refactor(postgres): port sales_order_analysis report to the query builder

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Mihir Kandoi
2026-06-19 16:15:26 +05:30
parent 60e05bdaa6
commit c86aa3e3ad

View File

@@ -6,9 +6,9 @@ from collections import OrderedDict
import frappe
from frappe import _, qb
from frappe.query_builder import CustomFunction
from frappe.query_builder.functions import Max
from frappe.utils import date_diff, flt, getdate
from frappe.query_builder import Case, CustomFunction
from frappe.query_builder.functions import Coalesce, DateDiff, Max, Sum
from frappe.utils import date_diff, flt, getdate, nowdate
def execute(filters=None):
@@ -18,8 +18,7 @@ def execute(filters=None):
validate_filters(filters)
columns = get_columns(filters)
conditions = get_conditions(filters)
data = get_data(conditions, filters)
data = get_data(filters)
so_elapsed_time = get_so_elapsed_time(data)
if not data:
@@ -39,64 +38,66 @@ def validate_filters(filters):
frappe.throw(_("To Date cannot be before From Date."))
def get_conditions(filters):
conditions = ""
if filters.get("from_date") and filters.get("to_date"):
conditions += " and so.transaction_date between %(from_date)s and %(to_date)s"
def get_data(filters):
so = qb.DocType("Sales Order")
soi = qb.DocType("Sales Order Item")
sii = qb.DocType("Sales Invoice Item")
if filters.get("company"):
conditions += " and so.company = %(company)s"
# Use the application's today (nowdate, System Settings timezone) rather than the database
# server's CURRENT_DATE: the two differ by a day when the DB server runs in a different timezone
# (e.g. UTC DB + IST app near midnight), which made delay_days non-deterministic on postgres CI.
# DateDiff is cross-database: DATEDIFF() on MariaDB, date subtraction on postgres; it casts the
# string date to a date on postgres. delivery_date is functionally dependent on the grouped
# soi.name primary key, so this is valid under both.
delay = DateDiff(nowdate(), soi.delivery_date)
conversion_rate = Coalesce(so.conversion_rate, 1)
if filters.get("sales_order"):
conditions += " and so.name in %(sales_order)s"
if filters.get("status"):
conditions += " and so.status in %(status)s"
if filters.get("warehouse"):
conditions += " and soi.warehouse = %(warehouse)s"
return conditions
def get_data(conditions, filters):
data = frappe.db.sql(
f"""
SELECT
so.transaction_date as date,
soi.delivery_date as delivery_date,
so.name as sales_order,
so.status, so.customer, soi.item_code,
DATEDIFF(CURRENT_DATE, soi.delivery_date) as delay_days,
IF(so.status in ('Completed','To Bill'), 0, (SELECT delay_days)) as delay,
soi.qty, soi.delivered_qty,
(soi.qty - soi.delivered_qty) AS pending_qty,
IFNULL(SUM(sii.qty), 0) as billed_qty,
soi.base_amount as amount,
(soi.delivered_qty * soi.base_rate) as delivered_qty_amount,
(soi.billed_amt * IFNULL(so.conversion_rate, 1)) as billed_amount,
(soi.base_amount - (soi.billed_amt * IFNULL(so.conversion_rate, 1))) as pending_amount,
soi.warehouse as warehouse,
so.company, soi.name,
soi.description as description
FROM
`tabSales Order` so,
`tabSales Order Item` soi
LEFT JOIN `tabSales Invoice Item` sii
ON sii.so_detail = soi.name and sii.docstatus = 1
WHERE
soi.parent = so.name
and so.status not in ('Stopped', 'On Hold')
and so.docstatus = 1
{conditions}
GROUP BY soi.name
ORDER BY so.transaction_date ASC, soi.item_code ASC
""",
filters,
as_dict=1,
query = (
qb.from_(so)
.join(soi)
.on(soi.parent == so.name)
.left_join(sii)
.on((sii.so_detail == soi.name) & (sii.docstatus == 1))
.select(
so.transaction_date.as_("date"),
soi.delivery_date.as_("delivery_date"),
so.name.as_("sales_order"),
so.status,
so.customer,
soi.item_code,
delay.as_("delay_days"),
Case().when(so.status.isin(["Completed", "To Bill"]), 0).else_(delay).as_("delay"),
soi.qty,
soi.delivered_qty,
(soi.qty - soi.delivered_qty).as_("pending_qty"),
Coalesce(Sum(sii.qty), 0).as_("billed_qty"),
soi.base_amount.as_("amount"),
(soi.delivered_qty * soi.base_rate).as_("delivered_qty_amount"),
(soi.billed_amt * conversion_rate).as_("billed_amount"),
(soi.base_amount - (soi.billed_amt * conversion_rate)).as_("pending_amount"),
soi.warehouse.as_("warehouse"),
so.company,
soi.name,
soi.description.as_("description"),
)
.where((so.status.notin(["Stopped", "On Hold"])) & (so.docstatus == 1))
.groupby(soi.name, so.name)
.orderby(so.transaction_date)
.orderby(soi.item_code)
)
return data
if filters.get("from_date") and filters.get("to_date"):
query = query.where(so.transaction_date[filters.get("from_date") : filters.get("to_date")])
if filters.get("company"):
query = query.where(so.company == filters.get("company"))
if filters.get("sales_order"):
query = query.where(so.name.isin(filters.get("sales_order")))
if filters.get("status"):
query = query.where(so.status.isin(filters.get("status")))
if filters.get("warehouse"):
query = query.where(soi.warehouse == filters.get("warehouse"))
return query.run(as_dict=True)
def get_so_elapsed_time(data):
@@ -112,7 +113,17 @@ def get_so_elapsed_time(data):
dn = qb.DocType("Delivery Note")
dni = qb.DocType("Delivery Note Item")
to_seconds = CustomFunction("TO_SECONDS", ["date"])
# TO_SECONDS is MariaDB-only. On postgres, subtracting dates yields days, so multiply
# by 86400 for the equivalent second delta. so.transaction_date is neither aggregated nor
# in the GROUP BY, but it is selectable under postgres' strict GROUP BY because it is
# functionally dependent on the grouped so.name (a doctype's `name` is always the PK).
if frappe.db.db_type == "postgres":
elapsed_seconds = ((Max(dn.posting_date) - so.transaction_date) * 86400).as_("elapsed_seconds")
else:
to_seconds = CustomFunction("TO_SECONDS", ["date"])
elapsed_seconds = (to_seconds(Max(dn.posting_date)) - to_seconds(so.transaction_date)).as_(
"elapsed_seconds"
)
query = (
qb.from_(so)
@@ -125,11 +136,11 @@ def get_so_elapsed_time(data):
.select(
so.name.as_("sales_order"),
soi.item_code.as_("so_item_code"),
(to_seconds(Max(dn.posting_date)) - to_seconds(so.transaction_date)).as_("elapsed_seconds"),
elapsed_seconds,
)
.where((so.name.isin(sales_orders)) & (dn.docstatus == 1))
.orderby(so.name, soi.name)
.groupby(soi.name)
.groupby(soi.name, so.name)
)
dn_elapsed_time = query.run(as_dict=True)