How to join 2 tables from different queries in SQLAlchemy - python

I have 2 queries which both get a subset of a tables, let's call them Table1 and Table2
I would like to join these 2 child tables on their id.
I tried something like this, but it throws unhelpful errors:
table1: List[Table1] = db.session.execute(query1)
table2: List[Table2] = db.session.execute(query2)
db.session.query(table1).join(table2, table1.id == table2.id).all()

You have to join the tables before executing the query.
Maybe you wanted to do like this?
results = db.session.query(Table1).filter(
{whatever the query1 does},
{whatever the query2 does}
).join(Table2, Table1.id==Table2.id)

Related

How to iteratively create UNION ALL SQL statement using Python?

I am connecting to Snowflake to query row count data of view table from Snowflake. I am also querying metadata related to View table. My Query looks like below. I was wondering if I can iterate through UNION ALL statement using python ? When I try to run my below query I received an error that says "view_table_3" does not exist.
Thanks in advance for your time and efforts!
Query to get row count for Snowflake view table (with metadata)
view_tables=['view_table1','view_table2','view_table3','view_table4']
print(f""" SELECT * FROM (SELECT TABLE_SCHEMA,TABLE_NAME,CREATED,LAST_ALTERED FROM SCHEMA='INFORMATION_SCHEMA.VIEWS' WHERE TABLE_SCHEMA='MY_SCHEMA' AND TABLE_NAME IN ({','.join("'" +x+ "'" for x in view_tables)})) t1
LEFT JOIN
(SELECT 'view_table1' table_name2, count(*) as view_row_count from MY_DB.SCHEMA.view_table1
UNION ALL SELECT {','.join("'" +x+ "'" for x in view_tables[1:])},count(*) as view_row_count from MY_DB.SCHEMA.{','.join("" +x+ "" for x.replace("'"," ") in view_tables)})t2
on t1.TABLE_NAME =t2.table_name2 """)
If you want to make a union dynamically, put the entire SELECT query inside the generator, and then join them with ' UNION '.
sql = f'''SELECT * FROM INFORMATION_SCHEMA.VIEWS AS v
LEFT JOIN (
{' UNION '.join(f"SELECT '{table}' AS table_name2, COUNT(*) AS view_row_count FROM MY_SCHEMA.{table}" for table in view_tables)}
) AS t2 ON v.TABLE_NAME = t2.table_name2
WHERE v.TABLE_NAME IN ({','.join(f"'{table}'" for table in view_tables)})
'''
print(sql);

How to select the distinct values of three sql tables and perform inner join with python sqlite3?

I'm trying to perform an inner join of distinct values of three tables from an SQLite DB. I tried multiple times and failed. Please guide me.
Below is a pseudo-code of what I'm trying to achieve
sql = '''
SELECT DISTINCT lesson_id, question_id FROM lesson_practice_questions as lpq
INNER JOIN
SELECT DISTINCT topic_id, lesson_id FROM chapter_lessons as cl
WHERE cl.topic_id==2
ON cl.lesson_id = lpq.lesson_id
INNER JOIN
SELECT DISTINCT question_id, subject_id, question_type_id, knowledge_type_ids complexity_level FROM questions as q
ON q.question_id = lpq.question_id;'''
cur.execute(sql)
Many Thanks to #eshirvana for taking the time to help out!.
Perfect Solution with ambiguous error resolution for future stackoverflow reference:
sql = '''SELECT
lpq.lesson_id, cl.lesson_id,
topic_id,
q.question_id, lpq.question_id,
subject_id,
question_type_id,
knowledge_type_ids,
complexity
FROM lesson_practice_questions as lpq
INNER JOIN chapter_lessons as cl on cl.topic_id = 2 and cl.lesson_id = lpq.lesson_id
INNER JOIN questions as q ON q.question_id = lpq.question_id;'''
here is the right sql syntax , however you need to provide sample data and desired output if this is not the right output :
SELECT
lpq.lesson_id,
question_id,
topic_id,
lesson_id,
question_id,
subject_id,
question_type_id,
knowledge_type_ids,
complexity_level
FROM lesson_practice_questions as lpq
INNER JOIN chapter_lessons as cl on cl.topic_id = 2 and cl.lesson_id = lpq.lesson_id
INNER JOIN questions as q ON q.question_id = lpq.question_id;

