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How to filter if this id not exist in another table?

I'm try to filter if id of column A not exist in column B by this code.
query = db.session.query().select_from(Spare_Parts, Vendors, Replacement)\
.filter(Vendors.vendor_code == Spare_Parts.vendor_code,\
~ exists().where(Spare_Parts.spare_part_code == Replacement.spare_part_code))
I want to query the data from Spare_Parts that not have an id exist in Replacement as a foriegn key but i got the error like this.
Select statement 'SELECT *
FROM spare_parts, replacement
WHERE spare_parts.spare_part_code = replacement.spare_part_code' returned no FROM clauses due to auto-correlation; specify correlate(<tables>) to control correlation manually.
So what is a problem and how to fix that.

try to use the subquery like this instead
to filter spare_part_code from spare_parts which are not in replacement table``
SELECT *
FROM spare_parts
WHERE spare_parts.spare_part_code not in
(select distinct
replacement.spare_part_code
FROM replacement)
or you can use not exists
SELECT *
FROM spare_parts
WHERE not exists
(select 1
FROM replacement
where spare_parts.spare_parts_code = replacement.spare_parts_code)

Python sqlite - insert if not exists [duplicate]

I have an SQLite database. I am trying to insert values (users_id, lessoninfo_id) in table bookmarks, only if both do not exist before in a row.
INSERT INTO bookmarks(users_id,lessoninfo_id)
VALUES(
(SELECT _id FROM Users WHERE User='"+$('#user_lesson').html()+"'),
(SELECT _id FROM lessoninfo
WHERE Lesson="+lesson_no+" AND cast(starttime AS int)="+Math.floor(result_set.rows.item(markerCount-1).starttime)+")
WHERE NOT EXISTS (
SELECT users_id,lessoninfo_id from bookmarks
WHERE users_id=(SELECT _id FROM Users
WHERE User='"+$('#user_lesson').html()+"') AND lessoninfo_id=(
SELECT _id FROM lessoninfo
WHERE Lesson="+lesson_no+")))
This gives an error saying:
db error near where syntax.

If you never want to have duplicates, you should declare this as a table constraint:
CREATE TABLE bookmarks(
users_id INTEGER,
lessoninfo_id INTEGER,
UNIQUE(users_id, lessoninfo_id)
);
(A primary key over both columns would have the same effect.)
It is then possible to tell the database that you want to silently ignore records that would violate such a constraint:
INSERT OR IGNORE INTO bookmarks(users_id, lessoninfo_id) VALUES(123, 456)

If you have a table called memos that has two columns id and text you should be able to do like this:
INSERT INTO memos(id,text)
SELECT 5, 'text to insert'
WHERE NOT EXISTS(SELECT 1 FROM memos WHERE id = 5 AND text = 'text to insert');
If a record already contains a row where text is equal to 'text to insert' and id is equal to 5, then the insert operation will be ignored.
I don't know if this will work for your particular query, but perhaps it give you a hint on how to proceed.
I would advice that you instead design your table so that no duplicates are allowed as explained in #CLs answer below.

For a unique column, use this:
INSERT OR REPLACE INTO tableName (...) values(...);
For more information, see: sqlite.org/lang_insert

insert into bookmarks (users_id, lessoninfo_id)
select 1, 167
EXCEPT
select user_id, lessoninfo_id
from bookmarks
where user_id=1
and lessoninfo_id=167;
This is the fastest way.
For some other SQL engines, you can use a Dummy table containing 1 record.
e.g:
select 1, 167 from ONE_RECORD_DUMMY_TABLE

How to convert SQL scalar subquery to SQLAlchemy expression

I need a litle help with expressing in SQLAlchemy language my code like this:
SELECT
s.agent_id,
s.property_id,
p.address_zip,
(
SELECT v.valuation
FROM property_valuations v WHERE v.zip_code = p.address_zip
ORDER BY ABS(DATEDIFF(v.as_of, s.date_sold))
LIMIT 1
) AS back_valuation,
FROM sales s
JOIN properties p ON s.property_id = p.id
Inner subquery aimed to get property value from table propert_valuations with columns (zip_code INT, valuation DECIMAL, as_if DATE) closest to the date of sale from table sales. I know how to rewrite it but I completely stuck on order_by expression - I cannot prepare subquery to pass ordering member later.
Currently I have following queries:
subquery = (
session.query(PropertyValuation)
.filter(PropertyValuation.zip_code == Property.address_zip)
.order_by(func.abs(func.datediff(PropertyValuation.as_of, Sale.date_sold)))
.limit(1)
)
query = session.query(Sale).join(Sale.property_)
How to combine these queries together?

