#!/usr/bin/env python
# coding: utf-8

# ![Banner](../media/banner1.png)
# 
# ---
# # Workshop 1.1: <font color=peru>Jupyter Notebooks Introduction</font>
# * **Contributors**:
#     * Roberto Rodriguez (@Cyb3rWard0g)
#     * Jose Rodriguez (@Cyb3rPandah)
# * **Agenda**:
#     * [Overview](#overview)
#     * [Architecture](#architecture)
#     * [Deployment](#deployment)
#     * [Jupyter Flavors](#flavors)
# * **Notebook**: [https://aka.ms/Jupyterthon-ws-1-1](https://aka.ms/Jupyterthon-ws-1-1)
# * **License**: [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/)

# # <a style="border: solid; padding:5pt; color:black; background-color:#90CAF9" name="overview">Jupyter Notebooks Overview</a>

# # <font color=dimgray>Getting up to speed..</font>
# 
# ![](../media/day1/timeline-2021.png)

# # <font color=dimgray>Getting up to speed..</font>
# 
# ![](../media/day1/timeline-ipython-2021.png)

# # <font color=dimgray>What is Interactive Computing?</font>
# 
# An Interactive computation is a persistent computer program that runs with a **"human in the loop"** where the primary mode of steering the program is through the human iteratively writing/running blocks of code and looking at the result.
# 
# Reference:https://www.youtube.com/watch?v=YKmJvHjTGAM&list=PL055Epbe6d5aP6Ru42r7hk68GTSaclYgi&index=29

# # <font color=dimgray>Interactivity as a Protocol</font>
# * Read-Evaluate-Print Loop (REPL):
#   * Takes a single user’s inputs
#   * Evaluates them
#   * Returns the result to the user
# * A two-process model based on a kernel-client infrastructure
#   * Kernel: Executes code
#   * Client: Reads input and present output
#  

# # <font color=dimgray>IPython</font> 
# 
# * Released on Dec 10, 2001 by Fernando Perez while he was a graduate student at the University of Colorado
#   * Release: https://mail.python.org/pipermail/python-list/2001-December/093408.html
# * IPython as we know it today grew out of the following three projects:
#   * ipython by Fernando Pérez.
#   * IPP by Janko Hauser.
#   * LazyPython by Nathan Gray.
# 
# Reference: https://ipython.readthedocs.io/en/stable/about/history.html

# ![](../media/day1/python-ipython-notebook.png)
# Reference: https://ipython.readthedocs.io/en/stable/interactive/python-ipython-diff.html

# # <font color=dimgray>Fernando Perez Inspiration</font>
# * Research with open tools for access and collaboration
#   * Validated in SciPy India 2010 - Workshop to include students from underprivileged colleges in rural India.
# * Scientific
#   * Business of science is to understand nature
#   * Science is about opening up the black boxes nature
# * Community!
#   * SciPy: Scientists collaborating and building better tools together!
#   * Less competitions and more collaboration!
#   
# reference: https://www.youtube.com/watch?v=xuNj5paMuow&list=PL055Epbe6d5aP6Ru42r7hk68GTSaclYgi

# # <font color=dimgray>IPython -> Jupyter Project</font>
# 
# ![](../media/day1/ipython-to-jupyter.png)

# ![](../media/day1/ipython-features.png)
# 
# Reference: https://speakerdeck.com/fperez/project-jupyter?slide=5

# ![](../media/day1/ipython-jupyter-features.png)
# 
# Reference: https://speakerdeck.com/fperez/project-jupyter?slide=5

# # <font color=dimgray>What are Jupyter Notebooks?</font>
# 
# The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. The Jupyter notebook combines two components:
# 
# * **A web application**: a browser-based tool for interactive authoring of documents which combine explanatory text, mathematics, computations and their rich media output.
# * **Notebook documents**: a representation of all content visible in the web application, including inputs and outputs of the computations, explanatory text, mathematics, images, and rich media representations of objects.
# 
# Uses include:
# * Data cleaning and transformation
# * Statistical modeling
# * Data visualization
# * Machine learning, and much more
# 
# reference: https://jupyter.org/

# # <font color=dimgray>What does it look like?</font>

# In[1]:


print("Hola Roberto!")


