pymongo

问题 Am trying to find documents from the mongo collection using the following query. db.collection_name.find({"id" : Id}) where Id is the variable am getting as input. But it doesn't work. If I hard code the value like this db.collection_name.find({"id" : "1a2b"}) it works. "id" is of string type and am using pymongo to access mongo DB. code : client = MongoClient("localhost:27017") db = client['sample_database'] Id = raw_input("enter id") cursor = db.collection_name.find({"id" : Id}) 回答1: Try

问题 This works- cursor = collection.find(query).limit(10678) for doc in cursor: print "entered loop" This doesn't- cursor = collection.find(query).limit(10679) for doc in cursor: print "entered loop" It just doesn't enter the loop. Ofcourse this upper-limit-number is different for different collections, which may be because of difference in size of each doc. So is there any size limitation for cursors in pymongo ? Any clues? 来源： https://stackoverflow.com/questions/14685492/pymongo-cursor-not

问题 I need test the accuracy of a server mongodb. I am trying to insert a sequence of data, take the moment and it was sent to the database to know when it was inserted. I'm trying this: #!/usr/bin/python from pymongo import Connection from datetime import date, timedelta, datetime class FilterData: @classmethod def setData(self, serialData): try: con = Connection('IP_REMOTE', 27017, safe=True) db = con['resposta'] inoshare = db.resposta inoshare.insert(serialData) con.close() except Exception as

问题 On my pymongo code, inserting twice the same doc raises an error : document = {"auteur" : "romain", "text" : "premier post", "tag" : "test2", "date" : datetime.datetime.utcnow()} collection.insert_one(document) collection.insert_one(document) raises : DuplicateKeyError: E11000 duplicate key error collection: test.myCollection index: _id_ dup key: { : ObjectId('5aa282eff1dba231beada9e3') } inserting two documents with different content works fine. Seems like according to https://docs.mongodb

问题 Here is my attempt at performing the aggregation (day-wise) based on timestamp if all the elements are hardcoded inside the query. pipe = [ { "$match": { "cid": ObjectId("57fe39972b8dbc1387b20913") } }, { "$project": { "animal_dog": "$animal.dog", "animal_dog_tail": "$animal.dog.tail", "animal_cat": "$animal.cat", "tree": "$fruits", "day": {"$substr": ["$timestamp", 0, 10]} }}, { "$group": { "_id" : "$day", "animal_dog" : {"$sum": "$animal_dog"}, "animal_dog_tail": {"$sum": "$animal_dog_tail"

问题 I have a Flask app that uses mongoengine and running on Heroku, init I use the bson package and after I updateded it from 0.5.6 to 0.5.7 I started getting the following error message: [2018-11-23 05:56:43 +0000] [39] [INFO] Worker exiting (pid: 39) [2018-11-23 05:56:43 +0000] [40] [ERROR] Exception in worker process Traceback (most recent call last): File "/app/.heroku/python/lib/python3.6/site-packages/gunicorn/arbiter.py", line 583, in spawn_worker worker.init_process() File "/app/.heroku

问题 I'm adding a 'GUID' key with a value of uuid.uuid1() (from python uuid module) for all my documents in Mongo. I noticed they are being stored not as strings, but as type BSON::Binary . I've done some Googling already, but I still don't understand what the purpose/advantage to this serialization is. Can someone explain? Should I be converting the uuid.uuid1() to strings before storing? How can I use a string to find() by the GUID value like db.myCol.find({ 'GUID' : aString })? 回答1: The default

问题 we have MongoDB 2.6 and 2 Replica Set, and we use pymongo driver and connect Mongo Replicat Set with the following url mongodb://admin:admin@127.0.0.1:10011:127.0.0.1:10012,127.0.0.1:10013/db?replicaSet=replica with python code from pymongo import MongoClient url = 'mongodb://admin:admin@127.0.0.1:10011:127.0.0.1:10012,127.0.0.1:10013/db?replicaSet=replica' db = 'db' db = MongoClient( url, readPreference='secondary', secondary_acceptable_latency_ms=1000, )[db] db.test.find_one() # more read

问题 I'm trying to create a pipeline which will count how many documents match some conditions. I can't see any way to use a regular expression in the conditions though. Here's a simplified version of my pipeline with annotations: db.Collection.aggregate([ // Pipeline before the issue {'$group': { '_id': { 'field': '$my_field', // Included for completeness }, 'first_count': {'$sum': { // We're going to count the number '$cond': [ // of documents that have 'foo' in {'$eq: ['$field_foo', 'foo']}, 1,

问题 I would like to use PyMongo’s bulk write operation features which executes write operations in batches in order to reduces the number of network round trips and increaseses rite throughput. I also found here that it was possible to used 5000 as a batch number. However, I do not want is the best size for batch number and how to combine PyMongo’s bulk write operation features with generators in the following code? from pymongo import MongoClient from itertools import groupby import csv def iter