def generate_control_chart(tickets: List[Issue],
chart_class: Type[IChart] = Chart) -> None:
if not tickets:
print('No data. Check that the JSON file was correctly populated ' +
'when you ran the `fetch` command.')
return
completed_cycle_times: List[CycleTime] = list(
sorted(
(get_cycle_time(ticket) for ticket in tickets
if ticket.completed is not None and ticket.started is not None),
key=attrgetter("completed"),
))
if not completed_cycle_times:
print('Could not process cycle time, check that the statuses ' +
'in config.yaml are correct.')
return
cycle_time_plot = CycleTimeScatterPlot(cycle_times=completed_cycle_times,
data_source=ColumnDataSource)
average_cycle_time_plot = AverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
rolling_cycle_time_plot = RollingAverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
cycle_time_deviation_plot = CycleTimeDeviationPlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
start_date, end_date = (
completed_cycle_times[0].completed,
completed_cycle_times[-1].completed,
)
chart = chart_class(
x=Axis(
label="Closed (date)",
values=[
d[0].date().isoformat() for d in Arrow.span_range(
"day",
Arrow(start_date.year, start_date.month, start_date.day),
Arrow(end_date.year, end_date.month, end_date.day),
)
],
size=1800,
),
y=Axis(label="Cycle time (days)", values=None, size=900),
label="Ticket",
tooltips=[
("Ticket", "@label"),
("Closed (date)", "@x"),
("Cycle time (days)", "@y"),
],
)
cycle_time_plot.draw(chart)
average_cycle_time_plot.draw(chart)
rolling_cycle_time_plot.draw(chart)
cycle_time_deviation_plot.draw(chart)
chart.render()
def generate_control_chart(tickets: List[Issue],
chart_class: Type[IChart] = Chart) -> None:
if not tickets:
return
completed_cycle_times: List[CycleTime] = list(
sorted(
(get_cycle_time(ticket) for ticket in tickets
if ticket.completed is not None and ticket.started is not None),
key=attrgetter("completed"),
))
cycle_time_plot = CycleTimeScatterPlot(cycle_times=completed_cycle_times,
data_source=ColumnDataSource)
average_cycle_time_plot = AverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
rolling_cycle_time_plot = RollingAverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
cycle_time_deviation_plot = CycleTimeDeviationPlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource)
start_date, end_date = (
completed_cycle_times[0].completed,
completed_cycle_times[-1].completed,
)
chart = chart_class(
x=Axis(
label="Closed (date)",
values=[
d[0].date().isoformat() for d in Arrow.span_range(
"day",
Arrow(start_date.year, start_date.month, start_date.day),
Arrow(end_date.year, end_date.month, end_date.day),
)
],
size=1800,
),
y=Axis(label="Cycle time (days)", values=None, size=900),
label="Ticket",
tooltips=[
("Ticket", "@label"),
("Closed (date)", "@x"),
("Cycle time (days)", "@y"),
],
)
cycle_time_plot.draw(chart)
average_cycle_time_plot.draw(chart)
rolling_cycle_time_plot.draw(chart)
cycle_time_deviation_plot.draw(chart)
chart.render()
def chart_constructor():
create_chart = mock.Mock()
render = mock.Mock()
return (
Chart(
x=Axis(label="X", values=[1, 2, 3], size=1000),
y=Axis(label="Y", values=[1, 2, 6], size=800),
label="Test",
create_chart=create_chart,
render=render,
tooltips="Tooltip",
),
create_chart,
render,
)
def generate_defect_chart(issues: List[Issue],
chart_class: Type[IChart] = Chart) -> None:
chart = chart_class(
label=None,
x=Axis(label="", values=None, size=600),
y=Axis(label="", values=None, size=300),
tooltips="@value: @defect_rate{0.1f}%",
)
DefectRateDonut(
issues=issues,
data_source=ColumnDataSource,
no_defects_transform=partial(cumsum, include_zero=True),
defects_transform=cumsum,
).draw(chart)
chart.render()
def generate_throughput_chart(issues: List[Issue],
chart_class: Type[IChart] = Chart) -> None:
"""Generate a throughput bar chart for the given list of issues.
:param issues: The list of issues to calculate the weekly throughput for.
:param chart: The chart_class to draw on, defaults to Chart
:raises NoTicketsProvided: If the list of issues is empty.
"""
if not issues:
raise NoTicketsProvided
grouped_issues = group_issues_by_week_commence(issues)
throughputs: OrderedDict[date, int] = OrderedDict(
((wc, len(completed)) for (wc, completed) in grouped_issues.items()))
throughput_plot = ThroughputPlot(weeks=list(throughputs.keys()),
throughputs=list(throughputs.values()))
chart = chart_class(
x=Axis(
label="Week Start",
values=[d.strftime("%d/%m/%Y") for d in throughput_plot.weeks],
size=1500,
),
y=Axis(
label="Issues Completed",
values=None,
size=800,
),
label="Throughput by week",
tooltips=[
("Week", "@x"),
("Issues Completed", "@y"),
],
)
throughput_plot.draw(chart)
chart.render()
def generate_control_chart(
tickets: List[Issue], chart_class: Type[IChart] = Chart
) -> None:
"""Generate the ticket control chart with the provided list of tickets.
:param tickets: The list of tickets to generate your control chart from.
:param chart_class: The chart class to output into, defaults to Chart.
:raises NoTicketsProvided: If len(tickets) == 0.
:raises ChartError: On any error attempting to generate a chart.
"""
if not tickets:
raise NoTicketsProvided
completed_cycle_times: List[CycleTime] = list(
sorted(
(
get_cycle_time(ticket)
for ticket in tickets
if ticket.completed is not None and ticket.started is not None
),
key=attrgetter("completed"),
)
)
if not completed_cycle_times:
raise ChartError(
"Could not process cycle time. Check your config.yaml statuses."
)
cycle_time_plot = CycleTimeScatterPlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource
)
average_cycle_time_plot = AverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource
)
rolling_cycle_time_plot = RollingAverageCycleTimePlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource
)
cycle_time_deviation_plot = CycleTimeDeviationPlot(
cycle_times=completed_cycle_times, data_source=ColumnDataSource
)
start_date, end_date = (
completed_cycle_times[0].completed,
completed_cycle_times[-1].completed,
)
chart = chart_class(
x=Axis(
label="Closed (date)",
values=[
d[0].date().isoformat()
for d in Arrow.span_range(
"day",
Arrow(start_date.year, start_date.month, start_date.day),
Arrow(end_date.year, end_date.month, end_date.day),
)
],
size=1800,
),
y=Axis(label="Cycle time (days)", values=None, size=900),
label="Ticket",
tooltips=[
("Ticket", "@label"),
("Closed (date)", "@x"),
("Cycle time (days)", "@y"),
],
)
cycle_time_plot.draw(chart)
average_cycle_time_plot.draw(chart)
rolling_cycle_time_plot.draw(chart)
cycle_time_deviation_plot.draw(chart)
chart.render()