Metadata-Version: 1.1
Name: salesforce-bulk
Version: 1.0.0
Summary: Python interface to the Salesforce.com Bulk API.
Home-page: https://github.com/heroku/salesforce-bulk
Author: Scott Persinger
Author-email: scottp@heroku.com
License: Copyright (c) 2013 Scott Persinger

MIT License

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"Software"), to deal in the Software without restriction, including
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The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

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Description: # Salesforce Bulk
        
        Python client library for accessing the asynchronous Salesforce.com Bulk API.
        
        ## Installation
        
        ```pip install salesforce-bulk```
        
        ## Authentication
        
        To access the Bulk API you need to authenticate a user into Salesforce. The easiest
        way to do this is just to supply `username` and `password`. This library
        will use the `salesforce-oauth-request` package (which you must install) to run
        the Salesforce OAUTH2 Web flow and return an access token.
        
        ```
        from saleforce_bulk import SalesforceBulk
        
        bulk = SalesforceBulk(username=username,password=password)
        ...
        ```
        
        Alternatively if you run have access to a session ID and instance_url you can use
        those directly:
        
        ```
        from urlparse import urlparse
        from saleforce_bulk import SalesforceBulk
        
        bulk = SalesforceBulk(sessionId=sessionId, host=urlparse(instance_url).hostname)
        ...
        ```
        
        ## Operations
        
        The basic sequence for driving the Bulk API is:
        
        1. Create a new job
        2. Add one or more batches to the job
        3. Wait for each batch to finish
        4. Close the job
        
        
        ## Bulk Query
        
        `SalesforceBulk.create_query_job(object_name, contentType='CSV', concurrency=None)`
        
        Example
        
        ```
        job = bulk.create_query_job("Contact", contentType='CSV')
        batch = bulk.query("select Id,LastName from Contact")
        while not bulk.is_batch_done(job, batch):
        	sleep(10)
        bulk.close_job(job)
        
        for row in bulk.get_batch_result_iter(job, batch, parse_csv=True):
        	print row   #row is a dict
        ```
        
        ## Bulk Insert, Update, Delete
        
        All Bulk upload operations work the same. You set the operation when you create the
        job. Then you submit one or more documents that specify records with columns to
        insert/update/delete. When deleting you should only submit the Id for each record.
        
        For efficiency you should use the `post_bulk_batch` method to post each batch of
        data. (Note that a batch can have a maximum 10,000 records and be 1GB in size.)
        You pass a generator or iterator into this function and it will stream data via
        POST to Salesforce. For help sending CSV formatted data you can use the
        salesforce_bulk.CsvDictsAdapter class. It takes an iterator returning dictionaries
        and returns an iterator which produces CSV data.
        
        Full example:
        
        ```
        from salesforce_bulk import CsvDictsAdapter
        
        job = bulk.create_insert_job("Account", contentType='CSV')
        
        accounts = [dict(Name="Account%d" % idx) for idx in xrange(5)]
        
        csv_iter = CsvDictsAdapter(iter(accounts))
        
        batch = bulk.post_bulk_batch(job, csv_iter)
        
        bulk.wait_for_batch(job, batch)
        
        bulk.close_job(job)
        
        print "Done. Accounts uploaded."
        ```
        
        ### Concurrency mode
        
        When creating the job, pass `concurrency=Serial` or `concurrency=Parallel` to set the
        concurrency mode for the job.
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
