How to Ignore Duplicate Key Errors Safely Using insert_many

Question

I need to ignore duplicate inserts when using insert_many with pymongo, where the duplicates are based on the index. I've seen this question asked on stackoverflow, but I haven't seen a useful answer.

Here's my code snippet:

try:
    results = mongo_connection[db][collection].insert_many(documents, ordered=False, bypass_document_validation=True)
except pymongo.errors.BulkWriteError as e:
    logger.error(e)

I would like the insert_many to ignore duplicates and not throw an exception (which fills up my error logs). Alternatively, is there a separate exception handler I could use, so that I can just ignore the errors. I miss "w=0"...

Thanks

Answer 1

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.

Answer 2

Adding more to Neil's solution.

Having 'ordered=False, bypass_document_validation=True' params allows new pending insertion to occur even on duplicate exception.

from pymongo import MongoClient, errors

DB_CLIENT = MongoClient()
MY_DB = DB_CLIENT['my_db']
TEST_COLL = MY_DB.dup_test_coll

doc_list = [
    {
        "_id": "82aced0eeab2467c93d04a9f72bf91e1",
        "name": "shakeel"
    },
    {
        "_id": "82aced0eeab2467c93d04a9f72bf91e1",  # duplicate error: 11000
        "name": "shakeel"
    },
    {
        "_id": "fab9816677774ca6ab6d86fc7b40dc62",  # this new doc gets inserted
        "name": "abc"
    }
]

try:
    # inserts new documents even on error
    TEST_COLL.insert_many(doc_list, ordered=False, bypass_document_validation=True)
except errors.BulkWriteError as e:
    print(f"Articles bulk insertion error {e}")

    panic_list = list(filter(lambda x: x['code'] != 11000, e.details['writeErrors']))
    if len(panic_list) > 0:
        print(f"these are not duplicate errors {panic_list}")

And since we are talking about duplicates its worth checking this solution as well.