In a little script I'm writing using SQLAlchemy and Elixir, I need to get all the distinct values for a particular column. In ordinary SQL it'd be a simple matter of
SELECT DISTINCT `column` F开发者_Python百科ROM `table`;
and I know I could just run that query "manually," but I'd rather stick to the SQLAlchemy declarative syntax (and/or Elixir) if I can. I'm sure it must be possible, I've even seen allusions to this sort of thing in the SQLAlchemy documentation, but I've been hunting through that documentation for hours (as well as that of Elixir) and I just can't seem to actually figure out how it would be done. So what am I missing?
You can query column properties of mapped classes and the Query class has a generative distinct()
method:
for value in Session.query(Table.column).distinct():
pass
For this class:
class Assurance(db.Model):
name = Column(String)
you can do this:
assurances = []
for assurance in Assurance.query.distinct(Assurance.name):
assurances.append(assurance.name)
and you will have the list of distinct values
I wanted to count the distinct values, and using .distinct()
and .count()
would count first, resulting in a single value, then do the distinct. I had to do the following
from sqlalchemy.sql import func
Session.query(func.count(func.distinct(Table.column))
For class,
class User(Base):
name = Column(Text)
id = Column(Integer, primary_key=True)
Method 1: Using load_only
from sqlalchemy.orm import load_only
records= (db_session.query(User).options(load_only(name)).distinct().all())
values = [record[0] if len(record) == 1 else record for record in records] # list of distinct values
Method2: without any imports
records = db_session.query(User.name).distinct().all()
l_values = [record.__dict__[l_columns[0]] for record in records]
for user in session.query(users_table).distinct():
print user.posting_id
SQL Alchemy version 2 encourages the use of the select()
function. You can use an SQL Alchemy table
to build a select statement that extracts unique values:
select(distinct(table.c.column_name))
SQL Alchemy 2.0 migration ORM usage:
"The biggest visible change in SQLAlchemy 2.0 is the use of Session.execute() in conjunction with select() to run ORM queries, instead of using Session.query()."
Reproducible example using pandas to collect the unique values.
Define and insert the iris dataset
Define an ORM structure for the iris dataset, then use pandas to insert the
data into an SQLite database. Pandas inserts with if_exists="append"
argument
so that it keeps the structure defined in SQL Alchemy.
import seaborn
import pandas
from sqlalchemy import create_engine
from sqlalchemy import MetaData, Table, Column, Text, Float
from sqlalchemy.orm import Session
Define metadata and create the table
engine = create_engine('sqlite://')
meta = MetaData()
meta.bind = engine
iris_table = Table('iris',
meta,
Column("sepal_length", Float),
Column("sepal_width", Float),
Column("petal_length", Float),
Column("petal_width", Float),
Column("species", Text))
iris_table.create()
Load data into the table
iris = seaborn.load_dataset("iris")
iris.to_sql(name="iris",
con=engine,
if_exists="append",
index=False,
chunksize=10 ** 6,
)
Select unique values
Re using the iris_table
from above.
from sqlalchemy import distinct, select
stmt = select(distinct(iris_table.c.species))
df = pandas.read_sql_query(stmt, engine)
df
# species
# 0 setosa
# 1 versicolor
# 2 virginica
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