bb-plane-fork/apiserver/plane/utils/analytics_plot.py
2023-05-16 10:50:14 +05:30

67 lines
2.4 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):
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 date, items in groupby(result_values, key=lambda x: x[str("dimension")]):
grouped_data[str(date)] = list(items)
return grouped_data