How to combine these queries together?
Use as_scalar(), or label():
subquery = (
session.query(PropertyValuation.valuation)
.filter(PropertyValuation.zip_code == Property.address_zip)
.order_by(func.abs(func.datediff(PropertyValuation.as_of, Sale.date_sold)))
.limit(1)
)
query = session.query(Sale.agent_id,
Sale.property_id,
Property.address_zip,
# `subquery.as_scalar()` or
subquery.label('back_valuation'))\
.join(Property)
Using as_scalar() limits returned columns and rows to 1, so you cannot get the whole model object using it (as query(PropertyValuation) is a select of all the attributes of PropertyValuation), but getting just the valuation attribute works.
but I completely stuck on order_by expression - I cannot prepare subquery to pass ordering member later.
There's no need to pass it later. Your current way of declaring the subquery is fine as it is, since SQLAlchemy can automatically correlate FROM objects to those of an enclosing query. I tried creating models that somewhat represent what you have, and here's how the query above works out (with added line-breaks and indentation for readability):
In [10]: print(query)
SELECT sale.agent_id AS sale_agent_id,
sale.property_id AS sale_property_id,
property.address_zip AS property_address_zip,
(SELECT property_valuations.valuation
FROM property_valuations
WHERE property_valuations.zip_code = property.address_zip
ORDER BY abs(datediff(property_valuations.as_of, sale.date_sold))
LIMIT ? OFFSET ?) AS back_valuation
FROM sale
JOIN property ON property.id = sale.property_id

Bulk move rows from one table to another with SQLAlchemy

I have two identical tables post and old_post. I have a query that checks for old posts. I would like to move the rows returned by the query into the table old_post and delete the rows from table post.
I could solve this by iterating through the results returned by the initial query and update my results this way, however I am worried this is very inefficient and will start to cause me problems when I have 1,000+ rows. How can I efficiently "bulk move" rows from one table to another?

Query for old Posts. Bulk insert OldPosts with the old Posts' data. Bulk delete the old Posts.
keys = db.inspect(Post).columns.keys()
get_columns = lambda post: {key: getattr(post, key) for key in keys}
posts = Post.query.filter(Post.expiry > ts)
db.session.bulk_insert_mappings(OldPost, (get_columns(post) for post in posts))
posts.delete()
db.session.commit()
The get_columns function takes a Post instance and creates a dictionary out of the column keys and values. Read the docs and warnings about using bulk insert and delete operations.

You can use Common Table Expressions in PostgreSQL
WITH moved_posts AS (
DELETE FROM post
WHERE expiry > time_stamp
RETURNING *
)
INSERT INTO old_post
SELECT * from moved_posts
CTE support for DELETE will be added in SQLAlchemy 1.1. In current release you can execute raw SQL
from sqlalchemy import text
sql = text('''
WITH moved_posts AS (
DELETE FROM post
WHERE expiry > ?
RETURNING *
)
INSERT INTO old_post
SELECT * from moved_posts
''')
db.session.execute(sql, [time_stamp])
db.session.commit()
In SQLAlchemy 1.1 it would look like this
posts = Post.__table__
old_posts = OldPost.__table__
moved_posts = (
posts.delete()
.where(posts.c.expiry > ts)
.returning(*(posts.c._all_columns))
.cte('moved_posts'))
insert = (
old_posts.insert()
.from_select(
[c.name for c in moved_posts.columns],
moved_posts.select()
))
db.session.execute(insert)
db.session.commit()

How to count rows with SELECT COUNT(*) with SQLAlchemy?

I'd like to know if it's possible to generate a SELECT COUNT(*) FROM TABLE statement in SQLAlchemy without explicitly asking for it with execute().
If I use:
session.query(table).count()
then it generates something like:
SELECT count(*) AS count_1 FROM
(SELECT table.col1 as col1, table.col2 as col2, ... from table)
which is significantly slower in MySQL with InnoDB. I am looking for a solution that doesn't require the table to have a known primary key, as suggested in Get the number of rows in table using SQLAlchemy.

