sd-metrics-lib 1.1

Library to calculate various metrics of software development process

sd-metrics-lib

Python library for calculation of various metrics related to software development process. Provides user velocity calculation based on data from Jira. Metrics calculation classes are using interfaces, so it could be easily extended with another data providers, like Trello, Asana etc. from application code.

Implementation notes

General architecture is simple and has 2 main parts:

• calculators package:
  • UserVelocityCalculator class calculates user velocity or developer performance in other words. Requires IssueProvider, StoryPointExtractor and WorklogExtractor for calculation.
  • GeneralizedTeamVelocityCalculator class calculates team generalized velocity. Requires IssueProvider, StoryPointExtractor and IssueTotalSpentTimeExtractor for calculation.
• data_providers package:
  • IssueProvider interface designed to provide issues/tickets for calculators.
    • JiraIssueProvider implementation class, which fetches issues from Jira by JQL using jira client from atlassian-python-api.
    • ProxyIssueProvider wrapper for issues fetched from another data providers.
  • StoryPointExtractor interface designed to extract "story points" from issue.
    • JiraCustomFieldStoryPointExtractor implementation class, which extract value of custom field from Jira.
    • JiraTShirtStoryPointExtractor implementation class, which extract value of custom field from Jira and maps string value into numbers.
  • WorklogExtractor interface designed to extract amount of time users spent on ticket.
    • JiraWorklogExtractor implementation class, which uses regular jira work log entries to define user spent time.
    • JiraStatusChangeWorklogExtractor implementation class, which uses issue status change history log to define user spent time on issue.
    • ChainedWorklogExtractor implementation class, which allows "chain" WorklogExtractor to execute them one by one.

Also library provides few util classes:

• JiraIssueSearchQueryBuilder builder for JQL queries.
• TimeRangeGenerator generator for time ranges. Useful for filtering by resolution date to calculate velocity for set of period of time.

Code examples

Calculate amount of tickets developer resolves per day based on Jira ticket status change history.

This code should work on any project and give at least some data for analysis.

from atlassian import Jira

from calculators import UserVelocityCalculator
from calculators.velocity_calculator import VelocityTimeUnit
from data_providers.jira.issue_provider import JiraIssueProvider
from data_providers.jira.worklog_extractor import JiraStatusChangeWorklogExtractor
from data_providers.story_point_extractor import ConstantStoryPointExtractor

JIRA_SERVER = 'server_url'
JIRA_LOGIN = 'login'
JIRA_PASS = 'password'
jira_client = Jira(JIRA_SERVER, JIRA_LOGIN, JIRA_PASS, cloud=True)

jql = " project in ('TBC') AND resolutiondate >= 2022-08-01 "
jql_issue_provider = JiraIssueProvider(jira_client, jql, expand='changelog')

story_point_extractor = ConstantStoryPointExtractor()
jira_worklog_extractor = JiraStatusChangeWorklogExtractor(['In Progress', 'In Development'])

velocity_calculator = UserVelocityCalculator(issue_provider=jql_issue_provider,
                                             story_point_extractor=story_point_extractor,
                                             worklog_extractor=jira_worklog_extractor)
velocity = velocity_calculator.calculate(velocity_time_unit=VelocityTimeUnit.DAY)

print(velocity)

Calculate amount of story points developer resolves per day based on Jira worklog.

This code will provide good enough dev performance metrics on projects, where worklog and story points are entered in Jira.

from atlassian import Jira

from calculators import UserVelocityCalculator
from calculators.velocity_calculator import VelocityTimeUnit
from data_providers.jira.issue_provider import JiraIssueProvider
from data_providers.jira.worklog_extractor import JiraWorklogExtractor
from data_providers.jira import JiraCustomFieldStoryPointExtractor

JIRA_SERVER = 'server_url'
JIRA_LOGIN = 'login'
JIRA_PASS = 'password'
jira_client = Jira(JIRA_SERVER, JIRA_LOGIN, JIRA_PASS, cloud=True)

jql = " project in ('TBC') AND resolutiondate >= 2022-08-01 "
jql_issue_provider = JiraIssueProvider(jira_client, jql)

story_point_extractor = JiraCustomFieldStoryPointExtractor('customfield_10010')
jira_worklog_extractor = JiraWorklogExtractor(jira_client)

velocity_calculator = UserVelocityCalculator(issue_provider=jql_issue_provider,
                                             story_point_extractor=story_point_extractor,
                                             worklog_extractor=jira_worklog_extractor)
velocity = velocity_calculator.calculate(velocity_time_unit=VelocityTimeUnit.DAY)

print(velocity)

Version history

1.1

• (Feature) Add team velocity calculator.
• (Improvement) Add JQL filter for last modified data.
• (Bug Fix) Fix wrong user resolving in JiraStatusChangeWorklogExtractor.
• (Bug Fix) Fix resolving more time than spent period of time.
• (Bug Fix) Fix Jira filter query joins without AND.

1.0.3

• (Improvement) Add JiraIssueSearchQueryBuilder util class.
• (Improvement) Add TimeRangeGenerator util class.
• (Bug Fix) Fix filtering by status when no status list passed.

1.0.2

• (Bug Fix) Fix package import exception after installing from pypi.

1.0

• (Feature) Add user velocity calculator.