DEV3L/twitter-learning-journal

Qualify learnings of a Twitter account as a learning journal

twitter-learning-journal

Qualify learnings of a Twitter account as a learning journal.

By doing this, there are a great deal of things we can measure!

• Articles words read
• Video minutes watched
• Audio minutes listened
• Book pages read
• Blogs published words
• Tweeted words

Plan

1. Scrape a twitter feed using Tweepy
   • Eventually need to get beyond 3k tweets
2. Classify tweets
   • Brute force at first, eventually algorithmic
3. Visualize the learning over time

Environment Variables

VARIABLE_NAME Default

• Twitter Api Credentials
  • TWITTER_ACCESS_TOKEN
  • TWITTER_CONSUMER_KEY
  • TWITTER_CONSUMER_SECRET
  • TWITTER_TOKEN_SECRET
• Logging
  • DEFAULT_LOGGING_FORMAT %(asctime)s - %(name)s - %(levelname)s - %(message)s
  • DEFAULT_LOGGING_LEVEL 20
• Pickle Cache Directories
  • CACHE_PATH ./data/pickle
  • WEBPAGE_CACHE_PATH ./data/pickle/web_pages/
  • TWEET_CACHE_PATH ./data/pickle/tweets/
  • GITHUB_CACHE_PATH ./data/pickle/tweets/

References

• Introduction to SQLite In Python
• SQLAlchemy Tutorial
• Python 3 Using 'yield from' In Generators
• Speeches: For the average person speaking at a normal pace, what is the typical number of words they can say in one minute?
  • "publishers recommend books on tape to be voiced at 150-160 wpm"

Contributing

1. Fork it!
2. Create your feature branch: git checkout -b my-twitter-learning-journal
3. Commit your changes: git commit -am 'Add something'
4. Push to the branch: git push origin my-twitter-learning-journal
5. Submit a pull request :D