Package: jsonquery
jsonqueryBasic json -> sqlalchemy query builderInstallationpip install jsonqueryBasic UsageLet’s define a model and get an engine set up:from sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String)
    email = Column(String)
    age = Column(Integer)
    height = Column(Integer)
engine = create_engine("sqlite://", echo=True)
Base.metadata.create_all(engine)
model = User
session = sessionmaker(bind=engine)()We want to get all users whose name starts with ‘Pat’ and are
at least 21:from jsonquery import jsonquery

json = {
    "operator": "and",
    "value": [
        {
            "operator": ">=",
            "column": "age",
            "value": 21
        },
        {
            "operator": "ilike",
            "column": "name",
            "value": "pat%"
        }
    ]
}

query = jsonquery(session, User, json)
users = query.all()Supported Data Typesjsonquery doesn’t care about column type.  Instead, it uses a whitelist of operators,
where keys are strings (the same that would be passed in the “operator” field of a node)
and the values are functions that take a column object and a value and return a
sqlalchemy criterion.  Here are some examples:def greater_than(column, value):
    return column > value
register_operator(">", greater_than)

def like(column, value):
    like_func = getattr(column, 'like')
    return like_func(value)
register_operator("like", like)By default, the following are registered:>, >=, ==, !=, <=, <
like, ilike, in_Useunregister_operator(opstring)to remove an operator.Future GoalsThere are a few features I want to add, but these are mostly convenience and aren’t necessary to
the core application, which I believe is satisfied.Compressed and/or formatReduce repetitive column and operator specification when possible by allowing non-scalar values
for column operators.  By flipping the nesting restriction on logical operators, we can omit
fields specified at the column level.  This is especially prominent in string matching,
when the column and operator are the same, but we want to compare against 3+ values.Currently:{
    "operator": "or",
    "value": [
        {
            "column": "age",
            "operator": "<=",
            "value": 16
        },
        {
            "column": "age",
            "operator": ">=",
            "value": 21
        },
        {
            "column": "age",
            "operator": "==",
            "value": 18
        }
    ]
}With compressed logical operators:{
    "column": "age"
    "value": {
        "operator": "or",
        "value": [
            {
                "operator": "<=",
                "value": 16
            },
            {
                "operator": ">=",
                "value": 21
            },
            {
                "operator": "==",
                "value": 18
            }
        ]
    }
}Or, when the operator is the same:{
    "column": "name"
    "operator": "like"
    "value": {
        "operator": "or",
        "value": [
            "Bill",
            "Mary",
            "Steve"
        ]
    }
}Contributorsduesenfranz- Python 3 compatibilitysvisser- Python 3 compatibility1.0.0First public release