:py:mod:`airflow.providers.salesforce.hooks.salesforce`
=======================================================

.. py:module:: airflow.providers.salesforce.hooks.salesforce

.. autoapi-nested-parse::

   This module contains a Salesforce Hook which allows you to connect to your Salesforce instance,
   retrieve data from it, and write that data to a file for other uses.

   .. note:: this hook also relies on the simple_salesforce package:
         https://github.com/simple-salesforce/simple-salesforce


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.salesforce.hooks.salesforce.SalesforceHook


Attributes
~~~~~~~~~~

.. autoapisummary::

   airflow.providers.salesforce.hooks.salesforce.log


.. py:data:: log
   

.. py:class:: SalesforceHook(salesforce_conn_id = default_conn_name, session_id = None, session = None)

   Bases: :py:obj:`airflow.hooks.base.BaseHook`

   Creates new connection to Salesforce and allows you to pull data out of SFDC and save it to a file.

   You can then use that file with other Airflow operators to move the data into another data source.

   :param conn_id: The name of the connection that has the parameters needed to connect to Salesforce.
       The connection should be of type `Salesforce`.
   :param session_id: The access token for a given HTTP request session.
   :param session: A custom HTTP request session. This enables the use of requests Session features not
       otherwise exposed by `simple_salesforce`.

   .. note::
       A connection to Salesforce can be created via several authentication options:

       * Password: Provide Username, Password, and Security Token
       * Direct Session: Provide a `session_id` and either Instance or Instance URL
       * OAuth 2.0 JWT: Provide a Consumer Key and either a Private Key or Private Key File Path
       * IP Filtering: Provide Username, Password, and an Organization ID

       If in sandbox, enter a Domain value of 'test'.

   .. py:attribute:: conn_name_attr
      :annotation: = salesforce_conn_id

      
   .. py:attribute:: default_conn_name
      :annotation: = salesforce_default

      
   .. py:attribute:: conn_type
      :annotation: = salesforce

      
   .. py:attribute:: hook_name
      :annotation: = Salesforce

      
   .. py:method:: get_connection_form_widgets()
      :staticmethod:

      Returns connection widgets to add to connection form


   .. py:method:: get_ui_field_behaviour()
      :staticmethod:

      Returns custom field behaviour


   .. py:method:: conn(self)

      Returns a Salesforce instance. (cached)


   .. py:method:: get_conn(self)

      Returns a Salesforce instance. (cached)


   .. py:method:: make_query(self, query, include_deleted = False, query_params = None)

      Make a query to Salesforce.

      :param query: The query to make to Salesforce.
      :param include_deleted: True if the query should include deleted records.
      :param query_params: Additional optional arguments
      :return: The query result.
      :rtype: dict


   .. py:method:: describe_object(self, obj)

      Get the description of an object from Salesforce.
      This description is the object's schema and
      some extra metadata that Salesforce stores for each object.

      :param obj: The name of the Salesforce object that we are getting a description of.
      :return: the description of the Salesforce object.
      :rtype: dict


   .. py:method:: get_available_fields(self, obj)

      Get a list of all available fields for an object.

      :param obj: The name of the Salesforce object that we are getting a description of.
      :return: the names of the fields.
      :rtype: list(str)


   .. py:method:: get_object_from_salesforce(self, obj, fields)

      Get all instances of the `object` from Salesforce.
      For each model, only get the fields specified in fields.

      All we really do underneath the hood is run:
          SELECT <fields> FROM <obj>;

      :param obj: The object name to get from Salesforce.
      :param fields: The fields to get from the object.
      :return: all instances of the object from Salesforce.
      :rtype: dict


   .. py:method:: write_object_to_file(self, query_results, filename, fmt = 'csv', coerce_to_timestamp = False, record_time_added = False)

      Write query results to file.

      Acceptable formats are:
          - csv:
              comma-separated-values file. This is the default format.
          - json:
              JSON array. Each element in the array is a different row.
          - ndjson:
              JSON array but each element is new-line delimited instead of comma delimited like in `json`

      This requires a significant amount of cleanup.
      Pandas doesn't handle output to CSV and json in a uniform way.
      This is especially painful for datetime types.
      Pandas wants to write them as strings in CSV, but as millisecond Unix timestamps.

      By default, this function will try and leave all values as they are represented in Salesforce.
      You use the `coerce_to_timestamp` flag to force all datetimes to become Unix timestamps (UTC).
      This is can be greatly beneficial as it will make all of your datetime fields look the same,
      and makes it easier to work with in other database environments

      :param query_results: the results from a SQL query
      :param filename: the name of the file where the data should be dumped to
      :param fmt: the format you want the output in. Default:  'csv'
      :param coerce_to_timestamp: True if you want all datetime fields to be converted into Unix timestamps.
          False if you want them to be left in the same format as they were in Salesforce.
          Leaving the value as False will result in datetimes being strings. Default: False
      :param record_time_added: True if you want to add a Unix timestamp field
          to the resulting data that marks when the data was fetched from Salesforce. Default: False
      :return: the dataframe that gets written to the file.
      :rtype: pandas.Dataframe


   .. py:method:: object_to_df(self, query_results, coerce_to_timestamp = False, record_time_added = False)

      Export query results to dataframe.

      By default, this function will try and leave all values as they are represented in Salesforce.
      You use the `coerce_to_timestamp` flag to force all datetimes to become Unix timestamps (UTC).
      This is can be greatly beneficial as it will make all of your datetime fields look the same,
      and makes it easier to work with in other database environments

      :param query_results: the results from a SQL query
      :param coerce_to_timestamp: True if you want all datetime fields to be converted into Unix timestamps.
          False if you want them to be left in the same format as they were in Salesforce.
          Leaving the value as False will result in datetimes being strings. Default: False
      :param record_time_added: True if you want to add a Unix timestamp field
          to the resulting data that marks when the data was fetched from Salesforce. Default: False
      :return: the dataframe.
      :rtype: pandas.Dataframe