Use pandasSQL transactions in sql test suite to avoid engine deadlocks
When trying to integrate the engine fixtures into these tests I have been running into a lot of deadlocking issues. From some [research](https://github.com/sqlalchemy/sqlalchemy/issues/5405#issuecomment-646607306) it looks like SQLAlchemy strongly discourages running doing [Connectionless Execution](https://docs.sqlalchemy.org/en/13/core/connections.html#connectionless-execution-implicit-execution) 

Note the comment:

> Modern SQLAlchemy usage, especially the ORM, places a heavy stress on working within the context of a transaction at all times; the “implicit execution” concept makes the job of associating statement execution with a particular transaction much more difficult.

We probably need an overhaul of the sql module to more natively account for this, but I think it makes sense to unlock our test suite first so that getting better coverage via fixtures in https://github.com/pandas-dev/pandas/pull/55074 would help us more confidently refactor

Here's an MRE to reproduce this deadlock locally:

```python
import sqlalchemy as sa

from pandas.io.sql import pandasSQL_builder

engine = sa.create_engine("mysql+pymysql://root@localhost:3306/pandas")

pandasSQL = pandasSQL_builder(engine)
with pandasSQL.run_transaction() as trans:
    stmt = sa.text("CREATE TABLE test_trans (A INT, B TEXT)")
    trans.execute(stmt)

with pandasSQL.run_transaction() as trans:
    stmt = sa.text("INSERT INTO test_trans (A,B) VALUES (1, 'blah')")
    trans.execute(stmt)

result = pandasSQL.read_query("SELECT * FROM test_trans")

# Assume fixture tries to clean up all tables after function exit
with engine.begin() as conn:
    stmt = sa.text("DROP TABLE test_trans")
    conn.execute(stmt)
```

If you wrap the read_query call in a transaction there is no deadlock

(tip: if you ran the above locally you will probably want to kill the thread so it doesn't lock up your database. run `show engine innodb status;` inside the db, look for the hanging thread id and run `KILL <thread_id>`)

Thanks @WillAyd 