widal001 / interview-scheduling Goto Github PK

Summary

Create a Matcher class with an match_interviews() method which takes a set of preferences and returns a set of interview assignments based on those preferences

Expected Behavior

• There's a class Matcher with the following attributes:
  • candidates - List of unique candidates
  • positions - List of unique positions
  • c_prefs - Dictionary of candidate preferences for each position
  • p_prefs - Dictionary of hiring manager preferences for each candidate by position
• The Matcher class has a match_interviews() method which accepts the following inputs:
  • Arguments
    • c_min - The minimum number of interviews a candidate must have to be considered "matched"
    • c_max - The minimum number of interviews a candidate can have
    • p_min - The minimum number of candidates that must be interviewing for a position in order for it to be considered "matched"
    • p_max - The maximum number of candidates that can interview for a position
  • Returns
    • self.c_matches
    • self.p_matches
    • self.c_remaining
    • self.p_remaining
    • self.logs

Summary

Add logging to the Matcher class to keep track of the steps that happen during the deferred acceptance algorithm

To Do

• Create a MatchLogger class
• Add logs for the following events:

Definition of Done

• Each step of the deferred acceptance algorithm is printed to the standard error
• A dictionary of the logs can be accessed from the MatchResult object returned by the

Summary

Create a class Scheduler and a method schedule_interviews() to schedule interviews based on mutual availability of candidates and hiring managers

Expected Behavior

• The __init__() method for Scheduler accepts the following inputs:
  • c_availability - Dictionary of candidate availability with following format {"candidate name": ["Block 1, "Block 2", "Block 3"]
  • p_availability - Dictionary of hiring manager availability by position with same format as c_availability
  • interviews - List of tuples that represent the candidate position pairing for each interview that needs to be scheduled
• The schedule_interviews() returns the following values
  • self.interview_schedule A dictionary that maps interview tuples to the blocks during which they'll occur

Summary

Complete the basic setup for the project

To Do

• Documentation
  • Build out README template
  • Create docs/ sub-directory
  • Add problem spec to docs/
• Development Environment
  • Create virtual environment
  • Install pytest
  • Install mdformat
  • Install and setup flake8
  • Install and setup black
  • Install and setup pre-commit hooks

Summary

Update repo structure to incorporate best practices from python boilerplate template project

To Do

• Convert to a poetry project
• Add code quality checks
  • tox
  • black
  • pylint
  • flake8
  • safety
  • liccheck
  • GitHub Actions
• Add collaboration docs and tools
  • adrs
  • LICENSE
  • CODE_OF_CONDUCT
  • CONTRIBUTING.md

Definition of Done

• New issues can be created from a template
• A contributor can install the project using poetry install
• Code quality checks are automatically run on pushes and pull requests
• Contributors can understand how to contribute to the project

Summary

Refactor algorithms to make them a bit more modularized and add Position and Candidate classes to reduce the amount of data stored directly on the Matcher and Scheduler class

To Do

• #9
• #10
  • Attributes
    • self.candidates List of candidates applying for the cohort
    • self.positions List of positions applying to be filled as part of the cohort
    • self.matcher Instance of the Matcher class used to assign interviews and placements
    • self.scheduler Instance of the Scheduler class used to schedule
  • Methods
    • self.assign_interviews() Assigns candidates to interviews with positions based on mutual rankings
    • self.schedule_interviews() Schedules the interviews assigned to time slots based on mutual availability
    • self.assign_placements() Assigns candidates to placements with positions based on mutual rankings
    • self.list_interviews() Returns the set of assigned interviews in the format specified
    • self.list_placements() Returns the set of assigned placements in one of a number of format
• #11
  • Attributes
  • Methods
• #12
  • Attributes
  • Methods
• #13
• #14

Definition of Done

• {Description of expected behavior once changes are made}
• {Description of expected behavior once changes are made}