Unfortunately, windows computers don't have this by default (yet). Fortunately, there are a couple options for obtaining a terminal-like environment, such as the following:

  • git-bash
  • Cygwin
  • If you go with cygwin, make sure to choose all git packages when you're in the package menu portion of the setup

If you're a windows user, make sure to download one of these.

Let's get this over with!

Package Manager#

A package manager will make your life easier.

  • on Mac, install Brew

    • Testing: To check that it installed, run the command which brew in the terminal. If it returns: /usr/local/bin/brew, it means that homebrew is installed; if it returns brew not found, it means homebrew is not installed.
  • on GNU/Linux, you probably already have yum (RedHat based distros) or apt (Debian based distros)

    • Testing: run yum help or apt help
  • ask Windows users around you for their preferred way to manage packages. And tell us, so we can add them here!

Git and GitHub Account#

  1. If you don't have a GitHub account, make one!

  2. Go to this site, input your username, and click "Add me to organization". Your username will be automatically added to the DSSG organization on GitHub.

  3. Install git using the appropriate OS’s package manager


In the terminal, type:

brew update
brew install git
sudo apt update
sudo apt install git

On Windows, you should already have git. (Either you installed git-bash, which is part of git, or you should have downloaded git in the cygwin package menu.)

  1. Test your installation. For example, create a directory, and make it a git repo:

mkdir mytestdir
cd mytestdir/
git init
> Initialized empty Git repository in [...]/mytestdir/.git/
You can un-git the directory by deleting the .git folder: rm -r .git (or simply delete mytestdir entirely with command rmdir mytestdir).


As said, your team will decide on which Python version (and versioning) to install. Thus, if you have any working setup already, don't break it (for now)! Just make sure you have the packages listed below installed.

pyenv vs anaconda

This is a contentious topic! For some people the way to go, because apparently is easier is Anaconda (conda or mini-conda), for other, for consistency and flexibility is pyenv. In reality, python library’s system is a mess and in constant evolution.

We will favor pyenv here, since we think is the one that allows you more flexibility and teaches you about how python works.

If you are in GNU/Linux or in MacOS you have python installed. But that python is the one use by your operative system for doing stuff, probably you don’t want to mess with it. So we will install a different python, for you exclusive use. First we will install some libraries1:

# optional, but recommended:
brew install openssl readline sqlite3 xz zlib

For Debian based distros:

sudo apt-get update; sudo apt-get install --no-install-recommends make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev

For Red hat based distros:

dnf install make gcc zlib-devel bzip2 bzip2-devel readline-devel sqlite sqlite-devel openssl-devel tk-devel libffi-devel

We will install pyenv

    $ curl | bash

And follow the instructions at the end (Mostly about adding some lines to your .bash_profile or .zsh_profile or similar.) Restart your terminal.

Virtual environment#

As a last step, we will create a virtual environment. A virtual environment is a tool that helps to keep dependencies required by different projects separate. By default, every project on your system will use the same directory to store and retrieve third party libraries (called site packages). A virtual environment helps avoid conflicts between requirements for different projects and it isolates dependencies. For example, different projects may use different versions of Python.

There are multiple tools to manage virtual environments. The most commonly used ones are

  • anaconda: Environment manager and package manager. Anaconda makes makes managing different environments, and installing packages very easy. In fact, many of the standard Data Science packages are automatically installed when setting up anaconda. However, it requires a large amount of storage space.
  • pyenv: Python version manager. The focus of pyenv is to switch between different python versions.
  • virtualenv: Python environment manager. virtualenv is an intermediate solution between anaconda and pyenv.

To create an environment called dssg with Python 3.7.3 in pyenv, install the python version:

    $ pyenv install 3.7.3

This will take several minutes. Once complete, create the environment

$ pyenv virtualenv 3.7.3 dssg

And then assign it as the virtual environment to use in your directory of choice with

$ echo dssg > .python-version

Depending on your command shell (bash, zsh, csh, etc) configuration you should get some info that the environment is in use, if not you can check it with

$ pyenv version
dssg (set by /home/user/projects/.python-version)

To perform the same task in anaconda, type

$ conda create -n dssg python=3.7

Press y to proceed. This wil install the Python version and all the default anaconda packages in path_to_your_anaconda_location/anaconda/envs/dssg

We activate the environment with

$ source activate dssg

Note that the active environment is visible in your command prompt. Virtual environments are only active in the current terminal. If you ever need to deactivate it, type

$ source deactivate

Package installations#

Packages are installed using pip. To install a single package:

$ pip install pandas

To install many packages at once, list all the packages needed in a file (usually called requirements.txt), navigate to the folder of the file and execute

$ pip install -r requirements.txt

To try it out, use this file: requirements.txt.


