WDJ36-II电位器
时间: 2023-08-13 07:10:43 浏览: 39
抱歉,我无法理解您的问题。WDJ36-II电位器是一种电子元件,用于调节电路中的电压或电流。它具有一定的阻值范围,可以通过旋转或滑动来改变电阻值。如果您有关于WDJ36-II电位器的具体问题,请提供更多细节,我将尽力回答。
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- *1* *2* *3* [从零实现深度学习框架——常见运算的计算图](https://blog.csdn.net/yjw123456/article/details/122024945)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control,239^v3^insert_chatgpt"}} ] [.reference_item]
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相关问题
获取https://www.wandoujia.com/apps/8130841/strategy?spm=aligames_platform_ug.wdj_seo.0.0.37965db8I6C3zN下所有链接地址并以表格保存在本地
你可以使用Python的requests库来获取网页内容,然后使用BeautifulSoup库来解析HTML文档,进而提取所有链接地址并保存为表格。以下是一个示例代码:
```python
import requests
from bs4 import BeautifulSoup
import csv
# 获取网页内容
url = "https://www.wandoujia.com/apps/8130841/strategy?spm=aligames_platform_ug.wdj_seo.0.0.37965db8I6C3zN"
response = requests.get(url)
content = response.content
# 解析HTML文档
soup = BeautifulSoup(content, 'html.parser')
# 找到所有链接地址
links = soup.find_all('a')
# 将链接地址保存到表格
filename = 'links.csv' # 保存文件的名称
with open(filename, 'w', newline='', encoding='utf-8') as file:
writer = csv.writer(file)
writer.writerow(['链接地址']) # 表头
for link in links:
writer.writerow([link.get('href')])
print(f"链接地址已保存到文件 {filename}")
```
请注意,上述代码中的URL需要根据指定页面的实际情况进行修改。同时,你还需要安装相应的库,可以使用`pip install requests`和`pip install beautifulsoup4`命令进行安装。运行代码后,将会在当前目录下生成一个名为 `links.csv` 的文件,其中包含了所有链接地址。
优化sql:SELECT we.organization_id ,we.wip_entity_id ,case when wl.line_id is null then we.wip_entity_name else '' end wip_entity_name ,we.primary_item_id ,mtt.transaction_type_name ,mmt.transaction_date ,bd.department_code ,mmt.inventory_item_id ,mmt.subinventory_code ,mta.reference_account ,br.resource_code ,lu2.meaning as line_type_name ,mta.base_transaction_value ,mta.cost_element_id ,flv.meaning as cost_element ,wdj.class_code job_type_code ,ml.meaning job_type_name FROM (select * from gerp.mtl_material_transactions where substr(transaction_date,1,7) >= '2023-06' and transaction_source_type_id = 5) mmt inner join gerp.wip_entities we on mmt.organization_id = we.organization_id inner join gerp.mtl_transaction_accounts mta on mta.transaction_source_id = we.wip_entity_id and mta.transaction_id = mmt.transaction_id and mta.transaction_source_type_id = 5 inner join gerp.mtl_transaction_types mtt on mtt.transaction_type_id = mmt.transaction_type_id inner join mfg_lookups lu2 on lu2.lookup_code = mta.accounting_line_type and lu2.lookup_type = 'CST_ACCOUNTING_LINE_TYPE' inner join gerp.mtl_system_items_b msi on msi.inventory_item_id = mmt.inventory_item_id and msi.organization_id = mta.organization_id left join gerp.bom_departments bd on bd.department_id = mmt.department_id left join gerp.bom_resources br on br.resource_id = mta.resource_id left join gerp.wip_lines wl on wl.line_id = mmt.repetitive_line_id left join gerp.wip_discrete_jobs wdj on wdj.wip_entity_id = mta.transaction_source_id left join gerp.fnd_lookup_values_vl flv on cast(mta.cost_element_id as string) = flv.lookup_code and flv.lookup_type = 'CST_COST_CODE_TYPE' left join mfg_lookups ml on ml.lookup_code = wdj.job_type and ml.lookup_type = 'WIP_DISCRETE_JOB' 。其中mmt,we,mta,msi,wdj数据量很大
针对这个SQL语句,可以优化的地方有:
1. 使用JOIN语句时,可以根据数据量大小,将数据量大的表放在后面,这样可以避免在连接时出现性能问题。
2. 使用子查询时,可以在子查询中添加条件筛选,减少返回的数据量。
3. 可以对查询中的日期条件进行优化,例如使用日期范围查询时,可以使用BETWEEN关键字代替大于等于和小于等于的运算符。
4. 可以对大表进行分区或分片,以加快查询速度。
5. 可以对JOIN语句中的字段添加索引,以提高查询效率。
下面是对原SQL语句的优化:
```
SELECT
we.organization_id,
we.wip_entity_id,
CASE WHEN wl.line_id is null THEN we.wip_entity_name ELSE '' END wip_entity_name,
we.primary_item_id,
mtt.transaction_type_name,
mmt.transaction_date,
bd.department_code,
mmt.inventory_item_id,
mmt.subinventory_code,
mta.reference_account,
br.resource_code,
lu2.meaning as line_type_name,
mta.base_transaction_value,
mta.cost_element_id,
flv.meaning as cost_element,
wdj.class_code job_type_code,
ml.meaning job_type_name
FROM
gerp.wip_entities we
INNER JOIN (
SELECT
*
FROM
gerp.mtl_material_transactions
WHERE
transaction_date BETWEEN '2023-06-01' AND '2023-06-30'
AND transaction_source_type_id = 5
) mmt ON mmt.organization_id = we.organization_id
INNER JOIN gerp.mtl_transaction_accounts mta ON mta.transaction_source_id = we.wip_entity_id
AND mta.transaction_id = mmt.transaction_id
AND mta.transaction_source_type_id = 5
INNER JOIN gerp.mtl_transaction_types mtt ON mtt.transaction_type_id = mmt.transaction_type_id
INNER JOIN mfg_lookups lu2 ON lu2.lookup_code = mta.accounting_line_type AND lu2.lookup_type = 'CST_ACCOUNTING_LINE_TYPE'
INNER JOIN gerp.mtl_system_items_b msi ON msi.inventory_item_id = mmt.inventory_item_id
AND msi.organization_id = mta.organization_id
LEFT JOIN gerp.bom_departments bd ON bd.department_id = mmt.department_id
LEFT JOIN gerp.bom_resources br ON br.resource_id = mta.resource_id
LEFT JOIN gerp.wip_lines wl ON wl.line_id = mmt.repetitive_line_id
LEFT JOIN gerp.wip_discrete_jobs wdj ON wdj.wip_entity_id = mta.transaction_source_id
LEFT JOIN gerp.fnd_lookup_values_vl flv ON cast(mta.cost_element_id as string) = flv.lookup_code
AND flv.lookup_type = 'CST_COST_CODE_TYPE'
LEFT JOIN mfg_lookups ml ON ml.lookup_code = wdj.job_type AND ml.lookup_type = 'WIP_DISCRETE_JOB';
```
在优化后的SQL语句中,将子查询中的日期范围查询放在了WHERE语句中,将数据量较大的表放在了后面,左连接的表也放在了后面。同时,可以根据具体情况对需要添加索引的字段进行索引优化。