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jupyter tutorial.txt
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Jupyter notebook
1/ Launch a basic EC2 instance but check the "auto-assign public IP"
and add in security group the port 8888(port of jupyter)
2/ connect to it through puttygen and putty
3/ download anaconda installer on the machine by writing and type YES
wget https://repo.continuum.io/archive/Anaconda3-4.4.0-Linux-x86_64.sh
and install anaconda by tiping :
bash Anaconda3-4.4.0-Linux-x86_64.sh
when it ask about PATH answer YES
4/ enter those 2 command to switch to python3
which python /usr/bin/python
source .bashrc
5/ We need to put a password because remember that Jupyter runs notebooks on a server which
anyone can access with an internet browser, so we need to set a password to prevent
any unauthorized access to our notebookseveryone can access to this
TO DO THAT we first need to access the IPYTHON console by typing
ipython
6/ import the password module by typing
from IPython.lib import passwd
then
passwd()
enter a password and confirm it (normal if you dont see anything when you type)
and copy the output SHA like that
Out[4]: 'sha1:0994f3bca11f:9e9a3e8c007feb18fa915e118e5f9740b21699bb'
and then exit by typing "exit"
7/ we need to Configure Jupyter/Ipython server to access your notebooks from your
local computer via your internet browser. First we’ll create a default config file by just typing:
jupyter notebook --generate-config
we’ll need to generate SSL certificates so our browser will trust our
Jupyter Notebooks server (*sigh* I know). By typing :
mkdir certs
cd certs
8/ we create our PEM file (this is separate from the PEM file on your
local computer which we downloaded from AWS):
sudo openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem
we need to enter some personal info
[ec2-user@ip-172-31-0-106 certs]$ sudo openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem
Generating a 1024 bit RSA private key
.++++++
........................++++++
writing new private key to 'mycert.pem'
-----
You are about to be asked to enter information that will be incorporated
into your certificate request.
What you are about to enter is what is called a Distinguished Name or a DN.
There are quite a few fields but you can leave some blank
For some fields there will be a default value,
If you enter '.', the field will be left blank.
-----
Country Name (2 letter code) [XX]:FR
State or Province Name (full name) []:Paris
Locality Name (eg, city) [Default City]:Paris
Organization Name (eg, company) [Default Company Ltd]:NONE
Organizational Unit Name (eg, section) []:NONE
Common Name (eg, your name or your server's hostname) []:ME
Email Address []:email
9/ go back to our home directory by typing : cd
10/ Edit your Jupyter configuration file.
Let’s use vim to edit the configuration file we crated in the previous step
vim .jupyter/jupyter_notebook_config.py
we need to enter this code, so press 'i' to input something and paste this anywhere (since all is in comment)
c = get_config()
# Kernel config
c.IPKernelApp.pylab = 'inline' # if you want plotting support always in your notebook
# Notebook config
c.NotebookApp.certfile = u'/home/ec2-user/certs/mycert.pem' #location of your certificate file
c.NotebookApp.ip = '*'
c.NotebookApp.open_browser = False #so that the ipython notebook does not opens up a browser by default
c.NotebookApp.password = u'sha1:0994f3bca11f:9e9a3e8c007feb18fa915e118e5f9740b21699bb' #edit this with the SHA hash that you generated after typing in Step 9
# This is the port we opened in Step 3.
c.NotebookApp.port = 8888
VERY IMPORTANT TO CHECK IF THERE IS ANY INDENTATION PROBLEM
and after ctrl+c and then ESC and then we type : :wq
11/ Create a folder for your notebooks and start Jupyter Notebook:
mkdir Notebooks
cd Notebooks
we can open Jupyter Notebooks:
jupyter notebook
12/ we can now access to the jupyter platform by typing in our browser :
https://ec2-34-245-19-198.eu-west-1.compute.amazonaws.com:8888/
we will arrive on a unsafe page but at the bottom expand and proceed to the website
DONT FORGET TO STOP THE INSTANCE WHEN YOU'VE FINISHED !
NEXT STEP :
you may want to save your models or objects to access them for later on another machine.
Also, you may need to import data from files on your machine to use on your EC2 notebooks.
To do this you just need the boto3 package and an S3 bucket. Setting up an S3 bucket is pretty simple and using boto3 is also very straight forward
so I will point you to boto3’s documentation for examples: https://boto3.readthedocs.io/en/latest/guide/quickstart.html#installation
And here’s AWS’s documentation for getting started with S3: https://aws.amazon.com/documentation/s3/
Just make sure to have your credentials properly stored. This is documented in the boto3 docs,
but you can also install the AWS CLI for easy configuration an access of AWS
from the command line: https://aws.amazon.com/cli/