Day Wise Filter

So this is my code below which generates a report of warehouses and it’s corresponding balance values.

from operator import itemgetter
from typing import Any, Dict, List, Optional, TypedDict

import frappe
from frappe import _
from frappe.query_builder.functions import Coalesce, CombineDatetime
from frappe.utils import cint, date_diff, flt, getdate
from frappe.utils.nestedset import get_descendants_of

import erpnext
from erpnext.stock.doctype.inventory_dimension.inventory_dimension import get_inventory_dimensions
from erpnext.stock.doctype.warehouse.warehouse import apply_warehouse_filter
from erpnext.stock.report.stock_ageing.stock_ageing import FIFOSlots, get_average_age
from erpnext.stock.utils import add_additional_uom_columns, is_reposting_item_valuation_in_progress
from datetime import timedelta
from typing import List, Tuple, Dict, Any


class StockBalanceFilter(TypedDict):
	company: Optional[str]
	from_date: str
	to_date: str
	item_group: Optional[str]
	item: Optional[str]
	warehouse: Optional[str]
	warehouse_type: Optional[str]
	include_uom: Optional[str]  # include extra info in converted UOM
	show_stock_ageing_data: bool
	show_variant_attributes: bool


SLEntry = Dict[str, Any]


def execute(filters: Optional[StockBalanceFilter] = None):
    is_reposting_item_valuation_in_progress()
    if not filters:
        filters = {}

    # Check if the "Group By Warehouse" filter is enabled
    group_by_warehouse = filters.get("group_by_warehouse", 0)
    if filters.get("company"):
        company_currency = erpnext.get_company_currency(filters.get("company"))
    else:
        company_currency = frappe.db.get_single_value("Global Defaults", "default_currency")

    include_uom = filters.get("include_uom")
    columns = get_columns(filters)
    items = get_items(filters)
    sle = get_stock_ledger_entries(filters, items)

    if filters.get("show_stock_ageing_data"):
        filters["show_warehouse_wise_stock"] = True
        item_wise_fifo_queue = FIFOSlots(filters, sle).generate()

    # if no stock ledger entry found return
    if not sle:
        return columns, []

    iwb_map = get_item_warehouse_map(filters, sle)
    item_map = get_item_details(items, sle, filters)
    item_reorder_detail_map = get_item_reorder_details(item_map.keys())

    data = []
    conversion_factors = {}

    _func = itemgetter(1)

    to_date = filters.get("to_date")

    for group_by_key in iwb_map:
        item = group_by_key[1]
        warehouse = group_by_key[2]
        company = group_by_key[0]

        if item_map.get(item):
            qty_dict = iwb_map[group_by_key]
            item_reorder_level = 0
            item_reorder_qty = 0
            if item + warehouse in item_reorder_detail_map:
                item_reorder_level = item_reorder_detail_map[item + warehouse]["warehouse_reorder_level"]
                item_reorder_qty = item_reorder_detail_map[item + warehouse]["warehouse_reorder_qty"]

            report_data = {
                "currency": company_currency,
                "item_code": item,
                "warehouse": warehouse,
                "company": company,
                "reorder_level": item_reorder_level,
                "reorder_qty": item_reorder_qty,
            }
            report_data.update(item_map[item])
            report_data.update(qty_dict)

            if include_uom:
                conversion_factors.setdefault(item, item_map[item].conversion_factor)

            if filters.get("show_stock_ageing_data"):
                fifo_queue = item_wise_fifo_queue[(item, warehouse)].get("fifo_queue")

                stock_ageing_data = {"average_age": 0, "earliest_age": 0, "latest_age": 0}
                if fifo_queue:
                    fifo_queue = sorted(filter(_func, fifo_queue), key=_func)
                    if not fifo_queue:
                        continue

                    stock_ageing_data["average_age"] = get_average_age(fifo_queue, to_date)
                    stock_ageing_data["earliest_age"] = date_diff(to_date, fifo_queue[0][1])
                    stock_ageing_data["latest_age"] = date_diff(to_date, fifo_queue[-1][1])

                report_data.update(stock_ageing_data)

            data.append(report_data)

    add_additional_uom_columns(columns, data, include_uom, conversion_factors)