# In[2]:


for x in range(5):
    print(x)


# ![](../media/day1/jupyter-notebooks-classic.png)

# # <a style="border: solid; padding:5pt; color:black; background-color:#90CAF9" name="architecture">Jupyter Notebook Architecture</a>

# # <font color=dimgray>Architecture (Interactive Protocol)</font>
# ![](../media/day1/jupyter-notebooks-architecture.png)
# 

# # <a style="border: solid; padding:5pt; color:black; background-color:#90CAF9" name="deployment">Jupyter Notebook Deployments</a>

# # <font color=dimgray>Installing Jupyter Notebooks (Manually)</font>
# 
# **Prerequisite**: Python
# 
# While Jupyter runs code in many programming languages, Python is a requirement (Python 3.3 or greater, or Python 2.7) for installing the JupyterLab or the classic Jupyter Notebook.
# 
# ## Classic Jupyter Notebook
# 
# **Using Mamba or Conda**
# 
# ```
# mamba install -c conda-forge notebook
# ```
# 
# ```
# conda install -c conda-forge notebook
# ```
# 
# **Using PIP**
# 
# ```
# pip install notebook
# ```
# 
# Once Jupyter Notebook is installed, you can run it with the following command:
# 
# ```
# jupyter notebook
# 
# ```

# # <font color=dimgray>Installing Jupyter Notebooks (Manually)</font>
# 
# **Prerequisite**: Python
# 
# While Jupyter runs code in many programming languages, Python is a requirement (Python 3.3 or greater, or Python 2.7) for installing the JupyterLab or the classic Jupyter Notebook.
# 
# ## JupyterLab
# 
# **Using Mamba or Conda**
# 
# ```
# mamba install -c conda-forge jupyterlab
# ```
# 
# ```
# conda install -c conda-forge jupyterlab
# ```
# 
# **Using PIP**
# 
# ```
# pip install jupyterlab
# ```
# 
# Once JupyterLab is installed, you can run it with the following command:
# 
# ```
# jupyter-lab
# 
# ```

# In[3]:


from IPython.display import YouTubeVideo

YouTubeVideo('KcoYnFVw9Xs', width=1000, height=800)


# # <font color=dimgray>Installing Jupyter Notebooks (Docker CE)</font>
# 
# **Prerequisite**: Docker CE
# 
# You just have to install the community edition of Docker, so that you can install JupyterLab from Docker images containing Jupyter applications and interactive computing tools.
# You can use a docker stack image to do any of the following (and more):
# 
# * Start a personal Jupyter Notebook server in a local Docker container
# * Run JupyterLab servers for a team using JupyterHub
# * Write your own project Dockerfile
# 
# You can use [ready-to-run Docker images](https://github.com/jupyter/docker-stacks) maintained by the Jupyter team:
# * Jupyter Github Docker Stacks project: https://github.com/jupyter/docker-stacks
# * Jupyter Docker registry: https://hub.docker.com/u/jupyter
# * Jupyter Docker Base Image: https://hub.docker.com/r/jupyter/base-notebook/
# 

# ## Running the Jupyter Base Notebook
# 
# ```
# docker run -p 8888:8888 jupyter/minimal-notebook:3b1f4f5e6cc1
# ```

# In[2]:


from IPython.display import YouTubeVideo

YouTubeVideo('KVR1_cVlLRE', width=1000, height=800)


# ## Jupyterthon - OTRF Docker Image
# 
# ```
# docker run -ti --rm -p 8888:8888 otrf/jupyterthon:2021
# ```

# # <font color=dimgray>Jupyter Hub</font>
# JupyterHub is a set of processes that together provide a single user Jupyter Notebook server for each person in a group. Three major subsystems are started by the jupyterhub command line program:
# 
# * **Hub (Python/Tornado)**: manages user accounts, authentication, and coordinates Single User Notebook Servers using a Spawner.
# * **Proxy**: the public facing part of JupyterHub that uses a dynamic proxy to route HTTP requests to the Hub and Single User Notebook Servers. configurable http proxy (node-http-proxy) is the default proxy.
# **Single-User Notebook Server (Python/Tornado)**: a dedicated, single-user, Jupyter Notebook server is started for each user on the system when the user logs in. The object that starts the single-user notebook servers is called a Spawner.
# 
# Reference: https://jupyterhub.readthedocs.io/en/latest/reference/technical-overview.html
# 
# ![](../media/day1/jupyter-hub-subsystems.png)

# # <font color=dimgray>Enter Binder Project</font>
# 
# * Released in May, 2016
# * Updated 2.0 on November, 2019
# * The Binder Project is an open community that makes it possible to create shareable, interactive, reproducible environments.
# * The main technical product that the community creates is called BinderHub, and one deployment of a BinderHub exists at mybinder.org.
# * Who is it for?: 
#   * Researchers, Educators, people analyzing data and people trying to communicate the data analysis to others!!

