How to Ignore Duplicate Key Errors Safely Using insert_many

You can deal with this by inspecting the errors produced with BulkWriteError. This is actually an “object” which has several properties. The interesting parts are in details:

import pymongo
from bson.json_util import dumps
from pymongo import MongoClient
client = MongoClient()
db = client.test

collection = db.duptest

docs = [{ '_id': 1 }, { '_id': 1 },{ '_id': 2 }]


try:
  result = collection.insert_many(docs,ordered=False)

except pymongo.errors.BulkWriteError as e:
  print e.details['writeErrors']

On a first run, this will give the list of errors under e.details['writeErrors']:

[
  { 
    'index': 1,
    'code': 11000, 
    'errmsg': u'E11000 duplicate key error collection: test.duptest index: _id_ dup key: { : 1 }', 
    'op': {'_id': 1}
  }
]

On a second run, you see three errors because all items existed:

[
  {
    "index": 0,
    "code": 11000,
    "errmsg": "E11000 duplicate key error collection: test.duptest index: _id_ dup key: { : 1 }", 
    "op": {"_id": 1}
   }, 
   {
     "index": 1,
     "code": 11000,
     "errmsg": "E11000 duplicate key error collection: test.duptest index: _id_ dup key: { : 1 }",
     "op": {"_id": 1}
   },
   {
     "index": 2,
     "code": 11000,
     "errmsg": "E11000 duplicate key error collection: test.duptest index: _id_ dup key: { : 2 }",
     "op": {"_id": 2}
   }
]

So all you need do is filter the array for entries with "code": 11000 and then only “panic” when something else is in there

panic = filter(lambda x: x['code'] != 11000, e.details['writeErrors'])

if len(panic) > 0:
  print "really panic"

That gives you a mechanism for ignoring the duplicate key errors but of course paying attention to something that is actually a problem.