A Python script that extracts SR&ED (Scientific Research and Experimental Development Tax Incentive Program) data from a Jira generated JSON file. See http://www.cra-arc.gc.ca/txcrdt/sred-rsde/menu-eng.html for details on SR&ED. It gathers "Start Date", "Resolution Date" and "# of People" and calculates the "Person Weeks" for each Jira Story.

SR_ED.py

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# SR&ED DATA GENERATOR
# ====================
# 1.- Use the Jira REST API to grab the JSON data that belongs to a given Epic:
#       https://your-jira-instance.com/rest/api/2/issue/115515?expand=changelog
# 2.- Save the JSON object in a .json file in the same folder as this script
# 3.- Repeat #1 and #2 as many times as Jira Epics you want to process
# 4.- Run this script
# 5.- The output data will be in the output.csv file. Same folder.

import json
import math
import csv
import os

from datetime import datetime, timedelta
from pprint import pprint

weeks_map = dict()
people_map = dict()

def dt_parse(t):
    # From http://stackoverflow.com/questions/26165659/python-timezone-z-directive-for-datetime-strptime-not-available
    ret = datetime.strptime(t[0:16],'%Y-%m-%dT%H:%M')
    if t[18]=='+':
        ret-=timedelta(hours=int(t[19:22]),minutes=int(t[23:]))
    elif t[18]=='-':
        ret+=timedelta(hours=int(t[19:22]),minutes=int(t[23:]))
    return ret

def get_week(t):
    return dt_parse(t).isocalendar()[1]

def get_weeks(d1, d2):
    # Returns the difefrence between 2 dates (in weeks)
    # Result is rounded up, so something that is less than a week
    # counts as 1 week.
    if d1 is None or d2 is None:
        return 0
    d1 = dt_parse(d1)
    d2 = dt_parse(d2)
    return math.ceil((d2 - d1).total_seconds() / 604800)

def get_people(list_of_people, start, end):
    out = dict()
    for person in list_of_people:
        out[person] = get_person_weeks(get_week(start), get_week(end), person)
    return json.dumps(out)

def get_person_weeks(start_week, end_week, person):
    worked = 0
    for week in range(start_week, end_week + 1):
        people_from_this_week = weeks_map.get(str(week))
        if people_from_this_week is None:
            people_from_this_week = []
        if person.lower() not in people_from_this_week:
            # Increase the counter for this person
            worked = worked + 1
            # Add the person to the array
            people_from_this_week.append(person.lower())
            weeks_map[str(week)] = people_from_this_week
    # Increment the global summary
    if people_map.get(person) is None:
        people_map[person] = 0
    people_map[person] = people_map[person] + worked
    # Return the count for the given range
    return worked

# Generate the CSV file and add headers to it
output = csv.writer(open("output.csv","w"), delimiter=',',quoting=csv.QUOTE_ALL)
headers = [
    'epic_key',
    'story_key',
    # 'assigned_date',
    'into_progress_date',
    'resolution_date',
    # 'weeks',
    '# of people',
    'people'
]
output.writerow(headers)

# find the JSON files to be used as input
files = [f for f in os.listdir('.') if os.path.isfile(f)]
for f in files:
    if f.endswith('.json'):
        # Parse the JSON file
        with open(f) as data_file:
            try:
                data = json.load(data_file)
                # Go over the tickets that belong to a given epic
                for issue in data['issues']:
                    issue_key = issue['key']
                    issue_histories = issue['changelog']['histories']
                    resolution_date = issue['fields']['resolutiondate']
                    result = {
                        'epic_key': f,
                        'issue_key': issue_key,
                        'assigned_date': None,
                        'into_progress_date': None,
                        'resolution_date': resolution_date,
                        'people': [],
                        'weeks': 0.0
                    }
                    # Go through the changelog for this particualr ticket
                    for history in issue_histories:
                        for event in history['items']:
                            if event['fromString'] == 'To Do'and event['toString'] == 'In Progress':
                                # When did we actually star working on this ticket?
                                into_progress_date = history['created']
                                result['into_progress_date'] = into_progress_date
                            elif event['field'] == 'assignee' and event['from'] is None:
                                # See when the assignement happened,
                                # and who worked on the ticket
                                assigned_date = history['created']
                                result['assigned_date'] = assigned_date
                                dev_person = event['to']
                                if dev_person not in result['people']:
                                    result['people'].append(dev_person.lower())
                            elif event['field'] == 'resolution':
                                # Who is the QA person?
                                qa_person = history['author']['name']
                                if qa_person not in result['people']:
                                    result['people'].append(qa_person.lower())
                    # Build a result object
                    result['weeks'] = get_weeks(result['into_progress_date'],
                                                result['resolution_date'])
                    # Add a row to the CSV file if applicable
                    if result['into_progress_date'] is not None:
                        csv_row = [
                            result['epic_key'],
                            result['issue_key'],
                            # result['assigned_date'],
                            result['into_progress_date'],
                            result['resolution_date'],
                            # result['weeks'],
                            len(result['people']),
                            get_people(result['people'], result['into_progress_date'], result['resolution_date'])
                        ]
                        output.writerow(csv_row)
            except Exception as e:
                # Deal with errors and move along!
                print "We had a problem with " + f
                print e
print ''
print 'SUMMARY'
print '========'
pprint(people_map)