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مدرس و برنامه نویس پایتون و لینوکس @alirezastack
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In order to verify that you certificate is generated successfully in openssl:

openssl verify -verbose -CAfile /etc/ssl/ca.pem /etc/ssl/mongo.pem

#openssl #verify #pem #ca #mongodb #ssl
How to check if a field exists in MongoDB and it's value is not empty?

db.users.find({ profile_image: {$exists: 1, $ne: ""}  }, { profile_image:1 })

NOTE: $ne makes sure that field is not empty and $exists check whether field exist or not.


#mongodb #mongo #find #exists #ne
Months ago we have talked about how to get mongoDB data changes. THe problem with that article was that if for any reason your script
was stopped you will lose the data in the downtime period.

Now we have a new solution that you will read from the point in time that have read last time. MongoDB uses bson Timestamp in order for its internal usage like replication oplog logs. We can use the same Timestamp and store it somewhere to read from the exact point
that we have read last time.

In python you can import it like below:

from bson.timestamp import Timestamp


Now to read data from that point read that time stamp from where you have saved it and query the oplog from that point:

ts = YOUR_TIMESTAMP_HERE
cursor = oplog.find({'ts': {'$gt': ts}},
cursor_type=pymongo.CursorType.TAILABLE_AWAIT,
oplog_replay=True)

After traversing cursors and catching mongoDB changes you can store the new timestamp that resides in ts field in the document you have fetched from MongoDB oplog.

Now use a while True and read data until cursor is alive. The point of this post is that you can store ts somewhere and read from the point you have stored ts.


If you remember from before we got last changes by the query below:

last = oplog.find().sort('$natural', pymongo.DESCENDING).limit(1).next()
ts = last['ts']


We read the last ts and read from the last record, that's why we were missing data.

#mongodb #mongo #replication #oplog #timestamp #cursor
In order to get a random document from MongoDB collection you can use aggregate framework:

db.users.aggregate(    [ { $sample: { size: 1 } } ] )

NOTE: MongoDB 3.2 introduced $sample to the aggregation pipeline.


Read more here: https://www.mongodb.com/blog/post/how-to-perform-random-queries-on-mongodb


This method is the fastest and most efficient way of getting random data from a huge database like 100 M records.

#mongodb #mongo #aggregate #sample #random
in pymongo you can give name to your connections. This definitely helps to debug issues or trace logs when seeing mongoDB logs. The
most important part if this scenario is when you are using micro service architecture and you have tens of modules which works independently from each other and send their requests to MongoDB:

mc = pymongo.MongoClient(host, port, appname='YOUR_APP_NAME')


Now if you look at the MongoDB log you would see:

I COMMAND  [conn173140] command MY_DB.users appName: "YOUR_APP_NAME" command: find { find: "deleted_users", filter: {}, sort: {        acquired_date: 1 }, skip: 19973, limit: 1000, $readPreference: { mode: "secondaryPreferred" }, $db: "blahblah" } planSummary:          COLLSCAN keysExamined:0 docsExamined:19973 hasSortStage:1 cursorExhausted:1 numYields:312 nreturned:0 reslen:235 locks:{ Global: {     acquireCount: { r: 626 } }, Database: { acquireCount: { r: 313 } }, Collection: { acquireCount: { r: 313 } } } protocol:op_query 153ms

In the above log you would see YOUR_APP_NAME.


#mongodb #mongo #pymongo #appname
Simple bash script to take nightly MongoDB backups:

#!/bin/sh
DIR=`date +%m%d%y`
DEST=/db_backups/$DIR
mkdir $DEST
mongodump -h <your_database_host> -d <your_database_name> -u <username> -p <password> -o $DEST

NOTE: db_backups folder shoud already be created by mkdir /db_backups.


Put it in a crontab for nightly backups. First open crotab:

sudo crontab -e


Create a new line (entry) in crontab and paste the below cron task:

45 1 * * * ../../scripts/db_backup.sh

NOTE: here our script is called db_backup.sh, should you use your own script name here. and make it executable by chmod +x /your/ full_path/scripts/db_backup.sh


#mongodb #backup #cron #cronjob #coderwall #mongodump #bash
How to ignore extra fields for schema validation in Mongoengine?

Some records currently have extra fields that are not included in my model schema (by error, but I want to handle these cases). When I try to query the DB and transform the records into the schema, I get the following error:

FieldDoesNotExist
The field 'X' does not exist on the document 'Y'



For ignoring this error when having extra fields while getting data, set strict to False in your meta dictionary.


class User(Document):
email = StringField(required=True, unique=True)
password = StringField()
meta = {'strict': False}



#mongodb #mongo #python #mongoengine #strict #FieldDoesNotExist