def demand(self, from_date, to_date, types=None):
"""
Return the number of issues created each week - i.e. the demand on the system
"""
if self.work_items is None:
self.work_items = self.source.work_items()
details = []
for work_item in self.work_items:
detail = work_item.detail()
detail['count'] = 1 # Need to figure out where to put this
# resolution_date_str = f.resolutiondate
# if resolution_date_str is not None:
# resolution_date = datetime.strptime(resolution_date_str[:10],
# '%Y-%m-%d')
# week = week_start_date(resolution_date.isocalendar()[0],
# resolution_date.isocalendar()[1]).strftime('%Y-%m-%d')
# else:
# week = None
detail['week_created'] = week_start_date(
detail['date_created'].isocalendar()[0],
detail['date_created'].isocalendar()[1]).strftime('%Y-%m-%d')
include = True
swimlane = work_item.category
if types is not None and self.types is not None:
include = False
for type_grouping in types:
if work_item.type in self.types[type_grouping]:
swimlane = swimlane + '-' + type_grouping
include = True
detail['swimlane'] = swimlane
if include:
details.append(detail)
df = pd.DataFrame(details)
table = pd.tools.pivot.pivot_table(df,
rows=['week_created'],
cols=['swimlane'],
values='count',
aggfunc=np.count_nonzero)
reindexed = table.reindex(index=fill_date_index_blanks(table.index),
fill_value=np.int64(0))
reindexed.index.name = "week"
return reindexed
def demand(self,
from_date,
to_date,
types=None):
"""
Return the number of issues created each week - i.e. the demand on the system
"""
if self.work_items is None:
self.work_items = self.source.work_items()
details = []
for work_item in self.work_items:
detail = work_item.detail()
detail['count'] = 1 # Need to figure out where to put this
# resolution_date_str = f.resolutiondate
# if resolution_date_str is not None:
# resolution_date = datetime.strptime(resolution_date_str[:10],
# '%Y-%m-%d')
# week = week_start_date(resolution_date.isocalendar()[0],
# resolution_date.isocalendar()[1]).strftime('%Y-%m-%d')
# else:
# week = None
detail['week_created'] = week_start_date(detail['date_created'].isocalendar()[0],
detail['date_created'].isocalendar()[1]).strftime('%Y-%m-%d')
include = True
swimlane = work_item.category
if types is not None and self.types is not None:
include = False
for type_grouping in types:
if work_item.type in self.types[type_grouping]:
swimlane = swimlane + '-' + type_grouping
include = True
detail['swimlane'] = swimlane
if include:
details.append(detail)
df = pd.DataFrame(details)
table = pd.tools.pivot.pivot_table(df, rows=['week_created'], cols=['swimlane'], values='count', aggfunc=np.count_nonzero)
reindexed = table.reindex(index=fill_date_index_blanks(table.index), fill_value=np.int64(0))
reindexed.index.name = "week"
return reindexed
def _issues_as_rows(self, issues, types=None):
"""
Get issues into a state where we can stick them into a Pandas dataframe
"""
# TODO: Decide if this should be a class / helper method?
# TODO: See if has any overlap with throughput function
issue_rows = []
for issue in issues:
f = issue.fields
resolution_date_str = f.resolutiondate
if resolution_date_str is not None:
resolution_date = datetime.strptime(resolution_date_str[:10],
'%Y-%m-%d')
week = week_start_date(resolution_date.isocalendar()[0],
resolution_date.isocalendar()[1]).strftime('%Y-%m-%d')
else:
week = None
date_created = datetime.strptime(f.created[:10], '%Y-%m-%d')
week_created = week_start_date(date_created.isocalendar()[0],
date_created.isocalendar()[1]).strftime('%Y-%m-%d')
if issue.changelog is not None:
tis = time_in_states(issue.changelog.histories,
datetime.strptime(f.created[:10],
'%Y-%m-%d'),
date.today())
since = tis[-1]['days']
else:
since = None
include = True
# TODO: This looks like a bit of a hack.
# Can we do without iterating over loop, seeing as we
# only ever want one swimlane/category combination?
swimlane = issue.category
if types is not None and self.types is not None:
include = False
for type_grouping in types:
if f.issuetype.name in self.types[type_grouping]:
swimlane = swimlane + '-' + type_grouping
include = True
if include:
try:
story_points = f.customfield_10002
except AttributeError:
story_points = None
try:
epic_link = f.customfield_10200
except AttributeError:
epic_link = None
# TODO: Fields need to come out of config too.
issue_row = {'swimlane': swimlane,
'type': f.issuetype.name,
'id': issue.key,
'name': f.summary,
'status': f.status.name,
'project': f.project.name,
'components': None,
'week': week,
'since': since,
'created': f.created,
'week_created': week_created,
'story_points': story_points,
'epic_link': epic_link,
'count': 1}
for cycle in self.cycles:
try:
issue_row[cycle] = getattr(issue, cycle)
except AttributeError:
pass
components = []
for component in f.components:
components.append(component.name)
issue_row['components'] = ",".join(components)
issue_rows.append(issue_row)
return issue_rows
def _issues_as_rows(self, issues, types=None):
"""
Get issues into a state where we can stick them into a Pandas dataframe
"""
# TODO: Decide if this should be a class / helper method?
# TODO: See if has any overlap with throughput function
issue_rows = []
for issue in issues:
f = issue.fields
resolution_date_str = f.resolutiondate
if resolution_date_str is not None:
resolution_date = datetime.strptime(resolution_date_str[:10],
'%Y-%m-%d')
week = week_start_date(
resolution_date.isocalendar()[0],
resolution_date.isocalendar()[1]).strftime('%Y-%m-%d')
else:
week = None
date_created = datetime.strptime(f.created[:10], '%Y-%m-%d')
week_created = week_start_date(
date_created.isocalendar()[0],
date_created.isocalendar()[1]).strftime('%Y-%m-%d')
if issue.changelog is not None:
tis = time_in_states(
issue.changelog.histories,
datetime.strptime(f.created[:10], '%Y-%m-%d'),
date.today())
since = tis[-1]['days']
else:
since = None
include = True
# TODO: This looks like a bit of a hack.
# Can we do without iterating over loop, seeing as we
# only ever want one swimlane/category combination?
swimlane = issue.category
if types is not None and self.types is not None:
include = False
for type_grouping in types:
if f.issuetype.name in self.types[type_grouping]:
swimlane = swimlane + '-' + type_grouping
include = True
if include:
try:
story_points = f.customfield_10002
except AttributeError:
story_points = None
try:
epic_link = f.customfield_10200
except AttributeError:
epic_link = None
# TODO: Fields need to come out of config too.
issue_row = {
'swimlane': swimlane,
'type': f.issuetype.name,
'id': issue.key,
'name': f.summary,
'status': f.status.name,
'project': f.project.name,
'components': None,
'week': week,
'since': since,
'created': f.created,
'week_created': week_created,
'story_points': story_points,
'epic_link': epic_link,
'count': 1
}
for cycle in self.cycles:
try:
issue_row[cycle] = getattr(issue, cycle)
except AttributeError:
pass
components = []
for component in f.components:
components.append(component.name)
issue_row['components'] = ",".join(components)
issue_rows.append(issue_row)
return issue_rows