def __init__(self):
"""
Report initialization that uses reports.conf file.
"""
config = self._get_config()
date_format = '%Y/%m/%d'
self.sprints = tuple(config.get('sprints', '').strip().split(','))
self.date_from = datetime.datetime.strptime(config['date_from'], date_format)
self.date_to = datetime.datetime.strptime(config['date_to'], date_format)
self.usernames = tuple(config['usernames'].strip().split(','))
self.projects = tuple(config.get('projects', '').strip().split(','))
self.issue_types = tuple(config.get('issue_types', '').strip().split(','))
self.status = tuple(config.get('status', '').strip().split(','))
# Jira Client
self.client = JiraClient()
# Custom fields
self.custom_fields = self.client.custom_fields
class JiraReport(object):
def __init__(self):
"""
Report initialization that uses reports.conf file.
"""
config = self._get_config()
date_format = '%Y/%m/%d'
self.sprints = tuple(config.get('sprints', '').strip().split(','))
self.date_from = datetime.datetime.strptime(config['date_from'], date_format)
self.date_to = datetime.datetime.strptime(config['date_to'], date_format)
self.usernames = tuple(config['usernames'].strip().split(','))
self.projects = tuple(config.get('projects', '').strip().split(','))
self.issue_types = tuple(config.get('issue_types', '').strip().split(','))
self.status = tuple(config.get('status', '').strip().split(','))
# Jira Client
self.client = JiraClient()
# Custom fields
self.custom_fields = self.client.custom_fields
def _get_config(self) -> Dict[str, str]:
"""
Gets config parameters.
File: reports.conf
:return: Config parameters.
"""
parser = ConfigParser()
parser.read(os.path.realpath(os.path.join(os.path.dirname(__file__), '..', 'reports.conf')))
# Get jira arguments
try:
jira = {option: parser.get('jira', option) for option in parser.options('jira')}
except Exception as e:
raise ImproperlyConfigured('jira') from e
return jira
def resolution_tasks(self) -> pd.DataFrame:
"""
Report all tasks given their resolution date. The fields included are:
- Key.
- Assignee.
- Summary.
- T-Shirt.
- Story Points.
- Original Estimate.
- Time Spent.
- Type.
- Project.
:return: Tasks.
"""
def get_tasks_data(issue):
fields = issue['fields']
t_shirt = fields.get(self.custom_fields['t_shirt_size'], {}) or {}
return {
'Key': issue['key'],
'Assignee': fields['assignee']['displayName'] if fields['assignee'] else None,
'Summary': fields['summary'],
'Type': fields['issuetype']['name'],
'T-Shirt': t_shirt.get('value', None),
'Story Points': fields.get(self.custom_fields['story_points'], None),
'Original Estimate': fields['aggregatetimeoriginalestimate'] / 3600 if fields[
'aggregatetimeoriginalestimate'] else 0,
'Time Spent': fields['aggregatetimespent'] / 3600 if fields['aggregatetimespent'] else 0,
'Project': fields['project']['name'],
}
# Create list of fields to retrieve
included_fields = (
'key',
'assignee',
'summary',
self.custom_fields['story_points'],
self.custom_fields['t_shirt_size'],
'aggregatetimeoriginalestimate',
'aggregatetimespent',
'issuetype',
'project'
)
# Get tasks from client
tasks = self.client.get_resolution_tasks(
projects=self.projects,
issue_types=self.issue_types,
status=self.status,
date_from=self.date_from.strftime("%Y/%m/%d"),
date_to=self.date_to.strftime("%Y/%m/%d"),
get_data=get_tasks_data,
fields=included_fields,
)
return pd.DataFrame.from_records(tasks, index='Key')
def sprint_tasks(self) -> pd.DataFrame:
"""
Report all tasks of a sprint. The fields included are:
- Key.
- Assignee.
- Summary.
- T-Shirt.
- Story Points.
- Original Estimate.
- Time Spent.
- Type.
- Project.
:return: Tasks.
"""
def get_tasks_data(issue):
fields = issue['fields']
t_shirt = fields.get(self.custom_fields['t_shirt_size'], {}) or {}
return {
'Key': issue['key'],
'Assignee': fields['assignee']['displayName'] if fields['assignee'] else None,
'Summary': fields['summary'],
'Type': fields['issuetype']['name'],
'T-Shirt': t_shirt.get('value', None),
'Story Points': fields.get(self.custom_fields['story_points'], None),
'Original Estimate': fields['aggregatetimeoriginalestimate'] / 3600 if fields[
'aggregatetimeoriginalestimate'] else 0,
'Time Spent': fields['aggregatetimespent'] / 3600 if fields['aggregatetimespent'] else 0,
'Project': fields['project']['name'],
}
# Create list of fields to retrieve
included_fields = (
'key',
'assignee',
'summary',
self.custom_fields['story_points'],
self.custom_fields['t_shirt_size'],
'aggregatetimeoriginalestimate',
'aggregatetimespent',
'issuetype',
'project'
)
# Get tasks from client
tasks = self.client.get_sprint_tasks(
get_data=get_tasks_data,
projects=self.projects,
sprints=self.sprints,
fields=included_fields
)
return pd.DataFrame.from_records(tasks, index='Key')
def sprint_subtasks(self) -> Dict[str, Any]:
"""
Report all subtasks of a sprint. The fields included are:
:return: Subtasks.
"""
def get_subtasks_data(issue):
fields = issue['fields']
resolution = fields.get('resolution', {}) or {}
return {
'Key': issue['key'],
'Parent': fields['parent']['key'],
'Summary': fields['summary'],
'Type': fields['issuetype']['name'],
'Status': fields['status']['name'],
'Resolution': resolution.get('name', None),
'Original Estimate': fields['aggregatetimeoriginalestimate'] / 3600 if fields[
'aggregatetimeoriginalestimate'] else 0,
'Time Spent': fields['aggregatetimespent'] / 3600 if fields['aggregatetimespent'] else 0,
'Assignee': fields['assignee']['displayName'] if fields['assignee'] else None,
}
subtasks = self.client.get_sprint_subtasks(projects=self.projects, sprints=self.sprints)
subtasks_data = [get_subtasks_data(subtask) for subtask in subtasks]
return pd.DataFrame.from_records(subtasks_data, index='Key')
def worklogs(self) -> pd.DataFrame:
"""
Report all worklogs for a given user.
:return: Worklogs.
"""
def get_worklogs_data(worklog):
return {
'Author': worklog['author']['displayName'],
'Key': worklog['issue']['key'],
'Issue': worklog['issue']['summary'],
'Type': worklog['issue']['issueType']['name'],
'Time Spent': worklog['timeSpentSeconds'] / 3600,
'Comment': worklog['comment'],
}
worklogs = [w for u in self.usernames for w in self.client.get_worklogs(self.date_from, self.date_to, u)]
worklogs_data = [get_worklogs_data(worklog) for worklog in worklogs]
return pd.DataFrame.from_records(worklogs_data)
