Grooming for issues

issues.py

#!/home/andrea/.local/share/miniconda3/bin/python

# Installation 
# 
# python dependencies
# pip3 install jira questionary
# 
# create the env var to connect to jira 
# export [email protected]
# export JIRA_TOKEN=***
# export JIRA_HOST=https://MYORG.atlassian.net

# https://jira.readthedocs.io/
from jira import JIRA
import os
import datetime
import questionary

import json

def get_client():
    user = os.getenv("JIRA_USER")
    token = os.getenv("JIRA_TOKEN")
    host = os.getenv("JIRA_HOST")
    return JIRA(server=host, basic_auth=(user, token))


def to_date(date_string):
  return datetime.datetime.fromisoformat(date_string)

def main():
    client = get_client()

    priority_weight = {
        "Lowest": 1000,
        "Low": 500,
        "Medium": 100,
        "High": 50,
        "Highest": 10
    }

    # the query is to get all open issues and re-prioritize them
    q = 'project = "MOON" and status in (Triage) ORDER BY created DESC'
    print(f"JQL:\n {q}")


    # do_update = questionary.confirm("Do you want to update the issues?", default=False).ask()
    do_update = False


    options = {"Top 5": 5, "Top 10": 10, "Top 20": 20, "All": None}
    howMany = questionary.select(
        "How many issues do you want to see?",
        choices=options,
        use_shortcuts=True
    ).ask()

    issues = []

    for issue in client.search_issues(q, maxResults=None):
        age = (datetime.datetime.now(tz=datetime.timezone.utc) - to_date(issue.fields.updated)).days
        weight = priority_weight[issue.fields.priority.name]
        score = weight * age
        issues.append({"key": issue.key, "score": score, "_age": age, "_weight": weight, "_priority": issue.fields.priority.name, "_updated": issue.fields.updated})
        if do_update:
            client.update(issue.key, fields={"priority": {"name": "High"}})

    # sort the issues by score
    issues.sort(key=lambda x: x.get("score", 0), reverse=False)


    print(f"{'Key':10} | {'Score':10} | {'URL'}")
    for record in issues[-options[howMany]:]:

        print(f'{record["key"]:10} | {record["score"]:10.0f} | {os.getenv("JIRA_HOST")}/browse/{record["key"]}')
        #print(f'{record["key"]:10} [{record["score"]:10.0f}]  ({record["_priority"]} {record["_age"]} {record["_weight"]} {record["_updated"]})')
    print(f"{'Total':10} | {issues.__len__():10.0f}")
        # client.update(fields={"priority": {"name": "High"}})




# Story points per release per user
def get_story_points_per_release_per_user():
    STORY_POINT_ESTIMATE_FIELD = "customfield_10016"

    client = get_client()
    # list the releases
    releases = client.project_versions("MOON")
    releases.sort(key=lambda x: x.raw.get("releaseDate", "5000-01-01"), reverse=True)

    do_select_release = True

    while do_select_release:
        # select the release
        selected = questionary.checkbox("Select the release", choices=[release.name for release in releases]).ask()
        if selected.__len__() == 0:
            print("at least one release must be selected")
            continue
        # get the issue for the release

        q = f'project = "MOON" and fixVersion in ({",".join(selected)}) and type != Epic'
        print(f"JQL:\n {q}")
        # "user": {"story_points": 0, "issues": 0}
        metrics_by_user = {}

        for issue in client.search_issues(q):
            sp = issue.get_field(STORY_POINT_ESTIMATE_FIELD) or 0
            if sp == 0:
                print(f'⚠️ issue {os.getenv("JIRA_HOST")}/browse/{issue.key} has no story points {issue.fields.creator.displayName}')

            assignee = issue.get_field("assignee")
            if assignee is None:
                print(f'⚠️ issue {os.getenv("JIRA_HOST")}/browse/{issue.key} has no assignee')
                assignee = "Unassigned"
            else:
                assignee = assignee.displayName

            data = metrics_by_user.get(assignee, {"story_points": 0, "issues": 0})
            data["story_points"] += sp
            data["issues"] += 1
            metrics_by_user[assignee] = data

        # transform the dictionary into a list
        # sort the list by story points
        summary = sorted([{'n': k, 'p': v['story_points'], 'i': v['issues']} for k,v in metrics_by_user.items()], key=lambda x: x["p"], reverse=True)

        print(f'Summary for version ({",".join(selected)})')
        print(f"{'User':20s} | {'Story Points':15s} | {'Issues':10s}")
        print("-" * 50)
        sum_story_points = 0
        sum_issues = 0
        for record in summary:
            sum_story_points += record["p"]
            sum_issues += record["i"]
            print(f'{record["n"]:20s} | {record["p"]:15.0f} | {record["i"]:10.0f}')
        print("-" * 50)
        print(f"{'Total':20s} | {sum_story_points:15.0f} | {sum_issues:10.0f}")

        do_select_release = questionary.confirm("Do you want to select another release?").ask()


if __name__ == '__main__':

    opt1 = "Re-prioritize issues"
    opt2 = "Analyze release story points"


    answer = questionary.select(
        "Select the action",
        choices=[opt1, opt2],
        use_shortcuts=True
    ).ask()

    if answer == opt1:
        main()
    elif answer == opt2:
        get_story_points_per_release_per_user()
    else:
        print("Invalid option")