    # Modify the report to group stock balances by warehouse if enabled
    if group_by_warehouse:
        data = group_stock_balances_by_warehouse(data)

    return columns, data
# Function to group stock balances by warehouse and calculate aggregate balance value
def group_stock_balances_by_warehouse(data):
    grouped_data = {}
    for row in data:
        warehouse = row.get("warehouse")
        if warehouse not in grouped_data:
            grouped_data[warehouse] = row
        else:
            # Aggregate balance value for the same warehouse
            grouped_data[warehouse]["bal_val"] += row.get("bal_val")

    # Convert the grouped data back to a list
    grouped_data_list = list(grouped_data.values())
    return grouped_data_list

def get_columns(filters: StockBalanceFilter):
	"""return columns"""
	columns = [

		{
			"label": _("Warehouse"),
			"fieldname": "warehouse",
			"fieldtype": "Link",
			"options": "Warehouse",
			"width": 300,
		},
	]

	columns.extend(
		[

			{
				"label": _("Balance Value"),
				"fieldname": "bal_val",
				"fieldtype": "Currency",
				"width": 150,
				"options": "currency",
			},

		]
	)

	if filters.get("show_stock_ageing_data"):
		columns += [
			{"label": _("Average Age"), "fieldname": "average_age", "width": 100},
			{"label": _("Earliest Age"), "fieldname": "earliest_age", "width": 100},
			{"label": _("Latest Age"), "fieldname": "latest_age", "width": 100},
		]

	if filters.get("show_variant_attributes"):
		columns += [
			{"label": att_name, "fieldname": att_name, "width": 100}
			for att_name in get_variants_attributes()
		]

	return columns


def apply_conditions(query, filters):
	sle = frappe.qb.DocType("Stock Ledger Entry")
	warehouse_table = frappe.qb.DocType("Warehouse")

	if not filters.get("from_date"):
		frappe.throw(_("'From Date' is required"))

	if to_date := filters.get("to_date"):
		query = query.where(sle.posting_date <= to_date)
	else:
		frappe.throw(_("'To Date' is required"))

	if company := filters.get("company"):
		query = query.where(sle.company == company)

	if filters.get("warehouse"):
		query = apply_warehouse_filter(query, sle, filters)
	elif warehouse_type := filters.get("warehouse_type"):
		query = (
			query.join(warehouse_table)
			.on(warehouse_table.name == sle.warehouse)
			.where(warehouse_table.warehouse_type == warehouse_type)
		)

	return query


def get_stock_ledger_entries(filters: StockBalanceFilter, items: List[str]) -> List[SLEntry]:
	sle = frappe.qb.DocType("Stock Ledger Entry")

	query = (
		frappe.qb.from_(sle)
		.select(
			sle.item_code,
			sle.warehouse,
			sle.posting_date,
			sle.actual_qty,
			sle.valuation_rate,
			sle.company,
			sle.voucher_type,
			sle.qty_after_transaction,
			sle.stock_value_difference,
			sle.item_code.as_("name"),
			sle.voucher_no,
			sle.stock_value,
			sle.batch_no,
		)
		.where((sle.docstatus < 2) & (sle.is_cancelled == 0))
		.orderby(CombineDatetime(sle.posting_date, sle.posting_time))
		.orderby(sle.creation)
		.orderby(sle.actual_qty)
	)

	inventory_dimension_fields = get_inventory_dimension_fields()
	if inventory_dimension_fields:
		for fieldname in inventory_dimension_fields:
			query = query.select(fieldname)
			if fieldname in filters and filters.get(fieldname):
				query = query.where(sle[fieldname].isin(filters.get(fieldname)))

