I want to print all the contents of a table using sqalchemy. I can't seem to figure out how inspect works.
I want to achieve something like that:
column1: value1, column2: value4
column1: value2, column2: value5
column1: value3, column2: value6
In a table that looks like this:
Table_1:
+---------+---------+
| column1 | column2 |
+---------+---------+
| value1 | value4 |
| value2 | value5 |
| value3 | value6 |
+---------+---------+
While I don't know how to do this with inspect
, I achieve the desire output through regular queries. For this example, I created a sqlite
table based on your example. First, we connect and reflect on this existing database.
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy import select
eng = create_engine("sqlite:///databases/example_table.db")
Base = automap_base()
Base.prepare(eng, reflect=True)
Table = Base.classes.example_table
To facilitate our query, we instantiate a session
,
Session = sessionmaker(bind=eng)
session = Session()
and perform the query, saving the outcome to result
.
stmt = select('*').select_from(Table)
result = session.execute(stmt).fetchall()
The elements of this query are instances of the sqlalchemy
RowProxy
class, which has a keys
method that can be used to access the column names. Consequently, we can transform the result
with a few short functions.
def result_dict(r):
return dict(zip(r.keys(), r))
def result_dicts(rs):
return list(map(result_dict, rs))
result_dicts(result)
which returns
[{'id': 1, 'column1': 'value1', 'column2': 'value4'},
{'id': 2, 'column1': 'value2', 'column2': 'value5'},
{'id': 3, 'column1': 'value3', 'column2': 'value6'}]
I don't know how useful this might be, but you can visualize the table in desperate times or you need a quick sneak peek at the table.
# create an engine using the following code and
# replace it with the path to your .db file.
from sqlalchemy import create_engine
engine = create_engine('sqlite:///employee.db', echo = False)
# Import pandas and connect the engine
# use the lowercase representation of your table name for table_name parameter
# For ex:
class Users(db.Model):
...
...
...
import pandas as pd
user_table = pd.read_sql_table(table_name="users", con=engine)
# This will load the table as dataframe and then you can display
I understand that in case the database is huge, visualizing it using pandas may not be the best idea but as I said above, desperate times !
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