Metadata-Version: 1.1
Name: cruddy
Version: 0.8.0
Summary: A CRUD wrapper class for Amazon DynamoDB
Home-page: https://github.com/cloudnative/cruddy
Author: Mitch Garnaat
Author-email: mitch@cloudnative.io
License: Apache License 2.0
Description: # cruddy
        
        [![Circle CI](https://circleci.com/gh/cloudnative/cruddy.svg?style=svg)](https://circleci.com/gh/cloudnative/cruddy)
        
        A simple CRUD wrapper around Amazon DynamoDB.
        
        ## Installation
        
        ```
        $ pip install cruddy
        ```
        
        ## Getting Started
        
        The first thing to do is to create a CRUD handler for your DynamoDB table.  The
        constructor for the CRUD class takes a number of parameters to help configure
        the handler for your application.  The full list of parameters are:
        
        * table_name - name of the backing DynamoDB table (required)
        * profile_name - name of the AWS credential profile to use when creating the
          boto3 Session
        * region_name - name of the AWS region to use when creating the boto3 Session
        * prototype - a dictionary that describes the prototypical object stored in
          your table (see below)
        * supported_ops - a list of operations supported by the CRUD handler
          (choices are list, get, create, update, delete, query)
        * encrypted_attributes - a list of tuples where the first item in the tuple is
          the name of the attribute that should be encrypted and the second
          item in the tuple is the KMS master key ID to use for
          encrypting/decrypting the value.
        * debug - if not False this will cause the raw_response to be left
          in the response dictionary
        
        ### Prototypes
        
        A prototype is a description of the prototypical item in your table.  It's
        kind of like a template for the item.  A prototype can be used to describe what
        attributes are in the item, which are required or optional, and the type of
        value that is associated with the attribute.  In addition, there are special
        values you can use that allow a small range of calculated values in your item.
        
        If you don't specify a prototype, cruddy will store whatever values are in the
        item with no validation or insertion of calculated values.
        
        Let's look at a few examples using prototypes.
        
        ```
        {
          'id': '',
          'created_at': 1,
          'foo': 1
        }
        ```
        
        This prototype says that your item must have an ``id`` attribute whose value is
        of type ``str``, a ``created_at`` attribute whose value is of type ``int``, and
        a ``foo`` attribute whose value is also an ``int``.  Your item may contain
        other items as well (this is not a schema) but it must contain these attribute
        name/value pairs.  If the item you pass into the ``create`` method does not
        contain these attributes cruddy will create the necessary attributes and will
        initialize the value to what ever value you have specified.
        
        
        #### Calculated Values
        
        The above example assumes that you are going to generate the ``id`` and
        ``created_at`` values in your application code.  You may, however, prefer to
        have cruddy handle that for you.  In that case, you can make use of cruddy's
        calcuated value tokens.
        
        ```
        {
          'id': 'on-create:<uuid>',
          'created_at': 'on-create:<timestamp>'
        }
        ```
        
        Now, when you create a new item you could supply one without an ``id`` or
        ``created_at`` value and cruddy will calculate these values for you.  If those
        attributes already exist in the item, cruddy will not overwrite them.  Note
        that the calulated values are specified as ``on-create``.  This is called a
        ``trigger`` and indicates when the calculation will be performed.
        
        If you wanted to also have a timestamp to indicate when an item has been
        modified (i.e. created or updated) you could do this.
        
        ```
        {
          'id': 'on-create:<uuid>',
          'created_at': 'on-create:<timestamp>',
          'modified_at': 'on-update:<timestamp>'
        }
        ```
        
        The currently supported calculated value types are:
        
        * **<uuid>** to generate a string representation of a Type4 UUID
        * **<timestamp>** to generate an integer timestamp generated by
          ``int(time.time()*1000)``
        
        The currently supported triggers for calculated values are:
        
        * **on-create** will be applied when the item is created
        * **on-update** will be applied when the item is created or updated
        
        ### Configuring your CRUD handler
        
        An easy way to configure your CRUD handler is to gather all of the parameters
        together in a dictionary and then pass that dictionary to the class
        constructor.
        
