brotherton-erpnext/erpnext/stock/report/stock_analytics/stock_analytics.py
Ankush Menat 198b91f8d4 fix: only carry-forward balances till today's period
Showing data in future doesn't make sense. Only carry-forward till last
bucket that contains today's day.
2022-05-10 15:38:02 +05:30

266 lines
8.3 KiB
Python

# Copyright (c) 2013, Frappe Technologies Pvt. Ltd. and contributors
# For license information, please see license.txt
import datetime
from typing import List
import frappe
from frappe import _, scrub
from frappe.utils import get_first_day as get_first_day_of_month
from frappe.utils import get_first_day_of_week, get_quarter_start, getdate
from erpnext.accounts.utils import get_fiscal_year
from erpnext.stock.report.stock_balance.stock_balance import (
get_item_details,
get_items,
get_stock_ledger_entries,
)
from erpnext.stock.utils import is_reposting_item_valuation_in_progress
def execute(filters=None):
is_reposting_item_valuation_in_progress()
filters = frappe._dict(filters or {})
columns = get_columns(filters)
data = get_data(filters)
chart = get_chart_data(columns)
return columns, data, None, chart
def get_columns(filters):
columns = [
{"label": _("Item"), "options": "Item", "fieldname": "name", "fieldtype": "Link", "width": 140},
{
"label": _("Item Name"),
"options": "Item",
"fieldname": "item_name",
"fieldtype": "Link",
"width": 140,
},
{
"label": _("Item Group"),
"options": "Item Group",
"fieldname": "item_group",
"fieldtype": "Link",
"width": 140,
},
{"label": _("Brand"), "fieldname": "brand", "fieldtype": "Data", "width": 120},
{"label": _("UOM"), "fieldname": "uom", "fieldtype": "Data", "width": 120},
]
ranges = get_period_date_ranges(filters)
for dummy, end_date in ranges:
period = get_period(end_date, filters)
columns.append(
{"label": _(period), "fieldname": scrub(period), "fieldtype": "Float", "width": 120}
)
return columns
def get_period_date_ranges(filters):
from dateutil.relativedelta import relativedelta
from_date = round_down_to_nearest_frequency(filters.from_date, filters.range)
to_date = getdate(filters.to_date)
increment = {"Monthly": 1, "Quarterly": 3, "Half-Yearly": 6, "Yearly": 12}.get(filters.range, 1)
periodic_daterange = []
for dummy in range(1, 53, increment):
if filters.range == "Weekly":
period_end_date = from_date + relativedelta(days=6)
else:
period_end_date = from_date + relativedelta(months=increment, days=-1)
if period_end_date > to_date:
period_end_date = to_date
periodic_daterange.append([from_date, period_end_date])
from_date = period_end_date + relativedelta(days=1)
if period_end_date == to_date:
break
return periodic_daterange
def round_down_to_nearest_frequency(date: str, frequency: str) -> datetime.datetime:
"""Rounds down the date to nearest frequency unit.