# # <font color=dimgray>BinderHub</font>
# 
# BinderHub connects several services together to provide on-the-fly creation and registry of Docker images. It utilizes the following tools:
# * A cloud provider such Google Cloud, Microsoft Azure, Amazon EC2, and others
# * Kubernetes to manage resources on the cloud
# * Helm to configure and control Kubernetes
# * Docker to use containers that standardize computing environments
# * A BinderHub UI that users can access to specify Git repos they want built
# * BinderHub to generate Docker images using the URL of a Git repository
# * A Docker registry (such as gcr.io) that hosts container images
# * JupyterHub to deploy temporary containers for users

# # <font color=dimgray>BinderHub Flow</font>
# 
# ![](../media/day1/Binderhub-Architecture.png)

# # <font color=dimgray>Let's Try it!</font>
# ![](../media/day1/interactive-example.png)

# # <font color=dimgray>JupyterLab Desktop App</font>
# 
# * Released in September 2021.
# * Cross-platform standalone application distribution of JupyterLab.
# * Desktop app which bundles a Python environment (bundled conda Python env) with popular Python libraries (Numpy, scipy, pandas, ipywidgets and matplotlib).
# * Based on Electron with a front-end of JupyterLab inside an embedded browser.

# In[4]:


from IPython.display import YouTubeVideo

YouTubeVideo('1g1c81YTONo', width=1000, height=800)


# # <a style="border: solid; padding:5pt; color:black; background-color:#90CAF9" name="flavors">Jupyter Notebooks Flavors</a>

# # <font color=dimgray>Classic Jupyter Notebook</font>
# 
# ```
# docker run -ti --rm -p 8888:8888 otrf/jupyterthon:2021
# ```
# 
# ![](../media/day1/jupyter-notebook-classic.png)

# # <font color=dimgray>JupyterLab</font>
# 
# ```
# docker run -ti --rm -e JUPYTER_ENABLE_LAB=yes -p 8888:8888 otrf/jupyterthon:2021
# ```
# 
# ![](../media/day1/jupyterLab.png)

# # <font color=dimgray>VSCode Jupyter Notebook</font>
# 
# * Visual Studio Code
# * Python Extension for Visual Studio Code
# * Python Interpreter: you can find the steps to install it here.
# 
# **References**:
# * https://blog.openthreatresearch.com/first_jupyter_notebook_vscode
# * https://blog.openthreatresearch.com/installing_python_extension_vscode

# In[5]:


from IPython.display import YouTubeVideo

YouTubeVideo('4LrBMHL69VI', width=1000, height=800)


# # <font color=dimgray>Resources</font>
# 
# * https://the-turing-way.netlify.app/introduction/introduction.html
# * https://gist.github.com/fperez/1579699 
# * https://mail.python.org/pipermail/python-list/2001-December/093408.html 
# * https://ipython.org/news.html#ipython-0-12 
# * https://speakerdeck.com/fperez/project-jupyter 
# * https://blog.jupyter.org/rendering-notebooks-on-github-f7ac8736d686 
# * https://blog.jupyter.org/binder-2-0-a-tech-guide-2017-fd40515a3a84 
# * https://jupyterbook.org/intro.html
# * https://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html#pip
# * https://github.com/jupyter/docker-stacks
# * http://ipython.org/news
# * https://pypi.org/project/jupyterlite/#history
# * https://blog.jupyter.org/jupyterlite-jupyter-%EF%B8%8F-webassembly-%EF%B8%8F-python-f6e2e41ab3fa
# * https://github.com/jupyterlab/jupyterlab-desktop#download
# * https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a
# * https://elifesciences.org/labs/a7d53a88/toward-publishing-reproducible-computation-with-binder
# * https://tljh.jupyter.org/en/latest/

# # <font color=peru>Break: 5 Minutes</font>
# 
# ![](../media/dog-leash-break.jpg)