Forem: parmeshwar rathod

🚀 20 Programming Languages That Changed Their Original Names 👇

parmeshwar rathod — Mon, 21 Oct 2024 12:30:00 +0000

Ever wonder how some of the most popular programming languages got their names? You might be surprised to learn that many of them started with completely different names! Check out these fascinating examples:

JavaScript (Originally: Mocha)
Python (Originally: Molder)
Java (Originally: Oak)
C++ (Originally:_ C with Classes_)
Ruby (Originally: DLite)
PHP (Originally: Personal Home Page Tools)
Perl (Originally: Pearl)
Rust (Originally: Graydon)
Swift (Originally: Bob)
Kotlin (Originally: Jet)
ECMAScript (Originally: MochaScript)
TypeScript (Originally: Script#)
Go (Originally: Go Lang)
Scala (Originally: Scalable Language)
Julia (Originally: Cathy)
Haskell (Originally: ISWIM)
Lua (Originally: Lua Script)
Pascal (Originally: P-System)
Visual Basic (Originally: BASIC Interpreter)
Delphi (Originally: Turbo Pascal)

🎉 Honorable Mentions:

C# (Originally: COOL)
F# (Originally: FSharp)
ActionScript (Originally: Flash Script)

💡Why the Name Changes? Programming languages often change names due to:

Trademark issues
Rebranding for a fresh start
Expanded capabilities
To avoid confusion with other languages
Better reflect the language’s features
Merging with other projects
A shift in focus or target audience
To improve marketability
Name changes can help languages evolve and stand out in the ever-growing tech landscape! 🌐

Did any of these surprise you? Let’s talk about it in the comments!
👇

😎 Scale your Django App with Celery

parmeshwar rathod — Thu, 14 Dec 2023 03:56:10 +0000

Here, I will demonstrate how I integrated Celery into my Django app after reading many frustrating documentation pages. trust me you will find this is the easiest way

Requirements:

running django app template( if don't have clone it this repo )
celery
celery-beat
docker(optional) or redis-server

Celery in nutshell:

Celery is distributed task queue that helps in manage and execute the tasks in the background environments

to execute and receive task celery requires a message broker such as RabbitMQ, Redis. Celery worker nodes are used for offloading data-intensive processes to the background, making applications more efficient. Celery is highly available, and a single Celery worker can process millions of tasks a minute. As Celery workers perform critical tasks at scale, it is also important to monitor their performance, this worker continuously looks for tasks in the broker queue, picks a task and spin up a child process to process that task.
we will be using redis as message broker because its easy and popular.

**Celery beat is a scheduler, It kicks off tasks at regular intervals, that are then executed by available worker nodes in the cluster.

So let's install the celery and django_celery_beat

$ pip install celery django_celery_beat

Post installation of celery, django_celery_beat , let's do some configurations in django project

First, create a 'celery.py' file at the root of your project app. For illustration, if 'myapp' is your root project, then create 'celery.py' under the 'myapp' folder.

#celery.py

import os
from celery import Celery
from django.conf import settings

os.environ.setdefault("DJANGO_SETTINGS_MODULE", "myapp.settings")
app = Celery("myapp")
app.config_from_object("django.conf:settings", namespace="CELERY")
app.autodiscover_tasks()
app.conf.beat_scheduler = 'django_celery_beat.schedulers:DatabaseScheduler'

@app.task(bind=True, ignore_result=True)
def debug_task(self):
    print(f'Request: {self.request!r}')

In the above file, we have set some configurations that are important for the Celery app to run. We have used 'DatabaseScheduler' as the scheduler, which will store all schedules in the database. Alternatively, you can use 'PersistentScheduler,' which will create a file instead of storing in the database

make some changes in __init__.py file as below

# myapp__init__.py

from .celery import app  as celery_app

__all__ = ("celery_app")

now add some variables and installed app in settings.py file

#settings.py
...
INSTALLED_APPS = [
...
    'django_celery_beat'

]
...

CELERY_BROKER_URL = os.environ.get("CELERY_BROKER", "redis://127.0.0.1:6379/0")
CELERY_RESULT_BACKEND = os.environ.get("CELERY_BACKEND", "redis://127.0.0.1:6379/0")
CELERY_ACCEPT_CONTENT = ['json']
CELERY_TASK_SERIALIZER = 'json'
CELERY_RESULT_SERIALIZER = 'json'
CELERY_TIMEZONE = 'UTC'        
CELERY_TASK_TRACK_STARTED = True
CELERY_TASK_TIME_LIMIT = 30 * 60

Post all the configuration ,migrate the changes using below command (Tables will be created to store tasks and schedules)

$ python manage.py migrate

Now, starting the Docker container will pull the Redis image and run your Redis container in detached mode on port 6379.

$ docker run -d -p 6379:6379 redis

OR else you can start using Redis-cli

if you don't have docker then you can simply download the Redis from it's official site

to start the redis-server
$ sudo service redis-server restart

check if if its
$ redis-cli ping
out will be
$ PONG

All configurations are done, let's start the Celery and Beat
to start celery worker node:
$ celery -A <app-name> worker -l INFO
output:

start the beat for scheduler:
$ celery -A <app-name> beat -l INFO
output:

You can run both the worker and beat commands simultaneously using one command :
$ celery -A <root-app=name> worker --beat -l info

Let's schedule a task using the Django admin panel. Add a new task under the 'Periodic Task' table

Specify the date and time you would like to schedule for the trigger

finally we have scheduled and executed the debug task

how mongo import/export works ?

parmeshwar rathod — Wed, 27 Apr 2022 09:27:14 +0000

mongodump --uri "mongodb+srv://:@.mongodb.net/sample_supplies"

mongoexport --uri="mongodb+srv://:@.mongodb.net/sample_supplies" --collection=sales --out=sales.json

mongoimport --uri="mongodb+srv://:@.mongodb.net/sample_supplies" --drop sales.json

mongoDb change position of Array element

parmeshwar rathod — Wed, 02 Feb 2022 19:15:29 +0000

This post is to understand mongoDB query
Let's se how s$position operator works!! 🤩🥳

$position

it's operator used in mongoDB woth $(dollerSign) as pre-
basically its specifies position(index) in an Array
at which $push operator inserts elements/objects.

Example

let's see how to add element at any
position in above document using
$positoon operator

sql vs. nosql

parmeshwar rathod — Tue, 07 Sep 2021 04:20:06 +0000

two types sql and no-sql

SQL

SQL or Structured Query Language is pronounced as “S-Q-L” or sometimes as “see-quel” is a standard language to access and manipulate Relational Databases.
Common and Popular Examples of Relational Databases which use SQL are —

MySQL
Oracle
SQLite
Postgres
MS-SQL

No-SQL

As the name suggests NoSQL is “not” SQL, in other words, it is a non-relational database and is unstructured. Due to its unstructured nature, it is sometimes called as UnQL

Common and Popular Examples of NoSQL Databases are —

Mongo DB
BigTable
Cassandra
Hbase
Redis