Package: mercury-reels
Mercury ReelsWhat is this?TLDR: Reels helps identify patterns in event data and can predict target events.Reelsis a library to analyze sequences of events extracted from transactional data. These events can be automatically discovered
or manually defined.Reelsidentifies events by assigning themevent codesand createsclips, which are sequences of(code, time of occurrence)tuples for eachclient. Using these clips, a model can be generated to predict the time at whichtarget eventsmay occur in the future.What problems is REELS good for?Reels was born to analyze web navigation transactional data. It has natural applications in cybersecurity and everywhere where predictingeventsor scoringrisk of eventsbased on past events makes sense. The definition ofrelevant eventmay be discovered from
transactional data or is established as business domain knowledge. It can also be semi-automated using Reels event optimizer to iterate
and learn how events predict a target.What data size can reels tackle?Reels is a C++ implementation with a Python interface. It is single threaded and can seamlessly operate over millions of clients and
billions of records with hundreds of thousands of events. To further parallelize, it can partition the data by dividing the set of
clients into smaller subsets and operate on each subset independently.I already have time series and sequence prediction tools, why would I need another one?Reels is oriented towardsevents(as opposed to continuous variables like a price).Even when your problem is better seen as time series, Reels predictions can be used as features to boost another model.Supports manual, full automatic or assisted definition of what relevant (predictive) events are.Predicts a target event within or outside the transactional dataset.Highly efficient C++ implementation.100% pythonic interface: objects are serializable, use iterators, interfaces with pandas and pyspark.The Python APIReels is implemented in four classes.The Events classPython APIC++ APIThe Clients classPython APIC++ APIThe Clips classPython APIC++ APIThe Targets classPython APIC++ APITry it without any installation on Google ColabIntroductory: A walk through ReelsAdvanced: Event optimization -- How to do assisted event discoveryInstallpipinstallmercury-reelsClone and set up a development environment to work with itTo work with Reels command line or develop Reels, you can set up an environment with git, gcc, make and the following tools:catch2 (Already included in source code)doxygen 1.9.5 or better (to render C++ documentation)mkdocs 1.4.2 or better (to render Python documentation)swig 4.0.2python 3.x with appropriate paths to python.h (see Makefile)gitclonehttps://github.com/BBVA/mercury-reels.gitcdmercury-reels/src

makeMake without arguments gives help. Try all the options. Everything should work assuming the tools are installed.DocumentationPython APIC++ APILicenseApache License
                   Version 2.0, January 2004
                http://www.apache.org/licenses/

     Copyright 2022-23, Banco de Bilbao Vizcaya Argentaria, S.A.

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0