example:
>>> round_down_to_nearest_frequency("2021-02-21", "Monthly")
datetime.datetime(2021, 2, 1)
>>> round_down_to_nearest_frequency("2021-08-21", "Yearly")
datetime.datetime(2021, 1, 1)
"""
def _get_first_day_of_fiscal_year(date):
fiscal_year = get_fiscal_year(date)
return fiscal_year and fiscal_year[1] or date
round_down_function = {
"Monthly": get_first_day_of_month,
"Quarterly": get_quarter_start,
"Weekly": get_first_day_of_week,
"Yearly": _get_first_day_of_fiscal_year,
}.get(frequency, getdate)
return round_down_function(date)
def get_period(posting_date, filters):
months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
if filters.range == "Weekly":
period = "Week " + str(posting_date.isocalendar()[1]) + " " + str(posting_date.year)
elif filters.range == "Monthly":
period = str(months[posting_date.month - 1]) + " " + str(posting_date.year)
elif filters.range == "Quarterly":
period = "Quarter " + str(((posting_date.month - 1) // 3) + 1) + " " + str(posting_date.year)
else:
year = get_fiscal_year(posting_date, company=filters.company)
period = str(year[2])
return period
def get_periodic_data(entry, filters):
"""Structured as:
Item 1
- Balance (updated and carried forward):
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
- Jun 2021 (sum of warehouse quantities used in report)
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
- Jul 2021 (sum of warehouse quantities used in report)
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
Item 2
- Balance (updated and carried forward):
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
- Jun 2021 (sum of warehouse quantities used in report)
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
- Jul 2021 (sum of warehouse quantities used in report)
- Warehouse A : bal_qty/value
- Warehouse B : bal_qty/value
"""
expected_ranges = get_period_date_ranges(filters)
expected_periods = []
for _start_date, end_date in expected_ranges:
expected_periods.append(get_period(end_date, filters))
periodic_data = {}
for d in entry:
period = get_period(d.posting_date, filters)
bal_qty = 0
fill_intermediate_periods(periodic_data, d.item_code, period, expected_periods)
# if period against item does not exist yet, instantiate it
# insert existing balance dict against period, and add/subtract to it
if periodic_data.get(d.item_code) and not periodic_data.get(d.item_code).get(period):
previous_balance = periodic_data[d.item_code]["balance"].copy()
periodic_data[d.item_code][period] = previous_balance
if d.voucher_type == "Stock Reconciliation" and not d.batch_no:
if periodic_data.get(d.item_code) and periodic_data.get(d.item_code).get("balance").get(
d.warehouse
):
bal_qty = periodic_data[d.item_code]["balance"][d.warehouse]
qty_diff = d.qty_after_transaction - bal_qty
else:
qty_diff = d.actual_qty
if filters["value_quantity"] == "Quantity":
value = qty_diff
else:
value = d.stock_value_difference
# period-warehouse wise balance
periodic_data.setdefault(d.item_code, {}).setdefault("balance", {}).setdefault(d.warehouse, 0.0)
periodic_data.setdefault(d.item_code, {}).setdefault(period, {}).setdefault(d.warehouse, 0.0)
periodic_data[d.item_code]["balance"][d.warehouse] += value
periodic_data[d.item_code][period][d.warehouse] = periodic_data[d.item_code]["balance"][
d.warehouse
]
return periodic_data
def fill_intermediate_periods(
periodic_data, item_code: str, current_period: str, all_periods: List[str]
) -> None:
"""There might be intermediate periods where no stock ledger entry exists, copy previous previous data.
Previous data is ONLY copied if period falls in report range and before period being processed currently.
args:
current_period: process till this period (exclusive)
all_periods: all periods expected in report via filters
periodic_data: report's periodic data
item_code: item_code being processed
"""
previous_period_data = None
for period in all_periods:
if period == current_period:
return
if (
periodic_data.get(item_code)
and not periodic_data.get(item_code).get(period)
and previous_period_data
):
# This period should exist since it's in report range, assign previous period data
periodic_data[item_code][period] = previous_period_data.copy()
previous_period_data = periodic_data.get(item_code, {}).get(period)
def get_data(filters):
data = []
items = get_items(filters)
sle = get_stock_ledger_entries(filters, items)
item_details = get_item_details(items, sle, filters)
periodic_data = get_periodic_data(sle, filters)
ranges = get_period_date_ranges(filters)
today = getdate()
for dummy, item_data in item_details.items():
row = {
"name": item_data.name,
"item_name": item_data.item_name,
"item_group": item_data.item_group,
"uom": item_data.stock_uom,
"brand": item_data.brand,
}
previous_period_value = 0.0
for start_date, end_date in ranges:
period = get_period(end_date, filters)
period_data = periodic_data.get(item_data.name, {}).get(period)
if period_data:
row[scrub(period)] = previous_period_value = sum(period_data.values())
else:
row[scrub(period)] = previous_period_value if today >= start_date else None
data.append(row)
return data
def get_chart_data(columns):
labels = [d.get("label") for d in columns[5:]]
chart = {"data": {"labels": labels, "datasets": []}}
chart["type"] = "line"
return chart