#!/usr/bin/env python
# -*- coding: utf-8 -*-
from mongo import op
import logging
logger = logging.getLogger(__name__)
import re
price_pattern = re.compile(r'^\d+\.\d\d$')
from multiprocess.tools import timeUtil
from jingdong.Tools import format_cat_id
current_date = timeUtil.current_time()
price_pattern = re.compile(r'^\d+\.\d\d$')
def clean_price(item):
price_tmp = []
for key in item:
current_value = str(item[key])
str_price_list = price_pattern.findall(current_value)
if str_price_list and str_price_list[0] != "-1.00":
price_tmp.append(float(str_price_list[0]))
if price_tmp:
price = min(price_tmp)
else:
price = 79.90
return price
def run_result():
with op.DBManger() as m:
brandid2name={}
for brand_id, brand_name in m.read_from(db_collect=("jingdong", "jdbrand20210108retry0"),
out_field=("brand_id", "name")):
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from multiprocess.tools import timeUtil, collections
from mongo import op
print(timeUtil.getdate(0, format="%Y-%m%d"))
print(timeUtil.current_time())
dt = collections.DataSet([1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6])
for i in dt.shuffle(
buffer_size=3).map(lambda x: x * 2).map(lambda x: x + 1).distinct():
print(i)
with op.DBManger() as m:
last_brand_collect = m.get_lasted_collection(
"jingdong", filter={"name": {
"$regex": r"^brand20\d\d\d\d\d\d$"
}})
pipeline = [{
"$match": {
"cate_id": {
"$ne": None
}
}
}, {
"$match": {
"brand_id": {
"$ne": None
}
}
}, {
"$match": {