	if items:
		query = query.where(sle.item_code.isin(items))

	query = apply_conditions(query, filters)
	return query.run(as_dict=True)


def get_opening_vouchers(to_date):
	opening_vouchers = {"Stock Entry": [], "Stock Reconciliation": []}

	se = frappe.qb.DocType("Stock Entry")
	sr = frappe.qb.DocType("Stock Reconciliation")

	vouchers_data = (
		frappe.qb.from_(
			(
				frappe.qb.from_(se)
				.select(se.name, Coalesce("Stock Entry").as_("voucher_type"))
				.where((se.docstatus == 1) & (se.posting_date <= to_date) & (se.is_opening == "Yes"))
			)
			+ (
				frappe.qb.from_(sr)
				.select(sr.name, Coalesce("Stock Reconciliation").as_("voucher_type"))
				.where((sr.docstatus == 1) & (sr.posting_date <= to_date) & (sr.purpose == "Opening Stock"))
			)
		).select("voucher_type", "name")
	).run(as_dict=True)

	if vouchers_data:
		for d in vouchers_data:
			opening_vouchers[d.voucher_type].append(d.name)

	return opening_vouchers


def get_inventory_dimension_fields():
	return [dimension.fieldname for dimension in get_inventory_dimensions()]


def get_item_warehouse_map(filters: StockBalanceFilter, sle: List[SLEntry]):
	iwb_map = {}
	from_date = getdate(filters.get("from_date"))
	to_date = getdate(filters.get("to_date"))
	opening_vouchers = get_opening_vouchers(to_date)
	float_precision = cint(frappe.db.get_default("float_precision")) or 3
	inventory_dimensions = get_inventory_dimension_fields()

	for d in sle:
		group_by_key = get_group_by_key(d, filters, inventory_dimensions)
		if group_by_key not in iwb_map:
			iwb_map[group_by_key] = frappe._dict(
				{
					"opening_qty": 0.0,
					"opening_val": 0.0,
					"in_qty": 0.0,
					"in_val": 0.0,
					"out_qty": 0.0,
					"out_val": 0.0,
					"bal_qty": 0.0,
					"bal_val": 0.0,
					"val_rate": 0.0,
				}
			)

		qty_dict = iwb_map[group_by_key]
		for field in inventory_dimensions:
			qty_dict[field] = d.get(field)

		if d.voucher_type == "Stock Reconciliation" and not d.batch_no:
			qty_diff = flt(d.qty_after_transaction) - flt(qty_dict.bal_qty)
		else:
			qty_diff = flt(d.actual_qty)

		value_diff = flt(d.stock_value_difference)

		if d.posting_date < from_date or d.voucher_no in opening_vouchers.get(d.voucher_type, []):
			qty_dict.opening_qty += qty_diff
			qty_dict.opening_val += value_diff

		elif d.posting_date >= from_date and d.posting_date <= to_date:
			if flt(qty_diff, float_precision) >= 0:
				qty_dict.in_qty += qty_diff
				qty_dict.in_val += value_diff
			else:
				qty_dict.out_qty += abs(qty_diff)
				qty_dict.out_val += abs(value_diff)

		qty_dict.val_rate = d.valuation_rate
		qty_dict.bal_qty += qty_diff
		qty_dict.bal_val += value_diff

	iwb_map = filter_items_with_no_transactions(iwb_map, float_precision, inventory_dimensions)

	return iwb_map


def get_group_by_key(row, filters, inventory_dimension_fields) -> tuple:
	group_by_key = [row.company, row.item_code, row.warehouse]

	for fieldname in inventory_dimension_fields:
		if filters.get(fieldname):
			group_by_key.append(row.get(fieldname))

	return tuple(group_by_key)


def filter_items_with_no_transactions(iwb_map, float_precision: float, inventory_dimensions: list):
	pop_keys = []
	for group_by_key in iwb_map:
		qty_dict = iwb_map[group_by_key]

