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修改大屏数据接口，日完成量统计,获取产线产量相关,获取工单明细

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胡尧
2025-06-19 15:02:55 +08:00
parent d21e0c7fd9
commit 55cc4906ef
1 changed files with 109 additions and 51 deletions
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160
sf_machine_connect/controllers/controllers.py
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@@ -635,25 +635,32 @@ class Sf_Dashboard_Connect(http.Controller):
return date_list
for line in line_list:
date_field_name = 'date_finished' # 替换为你模型中的实际字段名
order_counts = []
if time_unit == 'hour':
for line in line_list:
date_field_name = 'date_finished' # 替换为你模型中的实际字段名
order_counts = []
if line == '业绩总览':
work_order_domain = [('routing_type', 'in', ['人工线下加工', 'CNC加工'])]
elif line == '人工线下加工中心':
work_order_domain = [('routing_type', '=', '人工线下加工')]
else:
work_order_domain = [
('production_line_id.name', '=', line),
('routing_type', '=', 'CNC加工')
]
if time_unit == 'hour':
if line == '业绩总览':
work_order_domain = [('routing_type', 'in', ['人工线下加工', 'CNC加工'])]
elif line == '人工线下加工中心':
work_order_domain = [('routing_type', '=', '人工线下加工')]
else:
work_order_domain = [
('production_line_id.name', '=', line),
('routing_type', '=', 'CNC加工')
]
time_intervals = get_time_intervals(begin_time, end_time, time_unit)
print('============================= %s' % time_intervals)
time_count_dict = {}
plan_count_dict = {}
orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['done']),
(date_field_name, '>=', begin_time.strftime('%Y-%m-%d %H:%M:%S')),
(date_field_name, '<=', end_time.strftime('%Y-%m-%d %H:%M:%S'))
])
for time_interval in time_intervals:
start_time, end_time = time_interval
@@ -665,55 +672,106 @@ class Sf_Dashboard_Connect(http.Controller):
# (date_field_name, '<=', end_time.strftime('%Y-%m-%d %H:%M:%S')) # 包括结束时间
# ])
orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['done']),
(date_field_name, '>=', start_time.strftime('%Y-%m-%d %H:%M:%S')),
(date_field_name, '<=', end_time.strftime('%Y-%m-%d %H:%M:%S'))
])
interval_orders = orders.filtered(
lambda o: o[date_field_name] >= start_time
and o[date_field_name] <= end_time
)
# 使用小时和分钟作为键，确保每个小时的数据有独立的键
key = start_time.strftime('%H:%M:%S') # 只取小时:分钟:秒作为键
# time_count_dict[key] = len(orders)
time_count_dict[key] = sum(orders.mapped('qty_produced'))
time_count_dict[key] = sum(interval_orders.mapped('qty_produced'))
# 计划量，目前只能从mail.message中筛选出
plan_order_messages = request.env['mail.message'].sudo().search([
('model', '=', 'mrp.workorder'),
('create_date', '>=', begin_time.strftime('%Y-%m-%d %H:%M:%S')),
('create_date', '<=', end_time.strftime('%Y-%m-%d %H:%M:%S')),
('tracking_value_ids.field_desc', '=', '状态'),
('tracking_value_ids.new_value_char', '=', '就绪')
])
for time_interval in time_intervals:
start_time, end_time = time_interval
# orders = plan_obj.search([
# ('production_line_id.name', '=', line),
# ('state', 'in', ['done']),
# (date_field_name, '>=', start_time.strftime('%Y-%m-%d %H:%M:%S')),
# (date_field_name, '<=', end_time.strftime('%Y-%m-%d %H:%M:%S')) # 包括结束时间
# ])
interval_plan_orders = plan_order_messages.filtered(
lambda o: o.create_date >= start_time
and o.create_date <= end_time
)
interval_orders = request.env['mrp.workorder'].sudo().browse(interval_plan_orders.mapped('res_id'))
if line == '业绩总览':
interval_orders = interval_orders.filtered(lambda o: o.routing_type in ['人工线下加工', 'CNC加工'])
elif line == '人工线下加工中心':
interval_orders = interval_orders.filtered(lambda o: o.routing_type == '人工线下加工')
else:
interval_orders = interval_orders.filtered(lambda o: o.routing_type == 'CNC加工' and o.production_line_id.name == line)
# 使用小时和分钟作为键，确保每个小时的数据有独立的键
key = start_time.strftime('%H:%M:%S') # 只取小时:分钟:秒作为键
# time_count_dict[key] = len(orders)
plan_count_dict[key] = sum(interval_orders.mapped('qty_produced'))
# order_counts.append()
res['data'][line] = {
'finish_order_nums': time_count_dict,
'plan_order_nums': 28
'plan_order_nums': plan_count_dict
}
return json.dumps(res)
else:
date_list = get_date_list(begin_time, end_time)
for line in line_list:
date_field_name = 'date_finished' # 替换为你模型中的实际字段名
order_counts = []
for date in date_list:
next_day = date + timedelta(days=1)
orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['done']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
if line == '业绩总览':
work_order_domain = [('routing_type', 'in', ['人工线下加工', 'CNC加工'])]
elif line == '人工线下加工中心':
work_order_domain = [('routing_type', '=', '人工线下加工')]
else:
work_order_domain = [
('production_line_id.name', '=', line),
('routing_type', '=', 'CNC加工')
]
rework_orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['rework']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
not_passed_orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['scrap', 'cancel']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
order_counts.append({
'date': date.strftime('%Y-%m-%d'),
'order_count': sum(orders.mapped('qty_produced')),
'rework_orders': sum(rework_orders.mapped('qty_produced')),
'not_passed_orders': sum(not_passed_orders.mapped('qty_produced'))
})
# 外面包一层，没什么是包一层不能解决的，包一层就能区分了，类似于包一层div
# 外面包一层的好处是，可以把多个数据结构打包在一起，方便前端处理
date_list = get_date_list(begin_time, end_time)
# date_list_dict = {line: order_counts}
for date in date_list:
next_day = date + timedelta(days=1)
orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['done']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
res['data'][line] = order_counts
rework_orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['rework']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
not_passed_orders = request.env['mrp.workorder'].sudo().search(work_order_domain + [
('state', 'in', ['scrap', 'cancel']),
(date_field_name, '>=', date.strftime('%Y-%m-%d 00:00:00')),
(date_field_name, '<', next_day.strftime('%Y-%m-%d 00:00:00'))
])
order_counts.append({
'date': date.strftime('%Y-%m-%d'),
'order_count': sum(orders.mapped('qty_produced')),
'rework_orders': sum(rework_orders.mapped('qty_produced')),
'not_passed_orders': sum(not_passed_orders.mapped('qty_produced'))
})
# 外面包一层，没什么是包一层不能解决的，包一层就能区分了，类似于包一层div
# 外面包一层的好处是，可以把多个数据结构打包在一起，方便前端处理
# date_list_dict = {line: order_counts}
res['data'][line] = order_counts
return json.dumps(res)
# 实时产量
@@ -799,7 +857,7 @@ class Sf_Dashboard_Connect(http.Controller):
:param kw:
:return:
"""
request.env['stock.warehouse'].browse(request.env.company.id).pbm_loc_id
# res = {'status': 1, 'message': '成功', 'not_done_data': [], 'done_data': []}
res = {'status': 1, 'message': '成功', 'data': {}}
plan_obj = request.env['sf.production.plan'].sudo()