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