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stock_valuation_xlsx: Speed-up for past valuation when few of the total products are in stock

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Closer to PEP8
This commit is contained in:
Alexis de Lattre
2020-09-25 12:19:26 +02:00
parent 1e4de02259
commit 063924fdc7
1 changed files with 31 additions and 20 deletions
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51
stock_valuation_xlsx/wizard/stock_valuation_xlsx.py
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@@ -5,7 +5,7 @@
from odoo import models, fields, api, _ from odoo import models, fields, api, _
from odoo.exceptions import UserError from odoo.exceptions import UserError
from odoo.tools import float_compare, float_is_zero, float_round from odoo.tools import float_is_zero, float_round
from cStringIO import StringIO from cStringIO import StringIO
from datetime import datetime from datetime import datetime
import xlsxwriter import xlsxwriter
@@ -105,19 +105,25 @@ class StockValuationXlsx(models.TransientModel):
domain += [('categ_id', 'child_of', self.categ_ids.ids)] domain += [('categ_id', 'child_of', self.categ_ids.ids)]
return domain return domain
def get_product_ids(self):
self.ensure_one()
domain = self._prepare_product_domain()
products = self.env['product.product'].search(domain)
return products.ids
def _prepare_product_fields(self): def _prepare_product_fields(self):
return ['uom_id', 'name', 'default_code', 'categ_id'] return ['uom_id', 'name', 'default_code', 'categ_id']
def compute_product_data(self, company_id, past_date=False): def compute_product_data(
self, company_id, in_stock_product_ids, past_date=False):
self.ensure_one() self.ensure_one()
logger.debug('Start compute_product_data') logger.debug('Start compute_product_data')
ppo = self.env['product.product'] ppo = self.env['product.product']
ppho = self.env['product.price.history'] ppho = self.env['product.price.history']
domain = self._prepare_product_domain()
fields_list = self._prepare_product_fields() fields_list = self._prepare_product_fields()
if not past_date: if not past_date:
fields_list.append('standard_price') fields_list.append('standard_price')
products = ppo.search_read(domain, fields_list) products = ppo.search_read([('id', 'in', in_stock_product_ids)], fields_list)
product_id2data = {} product_id2data = {}
now = fields.Datetime.now() now = fields.Datetime.now()
for p in products: for p in products:
@@ -186,6 +192,7 @@ class StockValuationXlsx(models.TransientModel):
('product_qty', '>', 0), ('product_qty', '>', 0),
], ['product_id', 'location_id', 'prod_lot_id', 'product_qty']) ], ['product_id', 'location_id', 'prod_lot_id', 'product_qty'])
res = [] res = []
in_stock_products = {}
for l in inv_lines: for l in inv_lines:
if not float_is_zero(l['product_qty'], precision_digits=prec_qty): if not float_is_zero(l['product_qty'], precision_digits=prec_qty):
res.append({ res.append({
@@ -194,8 +201,9 @@ class StockValuationXlsx(models.TransientModel):
'qty': l['product_qty'], 'qty': l['product_qty'],
'location_id': l['location_id'][0], 'location_id': l['location_id'][0],
}) })
in_stock_products[l['product_id'][0]] = True
logger.debug('End compute_data_from_inventory') logger.debug('End compute_data_from_inventory')
return res return res, in_stock_products
def compute_data_from_present_stock(self, company_id, product_ids, prec_qty): def compute_data_from_present_stock(self, company_id, product_ids, prec_qty):
self.ensure_one() self.ensure_one()
@@ -206,6 +214,7 @@ class StockValuationXlsx(models.TransientModel):
('company_id', '=', company_id), ('company_id', '=', company_id),
], ['product_id', 'lot_id', 'location_id', 'qty']) ], ['product_id', 'lot_id', 'location_id', 'qty'])
res = [] res = []
in_stock_products = {}
for quant in quants: for quant in quants:
if not float_is_zero(quant['qty'], precision_digits=prec_qty): if not float_is_zero(quant['qty'], precision_digits=prec_qty):
res.append({ res.append({
@@ -214,8 +223,9 @@ class StockValuationXlsx(models.TransientModel):
'location_id': quant['location_id'][0], 'location_id': quant['location_id'][0],
'qty': quant['qty'], 'qty': quant['qty'],
}) })
in_stock_products[quant['product_id'][0]] = True
logger.debug('End compute_data_from_present_stock') logger.debug('End compute_data_from_present_stock')
return res return res, in_stock_products
def compute_data_from_past_stock(self, product_ids, prec_qty, past_date): def compute_data_from_past_stock(self, product_ids, prec_qty, past_date):
self.ensure_one() self.ensure_one()
@@ -223,17 +233,19 @@ class StockValuationXlsx(models.TransientModel):
