how_many_tickets.py

import os
from datetime import datetime, timezone

from dotenv import load_dotenv
from jira import JIRA


def before_and_after_deadline(issues, deadline):
    # just a reference date I've already noted before
    sprint_239_start_datetime = datetime(
        year=2021,
        month=1,
        day=26,
        hour=0,
        minute=0,
        second=0,
        tzinfo=timezone.utc,
    )

    before_deadline = 0
    after_deadline = 0

    for issue in issues:
        created = datetime.strptime(issue.fields.created, "%Y-%m-%dT%H:%M:%S.%f%z")
        time_passed_between_sprint_239_and_created = created - sprint_239_start_datetime
        sprints_passed = int(time_passed_between_sprint_239_and_created.days / 14)
        created_on_sprint_day_number = time_passed_between_sprint_239_and_created.days - sprints_passed * 14

        if created_on_sprint_day_number > deadline:
            after_deadline += 1
        else:
            before_deadline += 1

    return before_deadline, after_deadline


load_dotenv()

username = os.getenv("JIRA_USERNAME")
password = os.getenv("JIRA_PASSWORD")

jira = JIRA("https://tasks.opencraft.com", auth=(username, password))

issues_before_change = jira.search_issues('project = Bebop and createdDate >= "2023-07-05" and createdDate < "2023-12-05"', maxResults=1000)
issues_after_change = jira.search_issues('project = Bebop and createdDate >= "2023-12-05"', maxResults=1000)

# don't ask why Sunday is 12 and not 14, just trust me
sunday_w2 = 12

before_deadline_before_change, after_deadline_before_change = before_and_after_deadline(issues_before_change, sunday_w2)
before_deadline_after_change, after_deadline_after_change = before_and_after_deadline(issues_after_change, sunday_w2)

print(
    f"Before change: {before_deadline_before_change} issues created before Monday W3,"
    f"{after_deadline_before_change} issues created on Monday W3,"
    f"which is {after_deadline_before_change / (after_deadline_before_change + before_deadline_before_change) * 100}% of all issues."
)
print(
    f"After change: {before_deadline_after_change} issues created before Monday W3,"
    f"{after_deadline_after_change} issues created on Monday W3,"
    f"which is {after_deadline_after_change / (after_deadline_after_change + before_deadline_after_change) * 100}% of all issues."
)