        ```
        import cruddy
        
        params = {
            'profile_name': 'foobar',
            'region_name': 'us-west-2',
            'table_name': 'fiebaz',
            'prototype': {'id': '<on-create:uuid>',
                          'created_at': '<on-create:timestamp>',
                          'modified_at': '<on-update:timestamp>'}
        }
        
        crud = cruddy.CRUD(**params)
        ```
        
        Once you have your handler, you can start to use it.
        
        ```
        item = {'name': 'the dude', 'email': 'the@dude.com', 'twitter': 'thedude'}
        response = crud.create(item)
        ```
        
        The response returned from all CRUD operations is a Python object with the
        following attributes.
        
        * **data** is the actual data returned from the CRUD operation (if successful)
        * **status** is the status of the response and is either ``success`` or
        ``error``
        * **metadata** is metadata from the underlying DynamoDB API call
        * **error_type** will be the type of error, if ``status != 'success'``
        * **error_code** will be the code of error, if ``status != 'success'``
        * **error_type** will be the full error message, if ``status != 'success'``
        * **raw_response** will contain the full response from DynamoDB if the CRUD
        handler is in ``debug`` mode.
        * **is_successful** a simple short-cut, equivalent to ``status == 'success'``
        
        You can convert the CRUDResponse object into a standard Python dictionary using
        the ``flatten`` method
        
        ```
        >>> response = crud.create(...)
        >>> response.flatten()
        {'data': {'created_at': 1452109758363,
          'name': 'the dude',
          'email': 'the@dude.com',
          'twitter': 'thedude',
          'id': 'a6ac0fd7-cdde-4170-a1a9-30e139c44897',
          'modified_at': 1452109758363},
         'error_code': None,
         'error_message': None,
         'error_type': None,
         'metadata': {'HTTPStatusCode': 200,
          'RequestId': 'LBBFLMIAVOKR8LOTK7SRGFO4Q3VV4KQNSO5AEMVJF66Q9ASUAAJG'},
         'raw_response': None,
         'status': 'success'}
         >>>
         ```
         
        ## CRUD operations
        
        The CRUD object supports the following operations.  Note that depending on the
        value of the ``supported_operations`` parameter passed to the constructor, some
        of these methods may return an ``UnsupportedOperation`` error type.
        
        ### list()
        
        Returns a list of items in the database.  Encrypted attributes are not
        decrypted when listing items.
        
        ### get(*id*, *decrypt=False*)
        
        Returns the item corresponding to ``id``.  If the ``decrypt`` param is not
        False (the default) any encrypted attributes in the item will be decrypted
        before the item is returned.  If not, the encrypted attributes will contain the
        encrypted value.
        
        ### create(*item*)
        
        Creates a new item.  You pass in an item containing initial values.  Any
        attribute names defined in ``prototype`` that are missing from the item will be
        added using the default value defined in ``prototype``.
        
        ### update(*item*)
        
        Updates the item based on the current values of the dictionary passed in.
        
        ### delete(*id*)
        
        Deletes the item corresponding to ``id``.
        
        ## Beyond CRUD
        
        The following operations extend beyond the basic CRUD functions but are
        included because of they are quite useful.
        
        ### query(*query*)
        
        Cruddy provides a limited but useful interface to query GSI indexes in DynamoDB
        with the following limitations (hopefully some of these will be expanded or
        eliminated in the future.
        
        * The GSI must be configured with a only HASH and not a RANGE.
        * The only operation supported in the query is equality
        
        To use the ``query`` operation you must pass in a query string of this form:
        
            <attribute_name>=<value>
        
        As stated above, the only operation currently supported is equality (=) but
        other operations will be added over time.  Also, the ``attribute_name`` must be
        an attribute which is configured as the ``HASH`` of a GSI in the DynamoDB
        table.  If all of the above conditions are met, the ``query`` operation will
        return a list (possibly empty) of all items matching the query and the
        ``status`` of the response will be ``success``.  Otherwise, the ``status`` will
        be ``error`` and the ``error_type`` and ``error_message`` will provide further
        information about the error.
        
