Social Media Ticker

Table of Contents

• 1) Hardware
  • 1.1) Hardware Requirements
  • 1.2) Hardware Setup
• 2) Software
  • 2.1) Install Dependencies
  • 2.2) Add tokens
  • 2.3) Running the Bot

1) Hardware

1.1) Hardware Requirements

• Any 96Boards CE
• SeeedStudio Sensors Mezzanine
• 5x MAX7219 LED Matrix Modules
• SSD1306 OLED 128x64

1.2) Hardware Setup

• Connect all the LED matrix Modules in a daisy-chain configuration
• Connect the Sensor Mezzanine to the first LED Matrix Module as follow:

Sensor Mezzanine	MAX7219 LED Matrix
5v	VCC
GND	GND
11	DI (MOSI)
10	CS
13	CLK

• Connect the OLED Module as follow:

Sensor Mezzanine	SSD1306 OLED
5v	VCC
GND	GND
SDA	SDA
SCL	SCL

• I used ICSP to program the SeeedStudio Mezzanine. You can follow this guide.

2) Software

This guide assumes that Debian OS is running on a Dragonboard410c on all 4 nodes. How ever the instructions hold true for other 96Boards CE Boards running Debian.

This project is compatible with other Linux based OS, but they might have to be tweaked accordingly.

2.1) Install Dependencies

$ sudo apt install python-setuptools python-dev python-pip
$ sudo pip install wheel tweepy requests serial

2.2) Add tokens

• Twitter

  • Create a developer account at: https://developer.twitter.com/en/apply/user
  • Get access token: https://developer.twitter.com/en/docs/basics/authentication/guides/access-tokens.html
  • Set <twconsumer_key> in ticker.py with your Twitter Consumer Key.
  • Set <twconsumer_secret> in ticker.py with your Twitter Consumer Secret Key.
  • Set <twaccess_token> in ticker.py with your Twitter access token.
  • Set <twaccess_token_secret> in ticker.py with your Twitter access token secret key.

• YouTube

  • Follow Google's official guide to generate API key.
  • Set in ticker.py with your YouTube API Key.

2.3) Running the Ticker

• Flash the Sensors Mezzanine with ticker.ino

Test Run

You can run it simply as

$ python ticker.py

Deploy

From Shell

$ python ticker.py &