  Twitter is perhaps the social media more amenable for research. It requires
only a few steps to obtain information, and there are plenty of libraries that
can help in this regard. Nonetheless, knowing whether a particular event is
expressed on Twitter is a challenging task that requires a considerable
collection of tweets. This proposal aims to facilitate, to a researcher
interested, the process of mining events on Twitter by opening a collection of
processed information taken from Twitter since December 2015. The events could
be related to natural disasters, health issues, and people's mobility, among
other studies that can be pursued with the library proposed. Different
applications are presented in this contribution to illustrate the library's
capabilities: an exploratory analysis of the topics discovered in tweets, a
study on similarity among dialects of the Spanish language, and a mobility
report on different countries. In summary, the Python library presented is
applied to different domains and retrieves a plethora of information in terms
of frequencies by day of words and bi-grams of words for Arabic, English,
Spanish, and Russian languages. As well as mobility information related to the
number of travels among locations for more than 200 countries or territories.