        ### increment_counter(*item*, *counter_name*, [*increment*])
        
        Atomically increments a counter attribute in the item.  You must specify the
        name of the attribute as ``counter_name`` and, optionally, the ``increment``
        which defaults to ``1``.
        
        ## Using the handler interface
        
        In addition to the methods described above, cruddy also provides a generic
        handler interface.  This is mainly useful when you want to wrap a cruddy
        handler in a Lambda function and then call that Lambda function to access the
        CRUD capabilities.
        
        To call the handler, you simply put all necessary parameters into a Python
        dictionary and then call the handler with that dict.
        
        ```
        params = {
            'operation': 'create',
            'item': {'foo': 'bar', 'fie': 'baz'}
        }
        response = crud.handler(**params)
        ```
        
        So, you could define a Lambda function like this:
        
        ```
        import logging
        import json
        
        import cruddy
        
        LOG = logging.getLogger()
        LOG.setLevel(logging.INFO)
        
        config = json.load(open('config.json'))
        crud = cruddy.CRUD(**config)
        
        
        def handler(event, context):
            LOG.info(event)
            response = crud.handler(**event)
            return response.flatten()
        ```
        
        Where ``config.json`` looks like this:
        
        ```
        {
            "region_name": "us-west-2",
            "table_name": "foobar",
            "prototype": {"id": "<on-create:uuid>",
                          "created_at": "<on-create:timestamp>",
                          "modified_at": "<on-update:timestamp>",
                          "foo": 1,
                          "bar": ""},
        }
        ```
        
        If you uploaded this function (and config file) to AWS Lambda you could then
        invoke the handler like this.
        
        ```
        import json
        
        import boto3
        
        session = boto3.Session()
        lambda_client = session.client('lambda')
        
        params = {'operation': 'create', 'item': {'fie': 'baz'}}
        response = lambda_client.invoke(
            FunctionName='myfunction',
            InvocationType='RequestResponse',
            Payload=json.dumps(params))
        cruddy_response = json.load(response['Payload'])
        ```
        
        The variable ``cruddy_response`` would now contain the response structure
        returned by cruddy, flattened into a Python dictionary.
        
        ## The cruddy CLI
        
        cruddy also offers a CLI that allows you to access your DynamoDB table or
        Lambda-based handler via a simple command line interface.  It supports all
        operations supported by cruddy.
        
        ### Using the cruddy CLI with a DynamoDB table
        
        To use cruddy to directly interact with a DynamoDB table, you need to place the
        configuration information for your cruddy handler in a JSON file.  So, from our
        previous example if we created a file called ``fiebaz.json`` like this:
        
        ```
        {
            "profile_name": "foobar",
            "region_name": "us-west-2",
            "table_name": "fiebaz",
            "prototype": {"id": "<on-create:uuid>",
                          "created_at": "<on-create:timestamp>",
                          "modified_at": "<on-update:timestamp>"}
        }
        ```
        
        We could then reference this when using the cruddy CLI:
        
        ```
        $ cruddy --config-file fiebaz.json list
        [
          {<a listing of all items in fiebaz>}
          ...
        ]
        ```
        
        Use the ``--help`` for more information on how to use the cruddy CLI.
        
        ### Using the cruddy CLI with a Lambda handler
        
        All of the operations of the CLI work exactly the same whether you are using it
        with a DynamoDB table directly or through a Lambda controller.  The only
        difference is that rather than referencing a config file containing info about
        the table and other parameters needed to create the cruddy CRUD handler, you
        simply tell the CLI about the Lambda function.
        
        ```
        $ cruddy --lambda-fn fiebaz list
        [
          {<a listing of all items in fiebaz>}
          ...
        ]
        ```
        
        where ``fiebaz`` is the name of your Lambda handler.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
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
