76 lines
2.8 KiB
Python
76 lines
2.8 KiB
Python
# Python imports
|
|
from itertools import groupby
|
|
|
|
# Django import
|
|
from django.db import models
|
|
from django.db.models import Count, F, Sum, Value, Case, When, CharField
|
|
from django.db.models.functions import Coalesce, ExtractMonth, ExtractYear, Concat
|
|
|
|
|
|
def build_graph_plot(queryset, x_axis, y_axis, segment=None):
|
|
|
|
temp_axis = x_axis
|
|
|
|
if x_axis in ["created_at", "start_date", "target_date", "completed_at"]:
|
|
year = ExtractYear(x_axis)
|
|
month = ExtractMonth(x_axis)
|
|
dimension = Concat(year, Value("-"), month, output_field=CharField())
|
|
queryset = queryset.annotate(dimension=dimension)
|
|
x_axis = "dimension"
|
|
else:
|
|
queryset = queryset.annotate(dimension=F(x_axis))
|
|
x_axis = "dimension"
|
|
|
|
if x_axis in ["created_at", "start_date", "target_date", "completed_at"]:
|
|
queryset = queryset.exclude(x_axis__is_null=True)
|
|
|
|
if segment in ["created_at", "start_date", "target_date", "completed_at"]:
|
|
year = ExtractYear(segment)
|
|
month = ExtractMonth(segment)
|
|
dimension = Concat(year, Value("-"), month, output_field=CharField())
|
|
queryset = queryset.annotate(segmented=dimension)
|
|
segment = "segmented"
|
|
|
|
queryset = queryset.values(x_axis)
|
|
|
|
# Group queryset by x_axis field
|
|
|
|
if y_axis == "issue_count":
|
|
queryset = queryset.annotate(
|
|
is_null=Case(
|
|
When(dimension__isnull=True, then=Value("None")),
|
|
default=Value("not_null"),
|
|
output_field=models.CharField(max_length=8),
|
|
),
|
|
dimension_ex=Coalesce("dimension", Value("null")),
|
|
).values("dimension")
|
|
if segment:
|
|
queryset = queryset.annotate(segment=F(segment)).values(
|
|
"dimension", "segment"
|
|
)
|
|
else:
|
|
queryset = queryset.values("dimension")
|
|
|
|
queryset = queryset.annotate(count=Count("*")).order_by("dimension")
|
|
|
|
if y_axis == "estimate":
|
|
queryset = queryset.annotate(estimate=Sum("estimate_point")).order_by(x_axis)
|
|
if segment:
|
|
queryset = queryset.annotate(segment=F(segment)).values(
|
|
"dimension", "segment", "estimate"
|
|
)
|
|
else:
|
|
queryset = queryset.values("dimension", "estimate")
|
|
|
|
result_values = list(queryset)
|
|
grouped_data = {}
|
|
for key, items in groupby(result_values, key=lambda x: x[str("dimension")]):
|
|
grouped_data[str(key)] = list(items)
|
|
|
|
sorted_data = grouped_data
|
|
if temp_axis == "priority":
|
|
order = ["low", "medium", "high", "urgent", "None"]
|
|
sorted_data = {key: grouped_data[key] for key in order if key in grouped_data}
|
|
else:
|
|
sorted_data = dict(sorted(grouped_data.items(), key=lambda x: (x[0] is "None", x[0])))
|
|
return sorted_data
|