Metadata-Version: 1.1
Name: mlalchemy
Version: 0.2.0
Summary: Library for converting YAML/JSON to SQLAlchemy SELECT queries
Home-page: https://github.com/thanethomson/MLAlchemy
Author: Thane Thomson
Author-email: connect@thanethomson.com
License: MIT
Description: MLAlchemy
        =========
        
        Overview
        --------
        
        MLAlchemy is a Python-based utility library aimed at allowing relatively
        safe conversion from YAML/JSON to SQLAlchemy read-only queries. One use
        case here is to allow RESTful web applications (written in Python) to
        receive YAML- or JSON-based queries for data, e.g. from a front-end
        JavaScript-based application.
        
        The name "MLAlchemy" is an abbreviation for "Markup Language for
        SQLAlchemy".
        
        Installation
        ------------
        
        Installation via PyPI:
        
        .. code:: bash
        
            > pip install mlalchemy
        
        Query Examples
        --------------
        
        To get a feel for what MLAlchemy queries look like, take a look at the
        following. **Note**: All field names are converted from ``camelCase`` or
        ``kebab-case`` to ``snake_case`` prior to query execution.
        
        Example YAML Queries
        ~~~~~~~~~~~~~~~~~~~~
        
        Fetching all the entries from a table called ``Users``:
        
        .. code:: yaml
        
            from: Users
        
        Limiting the users to only those with the last name "Michaels":
        
        .. code:: yaml
        
            from: Users
            where:
              last-name: Michaels
        
        A more complex YAML query:
        
        .. code:: yaml
        
            from: Users
            where:
              $or:
                last-name: Michaels
                first-name: Michael
              $gt:
                date-of-birth: 1984-01-01
        
        The raw SQL query for the above would look like:
        
        .. code:: sql
        
            SELECT * FROM users WHERE \
              (last_name = "Michaels" OR first_name = "Michael") AND \
              (date_of_birth > "1984-01-01")
        
        Example JSON Queries
        ~~~~~~~~~~~~~~~~~~~~
        
        The same queries as above, but in JSON format. To fetch all entries in
        the ``Users`` table:
        
        .. code:: json
        
            {
                "from": "Users"
            }
        
        Limiting the users to only those with the last name "Michaels":
        
        .. code:: json
        
            {
                "from": "Users",
                "where": {
                    "lastName": "Michaels"
                }
            }
        
        And finally, the more complex query:
        
        .. code:: json
        
            {
                "from": "Users",
                "where": {
                    "$or": {
                        "lastName": "Michaels",
                        "firstName": "Michael"
                    },
                    "$gt": {
                        "dateOfBirth": "1984-01-01"
                    }
                }
            }
        
        Usage
        -----
        
        A simple example of how to use MLAlchemy:
        
        .. code:: python
        
            from sqlalchemy import create_engine, Column, Integer, String, Date
            from sqlalchemy.ext.declarative import declarative_base
            from sqlalchemy.orm import sessionmaker
        
            from mlalchemy import parse_yaml_query, parse_json_query
        
            Base = declarative_base()
        
        
            class User(Base):
                __tablename__ = "users"
        
                id = Column(Integer, primary_key=True)
                first_name = Column(String)
                last_name = Column(String)
                date_of_birth = Column(Date)
        
        
            # use an in-memory SQLite database for this example
            engine = create_engine("sqlite:///:memory:")
            Base.metadata.create_all(engine)
            Session = sessionmaker(bind=engine)
            session = Session()
        
            # add a couple of dummy users
            user1 = User(first_name="Michael", last_name="Anderson", date_of_birth=date(1980, 1, 1))
            user2 = User(first_name="James", last_name="Michaels", date_of_birth=date(1976, 10, 23))
            user3 = User(first_name="Andrew", last_name="Michaels", date_of_birth=date(1988, 8, 12))
            session.add_all([user1, user2, user3])
            session.commit()
        
            # we need a lookup table for MLAlchemy
            tables = {
                "User": User
            }
        
            # try a simple YAML-based query first
            all_users = parse_yaml_query("from: User").to_sqlalchemy(session, tables).all()
            print(all_users)
        
            # same query, but this time in JSON
            all_users = parse_json_query("""{"from": "User"}""").to_sqlalchemy(session, tables).all()
            print(all_users)
        
            # a slightly more complex query
            young_users = parse_yaml_query("""from: User
            where:
                $gt:
                    date-of-birth: 1988-01-01
            """).to_sqlalchemy(session, tables).all()
            print(young_users)
        
        Query Language Syntax
        ---------------------
        
        As mentioned before, queries can either be supplied in YAML format or in
        JSON format to one of the respective parsers.
        
        ``from``
        ^^^^^^^^
        
        At present, MLAlchemy can only support selecting data from a single
        table (multi-table support is planned in future). Here, the ``from``
        parameter allows you to specify the name of the table from which to
        select data.
        
        ``where``
        ^^^^^^^^^
        
        The ``where`` parameter defines, in hierarchical fashion, the structure
        of the logical query to perform. There are 3 kinds of key types in the
        JSON/YAML structures, as described in the following table.
        