Jupyter notebooks are a convenient environment for experimentation, prototyping, and sharing exploratory work. Jupyter notebooks require a kernel that executes the code. It should link to the virtual environment:

$ python -m ipykernel install --user --name=myenv --display-name "myenv"

It's time to test! In order to test that both jupyter and the python packages installed appropriately, you should do the following:

  • Download the file SoftwareSetup.ipynb into your directory.
  • Type in the terminal

    $ jupyter notebook

Your browser will open a new tab and you will see something like the following:

  • Click on SoftwareSetup.ipynb to open the notebook
  • Follow the instructions in the notebook to run each cell.

SSH / Putty#

SSH keys#

You need to generate a SSH key pair. To do this, follow the instructions on GitHub, namely 'Generating a new SSH key' and 'Adding your SSH key to ssh-agent'. Windows users probably want to use git bash or PuTTYgen (if you're on Linux or OS X, your standard terminal should be the bash shell you need).

The steps in 'Generating a new SSH key' create two new files (by default in ~/.ssh/: One without a file extension (by default, it's called id_rsa), and one with the extension .pub. The latter one is your _pub_lic key, which you will share with your project server, so that it can recognize you; the former is your private key, which you must not share with anybody, as it will let you access your project server.

After having generated the key pair, you should set the correct file permissions for your private key: SSH requires that only you, the owner, are able to read/write it, and will give you an error otherwise. You can set the right permissions with this command:

chmod 600 ~/.ssh/nameofyourprivatekey

(where you'll have to substitute in the path and name of your private key that you chose during key generation).

Testing it#

Use your username and server's address to ssh into the server:

ssh yourusername@serverurl

Once you enter your password, you should be dropped into a shell on the server:

yourusername@servername: ~$

PRO tip

Your life will be easier if you set up a .ssh/config file


The database server runs Postgres 9.5.10.

For Windows users

Windows users should skip the steps below, and instead use DBeaver. When setting up the connection in DBeaver, you will need to specify the SSH tunnel; the database credentials are the ones we shared with you, and the SSH tunnel credentials are the ones you used in the previous step to SSH into the training server. Alternatively, everybody can access psql from the training server: SSH into the training server as in the step before, then, on the server's shell, call psql -h POSTGRESURL -U USERNAME -d DBNAME, where you need to substitute POSTGRESURL with the postgres server's address, USERNAME with your database username, and DBNAME with the name of the database.

For all non-Windows users, also do these steps to access the PostgreSQL server from your local machine. First we need to install the database client, psql


Make sure you have the psql client installed; on Mac, this would be

$ brew tap-pin dbcli/tap
$ brew install pgcli

Note, we are installing pgcli instead of psql, but apparently there is no way of install just the client without installing the whole database server.

If you still want to give it a shot:

$ brew postgres

On Debian based distros:

sudo apt install postgresql-client libpq-dev

Once you have the postgres client installed, you can access the training database with it. However, the database server only allows access from the training server. Thus, you need to set up an SSH tunnel through the training server to the Postgres server:

$ ssh -NL localhost:8888:POSTGRESURL:5432 ec2username@EC2URL

where you need to substitute POSTGRESURL, ec2username, and EC2URL with the postgres server's URL, your username on the training server, and the training server's URL respectively. Also, you should substitute 8888 with a random number in the 8000-65000 range of your choice (port 8888 might be in use already).

This command forwards your laptop's port 8888 through your account on the EC2 (EC2URL) to the Postgres server port 5432. So if you access your local port 8888 in the next step, you get forwarded to the Postgres server's port 5432 - but from the Postgres server's view, the traffic is now coming from the training server (instead of your laptop), and the training server is the only IP address that is allowed to access the postgres server.

Figure. A graphical representation of a ssh tunnel. Not quite our situation -they are using a MySQL db who knows why-, but it is close enough. Courtesy from this Medium post.

Connect to the Postgres database on the forwarded port

$ psql -h localhost -p 8888 -U USERNAME -d DBNAME

where you need to replace USERNAME with the postgres [!] username, DBNAME with the name of your database, and the 8888 with the number you chose in the previous step. You then get prompted for a password. This is now the postgres server asking, so you need to reply with the corresponding password!

This should drop you into a SQL shell on the database server.


In some configurations, you'll need to explicitly assume a role to do anything beyond connecting to the database. To make changes to the training database, use the training_write role. Let's test it by creating and dropping a schema:

set role training_write;
create schema jsmith;
drop schema jsmith;

PRO tip

You could save a lot of keystrokes if you setup a .pgservice.conffile and a .pgpass file in your $HOME folder.

Then you could simply type

$ psql service=mydb  # mydb is the name of the dbservice
I really prefer a GUI

if you want a graphical interface to databases - you might want to use DBeaver.

  1. for an updated version of this instructions see here