Pre-v3.0 Epispot Roadmap

13 Feb 2021

Written By quantum9innovation

As of 2/13/21, latest release being v2.0.1 of epispot published to both Anaconda and PyPI, and awaiting the release of v3.0.0, here is the epispot project roadmap:

It’s February 13th, 2021 and epispot v3.0 is on the horizon. It’s also one of those times when a very special document is released detailing a project roadmap that will determine the fate of epispot forever. Our team has worked in 3 separate branches, pushed over 200 commits, merged plenty of pull requests, run the package more than a thousand times, created over 8 repos on the epispot organization account, and worked countless hours to automate, deploy, manage, maintain, improve, expand, and deliver the epispot package to over five thousand installers. Our work doesn’t end here–on the contrary, there’s a whole lot more to be done …

In Maintenance:

Automation:

• Automate release notes on master & nightly
• Automate documentation on master & nightly
• Dependabot automation everywhere
  

  Packaging:

• Automatic conda deployment on nightly
• Direct conda packaging (without conda-forge)?
  

  Issue Management:

• Automate issue labels
  

  Branch Management:

• Automatic code coverage reports on pull requests and commits
• Automate merge conflict resolutions for master→nightly
• Automate merge conflict resolutions for nightly→master
  

  In Development:

  
  

  Compartments:

• Vaccinated
• Severe
• Mild
• Immune
• Asymptomatic
• Quarantined
  

  Model Types:

• Cluster
• Probabilistic
• Monte-Carlo Simulation
• Large Area Simulation
  

  Small Updates:

• Anything?
  

  Major Changes:

• Demographic modeling within compartments
• More information on integrate()
  • inflection points
  • extrema
  • herd immunity markers
• Pre-built support for geographic modeling
  

  Integrations:

• Live COVID-19 data
• Live national cases data
• Live city/county data
  

  In Simulations:

  
  

  Small-Scale

• Use spatial models get to accurate small-scale predictions
• Implement in large cities:
  • San Francisco
  • London
  • Tokyo
  • New York
  • Mexico City
  • Mumbai
  • Add an open-source platform for more cities to be added
• Build a web dashboard
  

  Large-Scale

• Add large-scale modeling to CLI
• Implement a Cluster model to simulate travel across major hotspots
• Get a geographic model ready for world mapping
  

  Reproducable

• CLI!