        +-----------------+----------------------------+---------------------------------------+
        | Kind            | Description                | Options                               |
        +=================+============================+=======================================+
        | **Operators**   | Logical (boolean)          | ``$and``, ``$or``, ``$not``           |
        |                 | operators for combining    |                                       |
        |                 | sub-clauses                |                                       |
        +-----------------+----------------------------+---------------------------------------+
        | **Comparators** | Comparative operators for  | ``$eq``, ``$gt``, ``$gte``, ``$lt``,  |
        |                 | comparing fields to values | ``$lte``, ``$like``, ``$neq``,        |
        |                 |                            | ``$in``, ``$nin``, ``$is``            |
        +-----------------+----------------------------+---------------------------------------+
        | **Field Names** | The name of a field in the | (Depends on table)                    |
        |                 | ``from`` table             |                                       |
        +-----------------+----------------------------+---------------------------------------+
        
        ``order-by`` (YAML) or ``orderBy`` (JSON)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        Provides the ordering for the resulting query. Must either be a single
        field name or a list of field names, with the direction specifier in
        front of the field name. For example:
        
        .. code:: yaml
        
            # Order by "field2" in ascending order
            order-by: field2
        
        Another example:
        
        .. code:: yaml
        
            # Order by "field2" in *descending* order
            order-by: "-field2"
        
        A more complex example:
        
        .. code:: yaml
        
            # Order first by "field1" in ascending order, then by "field2" in
            # descending order
            order-by:
                - field1
                - "-field2"
        
        ``offset``
        ^^^^^^^^^^
        
        Specifies the number of results to skip before providing results. If not
        specified, no results are skipped.
        
        ``limit``
        ^^^^^^^^^
        
        Specifies the maximum number of results to return. If not specified,
        there will be no limit to the number of returned results.
        
        Query Examples
        --------------
        
        Example 1: Simple Query
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        The following is an example of a relatively simple query in YAML format:
        
        .. code:: yaml
        
            from: SomeTable
            where:
                - $gt:
                    field1: 5
                - $lt:
                    field2: 3
            order-by:
                - field1
            offset: 2
            limit: 10
        
        This would translate into the following SQLAlchemy query:
        
        .. code:: python
        
            from sqlalchemy.sql.expression import and_
        
            session.query(SomeTable).filter(
                and_(SomeTable.field1 > 5, SomeTable.field2 < 3)
            ) \
                .order_by(SomeTable.field1) \
                .offset(2) \
                .limit(10)
        
        Example 2: Slightly More Complex Query
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        The following is an example of a more complex query in YAML format:
        
        .. code:: yaml
        
            from: SomeTable
            where:
                - $or:
                    field1: 5
                    field2: something
                - $not:
                    $like:
                        field3: "else%"
        
        This would translate into the following SQLAlchemy query:
        
        .. code:: python
        
            from sqlalchemy.sql.expression import and_, or_, not_
        
            session.query(SomeTable) \
                .filter(
                    and_(
                        or_(
                            SomeTable.field1 == 5,
                            SomeTable.field2 == "something"
                        ),
                        not_(
                            SomeTable.field3.like("else%")
                        )
                    )
                )
        
        Example 3: Complex JSON Query
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        The following is an example of a relatively complex query in JSON
        format:
        
        .. code:: json
        
            {
                "from": "SomeTable",
                "where": [
                    {
                        "$or": [
                            {"field1": 10},
                            {
                                "$gt": {
                                    "field2": 5
                                }
                            }
                        ],
                        "$and": [
                            {"field3": "somevalue"},
                            {"field4": "othervalue"},
                            {
                                "$or": {
                                    "field5": 5,
                                    "field6": 6
                                }
                            }
                        ]
                    }
                ],
                "orderBy": [
                    "field1",
                    "-field2
                ],
                "offset": 2,
                "limit": 10
            }
        
        This query would be translated into the following SQLAlchemy code:
        
        .. code:: python
        
            from sqlalchemy.sql.expression import and_, or_, not_
        
            session.query(SomeTable) \
                .filter(
                    and_(
                        or_(
                            SomeTable.field1 == 10,
                            SomeTable.field2 > 5
                        ),
                        and_(
                            SomeTable.field3 == "somevalue",
                            SomeTable.field4 == "othervalue",
                            or_(
                                SomeTable.field5 == 5,
                                SomeTable.field6 == 6
                            )
                        )
                    )
                ) \
                .order_by(SomeTable.field1, SomeTable.field2.desc()) \
                .offset(2) \
                .limit(10)
        
        License
        -------
        
        **The MIT License (MIT)**
        
        Copyright (c) 2017 Thane Thomson
        
        Permission is hereby granted, free of charge, to any person obtaining a
        copy of this software and associated documentation files (the
        "Software"), to deal in the Software without restriction, including
        without limitation the rights to use, copy, modify, merge, publish,
        distribute, sublicense, and/or sell copies of the Software, and to
        permit persons to whom the Software is furnished to do so, subject to
        the following conditions:
        
        The above copyright notice and this permission notice shall be included
        in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
        OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
        MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
        IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
        CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
        TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
        SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Database
Classifier: Topic :: Utilities
Classifier: Topic :: Software Development :: Libraries
