vkd225 / vested-shares

Calculate vested shares

This package calculates vested shares for an organization. The main file is vesting_program.py file. It takes 3 arguments

• Arg1: filepath
• Arg2: date (YYYY-MM-DD)
• Arg3: precision (optional field)

Usage

./vesting_program.py --help

Running script

open terminal and cd into the project directory

./vesting_program.py filepath/filename.csv date

I have included a few test files to run the program with.

• run ./vesting_program.py tests/example1.csv 2021-01-01 to test example1.csv file

Please replace example1.csv with other files you would like to test from.

If you would like to write the data to a new csv output file then please uncomment the last two lines of vesting_program.py file.

f = File()
f.write_data_to_csv(vested_share_data)

To run tests

I have also added a few test cases to to test different functions and inputs of the program

• run ./test.py -b

To get doc strings of all classes and methods

• run ./doc_strings.py

Sub modules

I have created 3 sub modules: helper, validator and default

helper module

• It has classes and methods to help with file class like opening, reading data, writing data to another file and closing.

• It also has helper classes to calculate toatal share based on some share event.

• It helps generating precise number without rounding off

validator module

• This submodule helps with input parameters and rows of the input file

default module

• Generates default values of vested shares.

Assumptions

List of some of the assumptions that I have made to solve the give problem.

• Assumed that the total vested shares cannot be negative. Hence, if the toatal is negative, it is going to return 0.
• Employee_id is case sensitive i.e. if the employee_id of same id but different case is found, the program is going to treat it differently.
• Award_id is case sensitive i.e. if the award_id of same id but different case is found, the program is going to treat it differently.
  • Different cases (lowercase or uppercase) for employee_id and award_id means multiple input.
• Name of the Employee encountered first is set and if the name is diffrent in different row, that is disregarded.
• Assumed that the only valid date format is YYYY-MM-DD.

Future work

In future we can modify the program to run it using parallel processing. We can process the csv file in multiple smaller chunks. For eg: We can process the file from top lenght_of_rows/2 in one process and bottom lenght_of_file/2 in a separate process. After processing the entire file, we can merge the vested_shares hash maps which would be created by these processes. Since the key (award_id, employee_id ) would be unique, we can just add the total award quantity of keys (award_id, employee_id ) form one dictionary into another.

We can do the same parallel processing logic and have more than 2 processes as well.