IHRD_PMD_Software_Developer_Backend

Django Task

1.Home Page Accessibility

Check if email or phone number already exists in registration:

if get_user_model().objects.filter(email=email).exists():
      return Response({'code': 400, 'message': 'Email already exists'})

page accessed successfully

2.User Registration Functionality:

User registerd succesfully!!:

3.User Login Functionality:

Authenticate the user in login function user = get_user_model().objects.filter(email=email).first()

Update last login time user.last_login = timezone.now() user.save()

Generate JWT tokens from rest_framework import status from rest_framework_jwt.settings import api_settings payload = jwt_payload_handler(user) access_token = jwt_encode_handler(payload)

login success

4.User Data Retrieval

Use RetrieveAPIView to retrieve a single model instance (in this case, the authenticated user)

Specify the authentication classes that you want to use (SessionAuthentication,TokenAuthentication, etc.) in authentication_classes

Use IsAuthenticated permission class to ensure only authenticated users can access this endpoint

image_name field deleted in serializer beacause there is no need of an image since image doesnot in APIUser model

5.Data Import and Visualization:

**data loaded from json file**

import sqlite3
import json

# Read JSON file
with open('dataset_world_population_by_country_name.json', 'r') as file:
    data = json.load(file)

# Create a SQLite database connection
conn = sqlite3.connect('video_db.db')
cursor = conn.cursor()

# Create a table to store population data
cursor.execute('''CREATE TABLE IF NOT EXISTS CountryPopulation (
	            country TEXT PRIMARY KEY,
	            population INTEGER
	        )''')

# Insert data into the SQLite database
for entry in data:
    country = entry['country']
    population = entry['pop1980']+entry['pop2000']+entry['pop2010']+entry['pop2022']					+entry['pop2023']+entry['pop2030']+entry['pop2050']
    cursor.execute("INSERT OR REPLACE INTO CountryPopulation (country, population) VALUES (?, ?)", (country, population))

# Commit changes and close connection
conn.commit()
conn.close()
	
**viewd in sql table**


		  country  population
0               India  9028361192
1               China  9174463823
2       United States  2222562101
3           Indonesia  1768676464
4            Pakistan  1547597303
..                ...         ...
229        Montserrat       38386
230  Falkland Islands       23726
231              Niue       15436
232           Tokelau       12920
233      Vatican City        4300

**data visualized in another file**

import pandas as pd
import matplotlib.pyplot as plt
import sqlite3
from django.shortcuts import render
from users.models import CountryPopulation

# Retrieve data from SQLite database
conn = sqlite3.connect('video_db.db')
df = pd.read_sql_query("SELECT * FROM CountryPopulation", conn)
conn.close()

# Display table of population data
print(df)

# Create a bar graph
plt.figure(figsize=(12, 6))
plt.bar(df['country'], df['population'])
plt.xlabel('Country')
plt.ylabel('Population')
plt.title('Population by Country')
plt.xticks(rotation=90)
plt.tight_layout()
plt.show()
plt.savefig('population_chart.png')

def display_population_table(request):
    queryset = CountryPopulation.objects.all()

    # Convert queryset to list of dictionaries
    data = list(queryset.values())  # or values_list() if you need specific fields

    # Convert data to DataFrame using Pandas
    df = pd.DataFrame(data)

    # Convert DataFrame to HTML table representation
    population_table = df.to_html(classes='table table-striped')

    return render(request, 'population_table.html', {'population_table': population_table})

6.Advanced Search Functionality

import json

# Load the data from the JSON file
with open('population_data.json', 'r') as file:
    data = json.load(file)

# Define a function for advanced search based on user-defined criteria
def advanced_search(data, criteria):
    # Initialize an empty list to store matched results
    matched_results = []

    # Iterate through each entry in the dataset
    for entry in data:
	match = True  # Flag to track if the entry matches all search criteria

	# Check if the entry matches all user-defined criteria
	for key, value in criteria.items():
	    if key in entry:
	        if entry[key] != value:
	            match = False
	            break  # Break out of the loop if any criteria doesn't match

	# If all criteria match, add the entry to matched_results
	if match:
	    matched_results.append(entry)

    return matched_results

# Example: Perform an advanced search based on certain criteria
search_criteria = {
    "country": "United Kingdom",
    "pop2023": 67736802,
    "density": 279.9851
}

# Perform the advanced search
results = advanced_search(data, search_criteria)

# Display the matched results
for result in results:
    print(result)

7.Add a Logout button:

// Logout functionality in JavaScript (example using localStorage)

// Function to handle logout action
function logout() {
  // Remove the token from localStorage or sessionStorage
  localStorage.removeItem('jwtToken'); // Change 'jwtToken' to your token key

  // Redirect to the login page or update UI accordingly
  window.location.href = '/login'; // Redirect to login page
}

FastAPi Task

run via : http://0.0.0.0:5001/

Setup FastAPI and Pandas:

Load Netflix dataset into a Pandas DataFrame

netflix_data = pd.read_csv("dataset_netflix.csv")

data visualized using pie and bar chart

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