使用浮点数时，SQLAlchemy filter_by查询失败

Question

I have a model defined as follows:

class EnergyProfiles(db.Model):
    __tablename__ = "energy_profiles"
    id = db.Column(db.Integer, primary_key=True)
    device_id = db.Column(db.String(64), index=True, unique=False, nullable=False)
    device_hardware = db.Column(db.String(64), index=True, unique=False, nullable=False)
    location = db.Column(db.String(64), index=True, unique=False, nullable=False)
    time = db.Column(db.String(64), index=True, unique=False, nullable=False)
    accompanied = db.Column(db.Boolean)
    wellbeing = db.Column(db.String(64), index=True, unique=False, nullable=False)
    battery = db.Column(db.Integer, index=True, unique=False, nullable=False)

When I add new objects via an API I would like to check that the new object (the post_data ) does not already exist. This check was easy with

energy_profile_existing = EnergyProfiles.query.filter_by(**post_data).first()

After changing the battery column type, however, from db.Integer to db.ARRAY(db.Float()) the previous query.filter_by fails with a postgres error (ignore the user text below, it's docker compose output logs)

 operator does not exist: double precision[] = numeric[]
user_1           | LINE 3: WHERE energy_profiles.battery = ARRAY[0.1,20.1]
user_1           |                                       ^
user_1           | HINT:  No operator matches the given name and argument types. You might need to add explicit type casts.

The post_data contains battery as part of the JSON object eg

{
    "device_id": "CP99",
    "device_hardware": "Pycom",
    "location": "irregular",
    "time": "daytime",
    "accompanied": false,
    "wellbeing": "ok",
    "battery": [0.11, 35.22]
}

Answer 1

As @benvc and @IljaEverilä pointed out when you pass an array without any explicit casting containing non-integer numeric constants, it is assumed that they are of type numeric .

What you can do is cast the array's contents to float and to do that you can use the array([]) literal to declare the array and cast() it to ARRAY(Float) using the datatype:

{
    "device_id": "CP99",
    "device_hardware": "Pycom",
    "location": "irregular",
    "time": "daytime",
    "accompanied": false,
    "wellbeing": "ok",
    "battery": cast(array([0.11, 35.22]), ARRAY(Float))
}