Cone Search Alchemy

The conesearch_alchemy Python package enhances SQLAlchemy to provide fast, indexed cone searches on astronomical catalogs using a PostgreSQL database. It does not rely on any database extensions.

Installation

You can install conesearch_alchemy the Python Package Index:

$ pip install conesearch-alchemy

Usage

from conesearch_alchemy.point import Point
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()


# Create two tables Catalog1 and Catalog2 that both have spherical coordinates.


class Catalog1(Point, Base):
    __tablename__ = "catalog1"
    id = Column(Integer, primary_key=True)


class Catalog2(Point, Base):
    __tablename__ = "catalog2"
    id = Column(Integer, primary_key=True)


...

# Populate Catalog1 and Catalog2 tables with some sample data...
session.add(Catalog1(id=0, ra=320.5, dec=-23.5))
...
session.add(Catalog2(id=0, ra=18.1, dec=18.3))
...
session.commit()


# Cross-match the two tables.
separation = 1  # separation in degrees
query = (
    session.query(Catalog1.id, Catalog2.id)
    .join(Catalog2, Catalog1.within(point, separation))
    .order_by(Catalog1.id, Catalog2.id)
)
for row in query:
    ...  # do something with the query results


# Do a cone search around literal ra, dec values.
separation = 1  # separation in degrees
point = Point(ra=212.5, dec=-33.2)
query = (
    session.query(Catalog1.id)
    .filter(Catalog1.within(point, separation))
    .order_by(Catalog1.id)
)
for row in query:
    ...  # do something with the query results