Query for just a single known column:
session.query(MyTable.col1).count()

I managed to render the following SELECT with SQLAlchemy on both layers.
SELECT count(*) AS count_1
FROM "table"
Usage from the SQL Expression layer
from sqlalchemy import select, func, Integer, Table, Column, MetaData
metadata = MetaData()
table = Table("table", metadata,
Column('primary_key', Integer),
Column('other_column', Integer) # just to illustrate
)
print select([func.count()]).select_from(table)
Usage from the ORM layer
You just subclass Query (you have probably anyway) and provide a specialized count() method, like this one.
from sqlalchemy.sql.expression import func
class BaseQuery(Query):
def count_star(self):
count_query = (self.statement.with_only_columns([func.count()])
.order_by(None))
return self.session.execute(count_query).scalar()
Please note that order_by(None) resets the ordering of the query, which is irrelevant to the counting.
Using this method you can have a count(*) on any ORM Query, that will honor all the filter andjoin conditions already specified.

I needed to do a count of a very complex query with many joins. I was using the joins as filters, so I only wanted to know the count of the actual objects. count() was insufficient, but I found the answer in the docs here:
http://docs.sqlalchemy.org/en/latest/orm/tutorial.html
The code would look something like this (to count user objects):
from sqlalchemy import func
session.query(func.count(User.id)).scalar()

Addition to the Usage from the ORM layer in the accepted answer: count(*) can be done for ORM using the query.with_entities(func.count()), like this:
session.query(MyModel).with_entities(func.count()).scalar()
It can also be used in more complex cases, when we have joins and filters - the important thing here is to place with_entities after joins, otherwise SQLAlchemy could raise the Don't know how to join error.
For example:
we have User model (id, name) and Song model (id, title, genre)
we have user-song data - the UserSong model (user_id, song_id, is_liked) where user_id + song_id is a primary key)
We want to get a number of user's liked rock songs:
SELECT count(*)
FROM user_song
JOIN song ON user_song.song_id = song.id
WHERE user_song.user_id = %(user_id)
AND user_song.is_liked IS 1
AND song.genre = 'rock'
This query can be generated in a following way:
user_id = 1
query = session.query(UserSong)
query = query.join(Song, Song.id == UserSong.song_id)
query = query.filter(
and_(
UserSong.user_id == user_id,
UserSong.is_liked.is_(True),
Song.genre == 'rock'
)
)
# Note: important to place `with_entities` after the join
query = query.with_entities(func.count())
liked_count = query.scalar()
Complete example is here.

If you are using the SQL Expression Style approach there is another way to construct the count statement if you already have your table object.
Preparations to get the table object. There are also different ways.
import sqlalchemy
database_engine = sqlalchemy.create_engine("connection string")
# Populate existing database via reflection into sqlalchemy objects
database_metadata = sqlalchemy.MetaData()
database_metadata.reflect(bind=database_engine)
table_object = database_metadata.tables.get("table_name") # This is just for illustration how to get the table_object
Issuing the count query on the table_object
query = table_object.count()
# This will produce something like, where id is a primary key column in "table_name" automatically selected by sqlalchemy
# 'SELECT count(table_name.id) AS tbl_row_count FROM table_name'
count_result = database_engine.scalar(query)

I'm not clear on what you mean by "without explicitly asking for it with execute()" So this might be exactly what you are not asking for.
OTOH, this might help others.
You can just run the textual SQL:
your_query="""
SELECT count(*) from table
"""
the_count = session.execute(text(your_query)).scalar()

def test_query(val: str):
query = f"select count(*) from table where col1='{val}'"
rtn = database_engine.query(query)
cnt = rtn.one().count
but you can find the way if you checked debug watch

query = session.query(table.column).filter().with_entities(func.count(table.column.distinct()))
count = query.scalar()
this worked for me.
Gives the query:
SELECT count(DISTINCT table.column) AS count_1
FROM table where ...

Below is the way to find the count of any query.
aliased_query = alias(query)
db.session.query(func.count('*')).select_from(aliased_query).scalar()
Here is the link to the reference document if you want to explore more options or read details.