		no_transactions = True
		for key, val in qty_dict.items():
			if key in inventory_dimensions:
				continue

			val = flt(val, float_precision)
			qty_dict[key] = val
			if key != "val_rate" and val:
				no_transactions = False

		if no_transactions:
			pop_keys.append(group_by_key)

	for key in pop_keys:
		iwb_map.pop(key)

	return iwb_map


def get_items(filters: StockBalanceFilter) -> List[str]:
	"Get items based on item code, item group or brand."
	if item_code := filters.get("item_code"):
		return [item_code]
	else:
		item_filters = {}
		if item_group := filters.get("item_group"):
			children = get_descendants_of("Item Group", item_group, ignore_permissions=True)
			item_filters["item_group"] = ("in", children + [item_group])
		if brand := filters.get("brand"):
			item_filters["brand"] = brand

		return frappe.get_all("Item", filters=item_filters, pluck="name", order_by=None)


def get_item_details(items: List[str], sle: List[SLEntry], filters: StockBalanceFilter):
	item_details = {}
	if not items:
		items = list(set(d.item_code for d in sle))

	if not items:
		return item_details

	item_table = frappe.qb.DocType("Item")

	query = (
		frappe.qb.from_(item_table)
		.select(
			item_table.name,
			item_table.item_name,
			item_table.description,
			item_table.item_group,
			item_table.brand,
			item_table.stock_uom,
		)
		.where(item_table.name.isin(items))
	)

	if uom := filters.get("include_uom"):
		uom_conv_detail = frappe.qb.DocType("UOM Conversion Detail")
		query = (
			query.left_join(uom_conv_detail)
			.on((uom_conv_detail.parent == item_table.name) & (uom_conv_detail.uom == uom))
			.select(uom_conv_detail.conversion_factor)
		)

	result = query.run(as_dict=1)

	for item_table in result:
		item_details.setdefault(item_table.name, item_table)

	if filters.get("show_variant_attributes"):
		variant_values = get_variant_values_for(list(item_details))
		item_details = {k: v.update(variant_values.get(k, {})) for k, v in item_details.items()}

	return item_details


def get_item_reorder_details(items):
	item_reorder_details = frappe._dict()

	if items:
		item_reorder_details = frappe.get_all(
			"Item Reorder",
			["parent", "warehouse", "warehouse_reorder_qty", "warehouse_reorder_level"],
			filters={"parent": ("in", items)},
		)

	return dict((d.parent + d.warehouse, d) for d in item_reorder_details)

Right now the report is giving me this output below
when from_date is 1 april 2023 and to_date is 3 april 2023

Warehouse Balance Value
Finished Goods - qwqaz 100
Finished Goods - asd 200
Finish Goods- wqe 300
Finished Goods - qwe 400
Finish Goods- asw 500
Finished Goods - qwe 600
Finished Goods - asd 700
IGASDB Item - sys 800
Finish Goods-asd 900
Goods In Transit-sys 1000
Total 5500

But i want this output below(day-wise) the columns must be created dynamically
when from_date is 1 april 2023 and to_date is 3 april 2023

Warehouse Balance Value on 03-04-2023 Balance Value on 02-04-2023 Balance Value on 01-04-2023
Finished Goods - qwqaz 100 100 100
Finished Goods - asd 200 100 50
Finish Goods- wqe 300 150 90
Finished Goods - qwe 400 190 100
Finish Goods- asw 500 120 90
Finished Goods - qwe 600 100 100
Finished Goods - asd 700 500 150
IGASDB Item - sys 800 600 200
Finish Goods-asd 900 690 300
Goods In Transit-sys 1000 700 400
Total 5500 3250 1580

NOW I HAVE ADDED THIS FILTER

{
			"fieldname": "day_wise",
			"label": __("Day Wise"),
			"fieldtype": "Check",
			"default": 1
		},

Now I need some help in building logic and like in which functions i should modify. And if possible a code with output will be more helpful for learning and understanding.