Confusing SQLAlchemy conversion of simple subquery

I've been wrestling with what should be a simple conversion of a straightforward SQL query into an SQLAlchemy expression, and I just cannot get things to line up the way I mean in the subquery. This is a single-table query of a "Comments" table; I want to find which users have made the most first comments:
SELECT user_id, count(*) AS count
FROM comments c
where c.date = (SELECT MIN(c2.date)
FROM comments c2
WHERE c2.post_id = c.post_id
)
GROUP BY user_id
ORDER BY count DESC
LIMIT 20;
I don't know how to write the subquery so that it refers to the outer query, and if I did, I wouldn't know how to assemble this into the outer query itself. (Using MySQL, which shouldn't matter.)
Well, after giving up for a while and then looking back at it, I came up with something that works. I'm sure there's a better way, but:
c2 = aliased(Comment)
firstdate = select([func.min(c2.date)]).\
where(c2.post_id == Comment.post_id).\
as_scalar() # or scalar_subquery(), in SQLA 1.4
users = session.query(
Comment.user_id, func.count('*').label('count')).\
filter(Comment.date == firstdate).\
group_by(Comment.user_id).\
order_by(desc('count')).\
limit(20)

SQLAlchemy raw SQL Query NoSuchColumnError

I have a relatively complex sql statement that I want to execute with sqlalchemy ORM. But when I try to do so I always get the error {NoSuchColumnError}"Could not locate column in row for column 'transaction_out.value'". My sql statement looks as follows:
sql = """
Select
addresses.address,
transaction_out1.value As sent,
transaction_out1.transaction_id As sent_id,
transactions.block As block_sent,
transactions.time As time_sent,
transactions.txid As txid_sent,
"sent" as type
From
transaction_out INNER Join
transaction_out_address On transaction_out_address.transaction_out_id = transaction_out.id INNER Join
addresses On transaction_out_address.address_id = addresses.id INNER Join
transaction_in On transaction_in.transaction_out_id = transaction_out.id INNER Join
transactions On transaction_in.transaction_id = transactions.id INNER Join
transaction_out transaction_out1 On transaction_out1.transaction_id = transactions.id INNER Join
transactions transactions1 On transaction_out.transaction_id = transactions1.id
WHERE addresses.address=:address_string
UNION
Select
addresses.address,
transaction_out.value As received,
transaction_out.transaction_id As received_id,
transactions.block As received_block,
transactions.time As received_time,
transactions.txid As received_txid,
"received"
From
transaction_out LEFT Join
transaction_out_address On transaction_out_address.transaction_out_id = transaction_out.id LEFT Join
addresses On transaction_out_address.address_id = addresses.id LEFT Join
transaction_in On transaction_in.transaction_out_id = transaction_out.id LEFT Join
transactions On transaction_out.transaction_id = transactions.id
WHERE addresses.address=:address_string
"""
And I tried to execute the statement in the following way:
query = session.query(Address.address, TransactionOut.value, TransactionOut.id, Block.height, Transaction.time, Transaction.txid).from_statement(
stmt.bindparams(
bindparam("address_string",
value=address_string)
))
I can execute the raw sql statement with engine.execute() without any problems but I need to do it with session.query() so I can use sqlalchemy-datatables. My database looks more or less like the one here: https://dba.stackexchange.com/questions/137791/blockchain-bitcoin-as-a-database/137800#137800.
What is the problem with the way I try to execute it?
The column aliases in the raw SQL are hiding the columns from the SQLAlchemy query. Either remove them, or alter the query to accommodate them:
query = session.query(Address.address,
TransactionOut.value.label('sent'),
TransactionOut.id.label('sent_id'),
Transaction.block.label('block_sent'),
Transaction.time.label('time_sent'),
Transaction.txid.label('txid_sent')).\
from_statement(stmt).\
params(address_string=address_string)

sqlalchemy: selecting columns referring to an aliased table name

I'm fairly new to using sqlalchemy and having some issues generating the sql code that I am looking for.
Ultimately, I'm trying to join two different subsets of table2 to table1 by using the following SQL query:
SELECT table1.date, a1.id AS name1_id, a2.id AS name2_id
FROM table1
LEFT JOIN table2 as a1
ON table1.name1 = table2.label AND table2.lookup_id = 1000
LEFT JOIN table2 as a2
ON table1.name2 = table2.label AND table2.lookup_id = 2000
Here's what I have so far using sqlalchemy:
q_generate = (
select([table1.c.date,
a1.id.label('name1_id'),
a2.id.label('name2_id')])
.select_from(table1
.outerjoin(table2.alias(name='a1'),
and_(
table2.c.lookup_id == 1000,
table1.c.name1 == table2.c.label
))
.outerjoin(table2.alias(name='a2'),
and_(
table2.c.lookup_id == 2000,
table1.c.name2== table2.c.label
))
)
)
which produces the following errors:
*NameError: name 'a1' is not defined*
Is there a special way that aliased table names must be referenced? What am I missing here? I think the error has something to do with these lines but I can't figure out how exactly to get this to work:
...
a1.id.label('name1_id'),
a2.id.label('name2_id')])
...
Thank you!
Yes, do this:
a1 = table2.alias(name='a1')
a2 = table2.alias(name='a2')
q_generate = (
select([table1.c.date,
a1.c.id.label('name1_id'),
a2.c.id.label('name2_id')])
.select_from(table1.outerjoin(a1, ...).outerjoin(a2, ...)))

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