New code will be posted over at Github!
​Earlier code is still available on Github in the form of gists.

The following code can be used to:
​1) Generate a list of words within a given frequency class (or a mix of frequency classes) from the ​SUBTLEXus database of word frequencies.
2) Automatically analyze the properties of a given list, including:

• word frequency
• word length
• letter n-gram frequency
  

3) Compare a set of n lists on these same properties, as well as:

• orthographic similarity (Levenshtein edit distance)
• semantic similarity (word2vec)

This demo script shows how tools from the Pandas library can be used to quickly and efficiently process experimental data generated with PsychoPy.

​The following code illustrates how to write a Twitter bot that automatically finds relevant users to follow, and unfollows users that haven't followed back. In the example usage, the bot intakes a seed list of influencers and harvests information about their followers. It then selectively follows a subset of the most relevant users, given a set of customizable conditions (e.g., language, keywords, Tweet frequency). In keeping with API limits, the bot auto-follows 250 new users at a time, caching a "blacklist" of users that have already been added.