Metadata-Version: 2.1
Name: sd-metrics-lib
Version: 1.2
Summary: Library to calculate various metrics of software development process
Home-page: https://github.com/clutcher/sd-metrics-lib
Author: Igor Zarvanskyi
Author-email: iclutcher@gmail.com
Project-URL: Bug Tracker, https://github.com/clutcher/sd-metrics-lib/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# 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](https://pypi.org/project/atlassian-python-api/). Supports multithreading.
            + **CachingJiraIssueProvider** wraps _JiraIssueProvider_ with caching.
        + **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.
        + **JiraResolutionTimeIssueTotalSpentTimeExtractor** implementation class, which uses creation and resolution
          time to calculate total spent time on issue.
        + **ChainedWorklogExtractor** implementation class, which allows "chain" **WorklogExtractor** to execute them
          one by one.
    + **WorkTimeExtractor** interface designed to extract and calculate working time from period.
        + **SimpleWorkTimeExtractor** Simple work time calculation. For more precision calculation you can use
          businesstimedelta.
        + **BoundarySimpleWorkTimeExtractor** Uses SimpleWorkTimeExtractor to limit calculation time range. Useful for
          workload calculation in some period of time, for example for "days without work" calculation.

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.

```python
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.

```python
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

### 1.2

+ **(Feature)** Added BoundarySimpleWorkTimeExtractor
+ **(Improvement)** Filter unneeded changelog items for better performance
+ **(Improvement)** Add T-Shirt to story points mapping util class
+ **(Improvement)** Add helper enums
+ **(Bug Fix)** Fix bug with story points returned instead of spent time
+ **(Bug Fix)** Fix bug with missing time for active status
+ **(Bug Fix)** Fix bug with passing class instances in extractor

### 1.1.4

+ **(Improvement)** Add multithreading support for JiraIssueProvider.

### 1.1.3

+ **(Feature)** Add CachingJiraIssueProvider.

### 1.1.2

+ **(Improvement)** Add story points getter for GeneralizedTeamVelocityCalculator.

### 1.1.1

+ **(Improvement)** Execute data fetching in Jira velocity calculators only once.
+ **(Improvement)** Add story points getter for Jira velocity calculators.

### 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.
