Raspberry pi full stack course

 What Will I Learn?

• Setup the minimal Raspbian operating system to the RPi.
• Install the a Python virtual environment.
• Install and use Flask, a Python-based web micro-framework
• Install and use uWSGI as the application server for Flask
• Install and use Nginx light-weight web server
• Use the RPi GPIOs as digital input and outputs
• Use a DHT22 humidity and temperature sensor
• Install and use the SQLite database
• Use the Google Chart API to create visual representations of the sensor data
• Use JQuery to add interactivity to web pages
• Use Plotly for graphical analysis of sensor data
• Install and configure a USB Wifi adaptor for your RPi

Requirements:

• A Raspberry Pi, any version
• A Windows, Mac or Linux computer
• A DHT11 or DHT22 sensor
• An 5mm LED
• Resistors
• A breadboard and jumper wires
• Access to the Internet
• A USB Wifi dongle, if available

Who is the target audience?

• Some experience in programming is useful.
• Python, Javascript (jQuery) and HTML is used throughout the course and some familiarity with basic programming concepts is expected.
• Ability to wire electronics.
• Ability to do independent research using online resources

Introduction to the course:

• Introduction
• About the Raspberry Pi
• Components
• Detailed List of Components you will need

The Operating System:

• Section Introduction
• How to extract a tar.gz file
• Installing mini Raspbian using Mac OS X
• Installing mini Raspbian using Windows

Python and GPIOs:

• Section Introduction
• Setup Python
• GPIO basics
• Make an LED blink
• Read the status of a button
• Read temperature and humidity from a digital sensor

Setup the Web application stack:

• Setup the Web application stack
• Section Introduction
• What is the Web application stack?
• Install Nginx, the Web server
• Install Flask and venv
• Install uWSGI
• Setup Upstart
• About log files
• Serving static assets and Skeleton
• Styling our Web application with Skeleton
• Debugging a Flask application

Building a simple Flask application on the Raspberry Pi:

• Section Intro
• Show DHT22 sensor data in the browser
• Install the SQLite3 database
• Use a Python script to store sensor reading to the database
• Automate sensor data logging with cron and SQLite3
• Show historical sensor data in the browser

Improving our application with date-time range record selector:

• Section Introduction
• Selecting historical sensor data records with a time-date range
• Define a date-time range in the URL
• Timezones in Rasbian
• Validating timestamps
• Tidying up: refactor our application code

Improving the user interface:

• Section Introduction
• Adding date range radio buttons
• Visualise sensor data with Google Charts
• Install a datetime picker widgets
• Setting up the datetime picker widget
• Setting up time zones on the client side
• Setting up time zones on the server side
• Link the two pages of the application

Setup cloud charting and analysis with Plotly:

• Section Introduction
• Setup Plotly
• Add Plotly links
• Add Plotly support to the Flask application script

Other useful things to know:

• Install and configure a Wifi USB dongle for wireless networking