我进行了一个SQL查询，该查询在表中复制一行（实际上是删除并插入新行），同时按给定的TIMESTAMPS拆分其原始TSRANGE字段。 据我测试，它工作得很好。以下是一个演示我的意思的演示，为方便起见here is a fiddle：
-- demo initialisation
CREATE TABLE random_table (
uid VARCHAR(36) PRIMARY KEY,
id VARCHAR(20),
tsrange_field TSRANGE
);
CREATE EXTENSION pgcrypto; -- needed for `gen_random_uuid` function
INSERT INTO public.random_table (uid, id, tsrange_field)
VALUES (gen_random_uuid(), 'random_id', tsrange('2000-01-01', '2020-01-01', '[)'));
-- actual query
WITH splitters AS (
SELECT uid, datetime
FROM random_table
JOIN unnest(ARRAY['2015-04-15'::timestamp, '2016-04-15'::timestamp, '2017-01-01'::timestamp, '2017-04-15'::timestamp]) datetime
ON tsrange_field @> datetime
WHERE id = 'random_id'
AND (lower(random_table.tsrange_field) IS NULL OR lower(random_table.tsrange_field) != datetime)
AND (upper(random_table.tsrange_field) IS NULL OR upper(random_table.tsrange_field) != datetime)
), to_be_splitted AS (
DELETE FROM random_table
USING splitters
WHERE splitters.uid = random_table.uid
RETURNING random_table.uid, id, tsrange_field
)
INSERT INTO random_table (uid, id, tsrange_field)
SELECT DISTINCT ON (id, tsrange_field)
gen_random_uuid() AS uid, id,
unnest(ARRAY[
tsrange(
CASE
WHEN LAG(splitters.datetime) OVER (PARTITION BY splitters.uid ORDER BY splitters.datetime) IS NOT NULL
THEN LAG(splitters.datetime) OVER (PARTITION BY splitters.uid ORDER BY splitters.datetime)
ELSE lower(tsrange_field)
END,
splitters.datetime,
'[)'
),
tsrange(
splitters.datetime,
CASE
WHEN LEAD(splitters.datetime) OVER (PARTITION BY splitters.uid ORDER BY splitters.datetime) IS NOT NULL
THEN LEAD(splitters.datetime) OVER (PARTITION BY splitters.uid ORDER BY splitters.datetime)
ELSE upper(tsrange_field)
END,
'[)'
)
]) AS tsrange_field
FROM to_be_splitted JOIN splitters ON to_be_splitted.uid = splitters.uid
ORDER BY tsrange_field
RETURNING *;
现在我想将其翻译为sqlalchemy，这就是我的问题所在。我产生了以下代码：
# pip install psycopg2, sqlalchemy
from datetime import datetime
from sqlalchemy import (and_, case, cast, column, Column, create_engine, delete, func,
insert, MetaData, or_, select, Table, VARCHAR)
from sqlalchemy.dialects.postgresql import array, TSRANGE, ARRAY
METADATA = MetaData()
RANDOM_TABLE = Table(
'random_table', METADATA,
Column('uid', VARCHAR(36), primary_key=True),
Column('id', VARCHAR(20)),
Column('tsrange_field', TSRANGE)
)
engine = create_engine('postgresql://test:test@localhost:5432/test')
def split_row(id, *datetimes):
# this function contains the translation attempt
splits = func.unnest([dt for dt in datetimes]).alias('datetime')
datetime_col = column('datetime')
splitters = (
select([RANDOM_TABLE.c.uid, datetime_col])
.select_from(RANDOM_TABLE.join(
splits,
onclause=RANDOM_TABLE.c.tsrange_field.op('@>')(datetime_col)
))
.where(and_(
RANDOM_TABLE.c.id == id,
or_(func.lower(RANDOM_TABLE.c.tsrange_field) == None,
func.lower(RANDOM_TABLE.c.tsrange_field).op('!=')(datetime_col)),
or_(func.upper(RANDOM_TABLE.c.tsrange_field) == None,
func.upper(RANDOM_TABLE.c.tsrange_field).op('!=')(datetime_col)),
))
).cte('splitters')
to_be_split = (
delete(RANDOM_TABLE)
.where(splitters.c.uid == RANDOM_TABLE.c.uid)
.returning(RANDOM_TABLE.c.uid, RANDOM_TABLE.c.tsrange_field)
).cte('to_be_split')
window_params = {'partition_by': column('uid'),
'order_by': datetime_col}
previous_splitter = func.lag(datetime_col).over(**window_params)
next_splitter = func.lead(datetime_col).over(**window_params)
lower_bound_case = case(
[(previous_splitter != None, previous_splitter)],
else_=func.lower(column('tsrange_field'))
)
upper_bound_case = case(
[(next_splitter != None, next_splitter)],
else_=func.upper(column('tsrange_field'))
)
split_tsranges = [
func.tsrange(lower_bound_case, datetime_col, '[)'),
func.tsrange(datetime_col, upper_bound_case, '[)')
]
split_query = select([
func.gen_random_uuid().label('uid'),
func.unnest(split_tsranges).alias('tsrange_field') # does not work
]).distinct(
column('tsrange_field')
).select_from(
to_be_split