ppo = self.env['product.product'] ppo = self.env['product.product']
products = ppo.with_context(to_date=past_date, location_id=self.location_id.id).browse(product_ids) products = ppo.with_context(to_date=past_date, location_id=self.location_id.id).browse(product_ids)
res = [] res = []
for p in products: in_stock_products = {}
qty = p.qty_available for product in products:
qty = product.qty_available
if not float_is_zero(qty, precision_digits=prec_qty): if not float_is_zero(qty, precision_digits=prec_qty):
res.append({ res.append({
'product_id': p.id, 'product_id': product.id,
'qty': qty, 'qty': qty,
'lot_id': False, 'lot_id': False,
'location_id': False, 'location_id': False,
}) })
in_stock_products[product.id] = True
logger.debug('End compute_data_from_past_stock') logger.debug('End compute_data_from_past_stock')
return res return res, in_stock_products
def group_result(self, data, split_by_lot, split_by_location): def group_result(self, data, split_by_lot, split_by_location):
logger.debug( logger.debug(
@@ -258,7 +270,6 @@ class StockValuationXlsx(models.TransientModel):
uom_id2name, lot_id2data, loc_id2name): uom_id2name, lot_id2data, loc_id2name):
logger.debug('Start stringify_and_sort_result') logger.debug('Start stringify_and_sort_result')
res = [] res = []
categ_subtotal = self.categ_subtotal
for l in data: for l in data:
product_id = l['product_id'] product_id = l['product_id']
qty = float_round(l['qty'], precision_digits=prec_qty) qty = float_round(l['qty'], precision_digits=prec_qty)
@@ -287,7 +298,6 @@ class StockValuationXlsx(models.TransientModel):
self.ensure_one() self.ensure_one()
logger.debug('Start generate XLSX stock valuation report') logger.debug('Start generate XLSX stock valuation report')
splo = self.env['stock.production.lot'].with_context(active_test=False) splo = self.env['stock.production.lot'].with_context(active_test=False)
pco = self.env['product.category'].with_context(active_test=False)
prec_qty = self.env['decimal.precision'].precision_get('Product Unit of Measure') prec_qty = self.env['decimal.precision'].precision_get('Product Unit of Measure')
prec_price = self.env['decimal.precision'].precision_get('Product Price') prec_price = self.env['decimal.precision'].precision_get('Product Price')
company = self.env.user.company_id company = self.env.user.company_id
@@ -304,18 +314,21 @@ class StockValuationXlsx(models.TransientModel):
past_date = self.past_date past_date = self.past_date
elif self.source == 'inventory': elif self.source == 'inventory':
past_date = self.inventory_id.date past_date = self.inventory_id.date
product_id2data = self.compute_product_data( product_ids = self.get_product_ids()
company_id, past_date=past_date) if not product_ids:
product_ids = product_id2data.keys() raise UserError(_("There are no products to analyse."))
if self.source == 'stock': if self.source == 'stock':
if self.stock_date_type == 'present': if self.stock_date_type == 'present':
data = self.compute_data_from_present_stock( data, in_stock_products = self.compute_data_from_present_stock(
company_id, product_ids, prec_qty) company_id, product_ids, prec_qty)
elif self.stock_date_type == 'past': elif self.stock_date_type == 'past':
data = self.compute_data_from_past_stock( data, in_stock_products = self.compute_data_from_past_stock(
product_ids, prec_qty, past_date) product_ids, prec_qty, past_date)
elif self.source == 'inventory': elif self.source == 'inventory':
data = self.compute_data_from_inventory(product_ids, prec_qty) data, in_stock_products = self.compute_data_from_inventory(product_ids, prec_qty)
in_stock_product_ids = in_stock_products.keys()
product_id2data = self.compute_product_data(
company_id, in_stock_product_ids, past_date=past_date)
data_res = self.group_result(data, split_by_lot, split_by_location) data_res = self.group_result(data, split_by_lot, split_by_location)
categ_id2name, uom_id2name, lot_id2data, loc_id2name = self.id2name(product_ids) categ_id2name, uom_id2name, lot_id2data, loc_id2name = self.id2name(product_ids)
res = self.stringify_and_sort_result( res = self.stringify_and_sort_result(
@@ -339,8 +352,6 @@ class StockValuationXlsx(models.TransientModel):
cols.pop('loc_name', None) cols.pop('loc_name', None)
if not categ_subtotal: if not categ_subtotal:
cols.pop('categ_subtotal', None) cols.pop('categ_subtotal', None)
tmp_list = sorted(cols.items(), key=lambda x: x[1]['sequence'])
col_sorted = [x[0] for x in tmp_list]
j = 0 j = 0
for col, col_vals in sorted(cols.items(), key=lambda x: x[1]['sequence']): for col, col_vals in sorted(cols.items(), key=lambda x: x[1]['sequence']):