azure-devops-aws / directory_app

Teacher Directory

Teacher's Directory

To setup the project follow the the instructions below

• optional setup venv if required
  • pip install virtualenv
  • virtualenv venv
• To activate venv in windows
  • venv\script\activate
• To activate venv in linux
  • source venv/bin/activate

Clone the project

• git clone https://github.com/doddahulugappa/directory_app.git
• cd directory_app
  • pip install -r requirements.txt
  • python manage.py makemigrations
  • python manage.py migrate
  • python manage.py createsuperuser
  • python manage.py runserver <HOST>:<PORT>

Usage Guide

• Open the url in any browser (http://HOST:PORT)
  • to see all the features as per the requirement, implemented in custom admin dashboard itself.
  • please navigate to admin panel from the user profile menu
  • Login with the created user creds and explore all the functionalities
• Use Import option for Bulk Import
  • first import subjects.csv from data directory
  • second import teacher.csv from data directory
  • try to add subjects more than 5, will get an error
  • try to add duplicate email, will get an error
• Export options given for the export data
• Filter options for filtering data

Docker Setup

• Create Dockerfile and save in the main directory

# Use the official Python image from the Docker Hub
FROM python:3.8.2

# Make a new directory to put our code in.
RUN mkdir /directory_app

# Change the working directory.
WORKDIR /directory_app

# Copy to code folder
COPY . /directory_app/

# Install the requirements.
RUN pip install -r requirements.txt

# Run the application:
CMD python manage.py runserver 0.0.0.0:8000

• Build Docker Image

docker build -t directory_app .

• Run Docker Image

docker run -it -p 8020:8020 directory_app

• Tag Docker Image

docker tag directory_app_v1 doddahulugappa/django:v2

• Push Docker Image

docker push doddahulugappa/django:v2

• Azure ACR

az login
az acr login --name myregistry
docker login myregistry.azurecr.io
docker tag directory_app myregistry.azurecr.io/huli/directory_app
docker push myregistry.azurecr.io/django/directoryapp

Celery Integration

pip install celery
pip install redis
pip install django-celery-results
pip install django-celery-beat

CELERY_BROKER_URL = 'redis://127.0.0.1:6379'
CELERY_ACCEPT_CONTENT = ['application/json']
CELERY_RESULT_SERIALIZER = 'json'
CELERY_TASK_SERIALIZER = 'json'
CELERY_TIMEZONE = 'Asia/Dubai'
CELERY_RESULT_BACKEND = 'django-db'

• command to start celery worker and celery beat

celery -A directory_app.celery worker --pool=solo -l info
celery -A directory_app beat -l info --scheduler=django_celery_beat.schedulers.DatabaseScheduler

Redis for windows

Download msi file from below and install

• https://github.com/tporadowski/redis/releases

GraphQL integration

• settings.py

pip install graphene-django
INSTALLED_APPS = (
    # ...
    'graphene_django',
)

GRAPHENE = {
    'SCHEMA': 'app.schema.schema' # Where your Graphene schema lives
}

• urls.py

from django.conf.urls import url
from graphene_django.views import GraphQLView

urlpatterns = [
    # ...
    url(r'^graphql$', GraphQLView.as_view(graphiql=True)),
]

• schema.py as similar path as settings.py

from graphene_django import DjangoObjectType
import graphene

class User(DjangoObjectType):
    class Meta:
        model = UserModel

class Query(graphene.ObjectType):
    users = graphene.List(User)

    @graphene.resolve_only_args
    def resolve_users(self):
        return UserModel.objects.all()

schema = graphene.Schema(query=Query)

query = '''
    query {
      users {
        name,
        lastName
      }
    }
'''
result = schema.execute(query)

• Sample Queries

{
  subjects {
    subjectName
  }
}

{
  teachers {
    firstName
    lastName
    phoneNumber
    roomNumber
    emailAddress
    profilePicture
  }
}