Pull the number of weekly done issues out of JIRA for use as forecasting samples

jira-weekly-samples.py

from jira import JIRA
import arrow
from datetime import timedelta

DONE_ISSUES_QUERY = 'statusCategory = done'
SAMPLES=24

jira = JIRA()

dates = []
max_results = 50
start_at = 0
while True:
    issues = jira.search_issues(DONE_ISSUES_QUERY, maxResults=max_results, startAt=start_at)
    num_issues = len(issues)
    for issue in issues:
        dates.append(arrow.get(issue.fields.resolutiondate))
    if num_issues < max_results:
        break
    else:
        start_at += max_results

end = arrow.get()
end = end.replace(hour=0, minute=0, second=0, microsecond=0)
end = end - timedelta(days=end.weekday())

curr = end - timedelta(weeks=SAMPLES)

while (curr < end):
    range_min = curr
    range_max = range_min + timedelta(days=7)
    count = 0
    for date in dates:
        if date > range_min and date < range_max:
            count += 1
    print(count)
    curr = range_max