Metadata-Version: 1.1
Name: pynoorm
Version: 1.0.0
Summary: Use Python with or without an ORM.
Home-page: https://github.com/jpeyret/pynoorm
Author: JL Peyret
Author-email: jpeyret@gmail.com
License: MIT License
Description: Use Python with or without an ORM.
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        PyNoORM consists of several very loosely-coupled classes that facilitate the use of Python in a web or SQL
        context without having to rely on an ORM.  Working with an ORM is entirely possible, in fact, it's used with
        the Django ORM and SQLAlchemy in an application that interfaces with Oracle, Microsoft SQL Server and PostgreSQL all at the same time.
        
        Focus is on:
        
         - simplicity for the user
         - support for databases that are not under "controlled" by the Python application or may be read-only for it.
         - performance
        
        +------------------------+-----------------------------------------------------------------------+
        | Class                  | Role                                                                  |
        +========================+=======================================================================+
        | Binder                 | abstract SQL query binding                                            |
        +------------------------+-----------------------------------------------------------------------+
        | Linker                 | join objects together                                                 |
        +------------------------+-----------------------------------------------------------------------+
        | TemplateGenerator      | generate Django Templates dynamically from query results, loosely     |
        | *(to be added)*        | inspired by Django Tables 2                                           |
        +------------------------+-----------------------------------------------------------------------+
        
        
        The Binder class
        ================
        
        A Binder support easier raw SQL by abstracting differences in the underlying database's bind variable syntax and also substituting bind variables from a list of arguments, using dict, then attribute lookup.
        
        Using native database binds also helps to protect you against SQL injection attacks.
        
        supported:  PostgreSQL, sqlite3, Oracle, MySQL, SQL Server
        
        Basic Use
        ---------
        
        Simple **sqlite3** example::
        
            from pynoorm.binder import Binder
            binder = Binder.factory("qmark")
        
            query, parameters = binder("select * from orders where custid = %(custid)s", dict(custid="ACME"), binder)
        
        ``query`` and ``parameters`` are now in the sqlite3/qmark format::
        
        	>>> print(query)
        	select * from orders where custid = ?
        	>>> print(parameters)
        	('ACME',)
        
        Oracle, with multiple parameters ::
        
            import cx_Oracle
            binder_ora = Binder.factory(cx_Oracle.paramstyle)
        
            #just for test... assign a custid for attribute lookup
            binder_ora.custid = "AMAZON"
        
            tqry = "select * from orders where custid = %(custid)s and has_shipped = %(shipped)s"
            query, parameters = binder_ora(tqry, binder_ora, dict(custid="ACME", shipped=1))
        
            >>> print(query)
            select * from orders where custid = :custid and has_shipped = :shipped
            >>> print(parameters)
            {'shipped': 1, 'custid': 'AMAZON'}
        
        SQL IN list criteria:
        
        This allows binding of Python lists as standard SQL ``in ('foo','bar')`` expressions, but as a prepared statement.
        
        It relies on using `'l'`, rather than `'s'` as the format qualifier.  Notice the `%(custid)l` below ::
        
            from pynoorm.binder import Binder
            binder = Binder.factory("qmark")
        
            query, parameters = binder(
                "select * from orders where custid in (%(custid)l)"
                , dict(custid=["ACME","FOO","BAR"])
                )
        
        
        Contents of `query` and `parameters`::
            
            select * from orders where custid in (?, ?, ?)
            ('ACME', 'FOO', 'BAR')
            
        
        And now with an empty list::
        
            query, parameters = binder(
                """select * 
                from orders 
                where custid in (%(custid)l) 
                and status=%(status)s"""
                , dict(custid=[], status="any")
                )
        
        Contents of `query` and `parameters`::
        
        
            select * from orders where custid in (NULL) and status=?
            ('any',)
        
        
        
        Features
        --------
        
        * adjust query to support database parameter style
        * find and prepare bind parameters from `*args`.
        
        
        
        The Linker class
        ================
        
        A Linker allows you to join objects or dictionaries without the need for an ORM.  You can think of it as performing `parent-child` linking, but it uses `left-right` instead as a more neutral terminology instead.
        
        Basic use 
        ---------
        
        Sample data, in dictionaries: ::
        
            customers = [
                dict(id=1, xref=1),
                dict(id=2, xref=2),
            ]
        
            orders = [
                dict(custid=1, xref=1, orderid=11),
                dict(custid=1, xref=1, orderid=12),
                dict(custid=2, xref=2, orderid=21),
                dict(custid=2, xref=2, orderid=22),
            ]
        
        Create a linker, then a lookup dictionary for the left side.  Finally, link the left and right side. ::
        
            linker = Linker(key_left="id")
            lookup = linker.dict_from_list(customers)
            linker.link(lookup, orders, attrname_on_left="orders", key_right="custid")
        
        
        The customers now have an `orders` list:  ::
        
            [ { 'id': 1,
                'orders': [ { 'custid': 1, 'orderid': 11, 'xref': 1},
                            { 'custid': 1, 'orderid': 12, 'xref': 1}],
                'xref': 1},
              { 'id': 2,
                'orders': [ { 'custid': 2, 'orderid': 21, 'xref': 2},
                            { 'custid': 2, 'orderid': 22, 'xref': 2}],
                'xref': 2}]
        
        Features
        --------
            
            * supports objects or dictionaries
            * takes basic Python objects so can join across different databases, allowing for example tagging of objects in a read-only database
            * allows compound field keys and aliasing
            * orphans, on the left or the right, can be initialized with empty attribute values.
        
        
        Note on Python 3.7 support:
        ---------------------------
        
        3.7 tests run to success locally, but travis-ci does not support Python 3.7 yet.  So expect `builds` to show
        "failing" 3.7, pending resolution of Travisissue485_.
        
        .. _Travisissue485: https://github.com/jopohl/urh/pull/485
        
        
        Credits
        ---------
        
        This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
        
        =======
        History
        =======
        
        0.1.0 (2016-02-17)
        ------------------
        
        * First release on github.
        
        0.1.1 (2016-02-22)
        ------------------
        
        * Registered on PyPI
        
        0.2.0 (2016-04-12)
        ------------------
        
        * Added support for Python 3.3+ and MySQL
        
        0.3.0 (2017-09-06)
        ------------------
        
        * Added SQL Server support
        * Added Linker class to support object cross-referencing
        
        0.4.0 (2018-07-24)
        ------------------
        
        * Updating to Beta status
        * Optimized Linker class
        * Python list => SQL IN (xxx, yyy) functionality on Binder.
        
        0.4.1 (2018-08-07)
        ------------------
        
        * adjusted for Python 3 
        
        0.4.2 (2019-01-10)
        ------------------
        
        * ran Black for code formatting
        * updated PyYaml to 4.2b4 to fix security vulnerability
        
        
        0.4.3 (2019-01-10)
        ------------------
        
        * removed Python 3.7 from tox since that Python version is not supported yet by tox.
        
        
        0.4.4 (2019-01-15)
        ------------------
        
        * adjusted list binding variable names from `__xxx_000` to `xxx_000__` because leading underscore are invalid under Oracle.
          
        0.1.0 (2019-07-15)
        ------------------
        
        * added the D3.js Tree Linker example.
        * Code is stable and hasn't had fixes or API changes.
        
        
Keywords: sql database multiplatform
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Database :: Front-Ends
Classifier: Topic :: Utilities
Classifier: Operating System :: OS Independent