.join(splitters, onclause=to_be_split.c.uid == splitters.c.uid)
).order_by(
column('tsrange_field')
)
whole_query = (
insert(RANDOM_TABLE)
.from_select([column('uid'), column('tsrange_field')], split_query)
.returning(column('uid'), column('tsrange_field'))
)
return whole_query
with engine.connect() as conn:
query = split_row('random_id', datetime.now())
import pdb; pdb.set_trace()
print(conn.execute(query).fetchall())
不幸的是，它失败并显示以下消息：
Traceback (most recent call last):
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1244, in _execute_context
cursor, statement, parameters, context
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/default.py", line 552, in do_execute
cursor.execute(statement, parameters)
psycopg2.ProgrammingError: can't adapt type 'Function'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "stuck.py", line 85, in <module>
print(conn.execute(query).fetchall())
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 988, in execute
return meth(self, multiparams, params)
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 287, in _execute_on_connection
return connection._execute_clauseelement(self, multiparams, params)
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1107, in _execute_clauseelement
distilled_params,
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1248, in _execute_context
e, statement, parameters, cursor, context
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1466, in _handle_dbapi_exception
util.raise_from_cause(sqlalchemy_exception, exc_info)
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 383, in raise_from_cause
reraise(type(exception), exception, tb=exc_tb, cause=cause)
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 128, in reraise
raise value.with_traceback(tb)
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1244, in _execute_context
cursor, statement, parameters, context
File "/home/tryph/sql_split/.env/lib/python3.6/site-packages/sqlalchemy/engine/default.py", line 552, in do_execute
cursor.execute(statement, parameters)
sqlalchemy.exc.ProgrammingError: (psycopg2.ProgrammingError) can't adapt type 'Function'
[SQL: WITH splitters AS
(SELECT random_table.uid AS uid, datetime
FROM random_table JOIN unnest(%(unnest_3)s) AS datetime ON random_table.tsrange_field @> datetime
WHERE random_table.id = %(id_1)s AND (lower(random_table.tsrange_field) IS NULL OR (lower(random_table.tsrange_field) != datetime)) AND (upper(random_table.tsrange_field) IS NULL OR (upper(random_table.tsrange_field) != datetime))),
to_be_split AS
(DELETE FROM random_table USING splitters WHERE splitters.uid = random_table.uid RETURNING random_table.uid, random_table.tsrange_field)
INSERT INTO random_table (uid, tsrange_field) SELECT DISTINCT ON (tsrange_field) gen_random_uuid() AS uid, tsrange_field.unnest_1
FROM unnest(%(unnest_2)s) AS tsrange_field, to_be_split JOIN splitters ON to_be_split.uid = splitters.uid ORDER BY tsrange_field RETURNING uid, tsrange_field]
[parameters: {'unnest_2': [<sqlalchemy.sql.functions.Function at 0x7fba18954a20; tsrange>, <sqlalchemy.sql.functions.Function at 0x7fba18954b00; tsrange>], 'unnest_3': [datetime.datetime(2019, 5, 3, 23, 37, 1, 773118)], 'id_1': 'random_id'}]
(Background on this error at: http://sqlalche.me/e/f405)
在查看生成的SQL时，我注意到原始SQL查询的unnest(ARRAY[...]) AS tsrange_field中的SELECT在FROM子句中呈现，我不知道为什么。另外，消息psycopg2.ProgrammingError: can't adapt type 'Function'并没有提供很大的帮助，并且似乎与unnest的错误呈现无关。
任何有关发生的情况以及如何解决的提示将不胜感激。
答案 0 :(得分：1)
您已经注意到，有问题的部分是
split_query = select([
func.gen_random_uuid().label('uid'),
func.unnest(split_tsranges).alias('tsrange_field') # does not work
])
，问题在于FunctionElement.alias()用于生成适合FROM子句的命名别名，因此SQLAlchemy将其移到那里。使用label('tsrange_field')来产生AS tsrange_field。另一个问题是，SQLAlchemy将列表按原样传递给DB-API驱动程序，该驱动程序不知道如何处理SQLAlchemy构造。将列表包装在对array()的调用中，以便SQLAlchemy呈现带有嵌套表达式的ARRAY文字：
split_tsranges = array([
func.tsrange(lower_bound_case, datetime_col, '[)'),
func.tsrange(datetime_col, upper_bound_case, '[)')
])