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    <p>I recently looked for such a thing myself (inspired by <a href="http://docs.djangoproject.com/en/1.1/topics/db/queries/#topics-db-queries-update" rel="noreferrer">QuerySet.update()</a>, as I imagine you are too). To my knowledge, no bulk create exists in the current production framework (1.1.1 as of today). We ended up creating a custom manager for the model that needed bulk-create, and created a function on that manager to build an appropriate SQL statement with the sequence of VALUES parameters.</p> <p>Something like (apologies if this does not work... hopefully I've adapted this runnably from our code):</p> <pre><code>from django.db import models, connection class MyManager(models.Manager): def create_in_bulk(self, values): base_sql = "INSERT INTO tbl_name (a,b,c) VALUES " values_sql = [] values_data = [] for value_list in values: placeholders = ['%s' for i in range(len(value_list))] values_sql.append("(%s)" % ','.join(placeholders)) values_data.extend(value_list) sql = '%s%s' % (base_sql, ', '.join(values_sql)) curs = connection.cursor() curs.execute(sql, values_data) class MyObject(models.Model): # model definition as usual... assume: foo = models.CharField(max_length=128) # custom manager objects = MyManager() MyObject.objects.create_in_bulk( [('hello',), ('bye',), ('c', )] ) </code></pre> <p>This approach does run the risk of being very specific to a particular database. In our case, we wanted the function to return the IDs just created, so we had a postgres-specific query in the function to generate the requisite number of IDs from the primary key sequence for the table that represents the object. That said, it does perform significantly better in tests versus iterating over the data and issuing separate QuerySet.create() statements.</p>
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    1. POHow do I perform a batch insert in Django?
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    1. USJarret Hardie
    1. USJarret Hardie
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    1. POHow do I perform a batch insert in Django?
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    1. COBy the way. This approach could lead to "Packet too large" error on mysql (and probably other databases) if you have very many data. It is better to split your dataset into a smaller chunks.
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      1. USAlexander Artemenko
 

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