如何使用 sqlalchemy 计算平均数?
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【中文标题】如何使用 sqlalchemy 计算平均数?【英文标题】:How to take avg on count using sqlalchemy? 【发布时间】:2020-05-27 03:33:46 【问题描述】:如何在 SQLAlchemy 中获取平均计数? 我尝试了很多东西,但都失败了。 代码:
month = sqlalchemy.func.date_trunc('month', Complaint.date)
records_count = sqlalchemy.sql.func.count(ClientGroupRecord.id)
complained_clients = session.query(Friend, records_count.label('count'), month). \
filter(Friend.friend_id == friend_id). \
join(Complaint, Complaint.friend == Friend.friend_id). \
join(ClientGroup, Complaint.client_group == ClientGroup.client_group_id). \
join(ClientGroupRecord, ClientGroup.client_group_id == ClientGroupRecord.client_group_id). \
join(Client, Client.client_id == ClientGroupRecord.client_id). \
group_by(month, Friend.friend_id)
records_avg = sqlalchemy.sql.func.avg(records_count)
result = ???
在result
中,我不需要Friend
,但希望在列上使用avg
,该列标记为count
,按month
列分组。
【问题讨论】:
如果您提供一些您所做的尝试,通常有助于获得正确的答案。 相关:***.com/questions/33826441/… 【参考方案1】:一个选项是使用窗口函数,如果您的 DBMS 支持它们 - 基于 date_trunc
的使用我假设您使用的是 PostgreSQL。这样做的原因是在 GROUP BY 生成组行之后评估窗口函数。所以将计数包装在AVG(...) OVER ()
中,其中窗口是整个结果集:
from sqlalchemy import func
month = func.date_trunc('month', Complaint.date)
records_count = func.count(ClientGroupRecord.id)
# Create a window of the whole set of results
records_avg = func.avg(records_count).over()
complained_clients = session.query(records_count.label('count'),
records_avg.label('avg'),
month.label('month')). \
select_from(Friend). \
join(Complaint, Complaint.friend == Friend.friend_id). \
join(ClientGroup, Complaint.client_group == ClientGroup.client_group_id). \
join(ClientGroupRecord, ClientGroup.client_group_id == ClientGroupRecord.client_group_id). \
join(Client, Client.client_id == ClientGroupRecord.client_id). \
filter(Friend.friend_id == friend_id). \
group_by(month). \
all()
请注意,Friend
已从 query(...)
移动到显式用作与 Query.select_from()
的第一个连接的左侧。即使您只选择具有特定 ID 的朋友,也无需在 GROUP BY 子句中使用 Friend.id
。
如果您对每月计数根本不感兴趣,而只想要平均值,那么更传统的subquery approach 也一样好:
from sqlalchemy import func
month = func.date_trunc('month', Complaint.date)
records_count = func.count(ClientGroupRecord.id)
complained_clients = session.query(records_count.label('count')). \
select_from(Friend). \
join(Complaint, Complaint.friend == Friend.friend_id). \
join(ClientGroup, Complaint.client_group == ClientGroup.client_group_id). \
join(ClientGroupRecord, ClientGroup.client_group_id == ClientGroupRecord.client_group_id). \
join(Client, Client.client_id == ClientGroupRecord.client_id). \
filter(Friend.friend_id == friend_id). \
group_by(month). \
subquery()
result = session.query(func.avg(complained_clients.c.count)).scalar()
...或使用窗口方法:
from sqlalchemy import func
month = func.date_trunc('month', Complaint.date)
records_count = func.count(ClientGroupRecord.id)
# Create a window of the whole set of results
records_avg = func.avg(records_count).over()
# Windows are evaluated for each row, but here we have a single window spanning
# the entire result, so the use of DISTINCT collapses this to a single value.
# Knowing what the query does LIMIT 1 / FETCH FIRST 1 ROW ONLY would work as well.
result = session.query(records_avg.label('avg')). \
select_from(Friend). \
join(Complaint, Complaint.friend == Friend.friend_id). \
join(ClientGroup, Complaint.client_group == ClientGroup.client_group_id). \
join(ClientGroupRecord, ClientGroup.client_group_id == ClientGroupRecord.client_group_id). \
join(Client, Client.client_id == ClientGroupRecord.client_id). \
filter(Friend.friend_id == friend_id). \
group_by(month). \
distinct(). \
scalar()
【讨论】:
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