mrtushartiwari

Coding Assessment Documentation

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Problem Statement

Design and implement two API endpoints using FastAPI or Flask that automate the process of ranking resumes based on job descriptions. The assessment evaluates candidates on their ability to handle text extraction, data processing, and structured outputs through REST APIs.
Note: Candidates must use FastAPI or Flask, implement a well-documented Swagger UI, and provide a loom video explaining their process and how they built the solution and a working demo.

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,Rank,Company,Industry,Address,City,State / Country,Postal Code,Country,"Revenue (in millions, USD)",Employees,Ticker,Website,CEO,Indian_cities,Department_in_india
0,1,Walmart,General Merchandisers,702 S.W. Eighth St.,Bentonville,Arkansas,72716,U.S.,"$572,754",2300000.0,WMT,www.walmart.com,C. Douglas Mcmillon,"['Bangalore', 'Gurugram', 'Hyderabad', 'Mumbai', 'New Delhi', 'Pune']","['E-commerce', 'Technology', 'Data Analytics', 'Finance', 'Human Resources', 'Supply Chain', 'Marketing', 'Customer Service', 'Operations', 'Legal']"
1,2,Amazon.com,Internet Services and Retailing,410 Terry Ave. N.,Seattle,Washington,98109,U.S.,"$469,822",1608000.0,AMZN,www.amazon.com,Andrew R. Jassy,"['Bangalore', 'Hyderabad', 'Chennai', 'Gurgaon']","['Technology', 'Operations', 'Customer Service', 'Business Development', 'Finance', 'Human Resources', 'Marketing']"
2,3,State Grid,Utilities,86 Xichang'an Ave.,Beijing,China,100031,China,"$460,617",871145.0,,www.sgcc.com.cn,,[],[]
3,4,China National Petroleum,Petroleum Refining,9 Dong

mrtushartiwari

import pandas as pd
from datetime import datetime
df = pd.DataFrame([1678448391,1678448399,1678448400,1678448500,1678448900],columns =[ 'time'])
df['time'] = pd.to_datetime(df['time'],unit='s', utc= True)
df['time'] = pd.to_datetime(pd.to_datetime(df['time'],unit='s'),utc = True)
df['time'].dt.tz_convert('Asia/Kolkata')

mrtushartiwari

manual_cities_urls = {
    "Abu": "https://en.wikipedia.org/wiki/Mount_Abu",
    "Ahmadabad": "https://en.wikipedia.org/wiki/Ahmedabad",
    "Bally": "https://en.wikipedia.org/wiki/Bally,_Howrah",
    "Banda": "https://en.wikipedia.org/wiki/Banda,_Uttar_Pradesh",
    "Barmer": "https://en.wikipedia.org/wiki/Barmer,_Rajasthan",
    "Basti": "https://en.wikipedia.org/wiki/Basti_district",
    "Betul": "https://en.wikipedia.org/wiki/Betul,_Madhya_Pradesh",
    "Bhadravati": "https://en.wikipedia.org/wiki/Bhadravati,_Karnataka",
    "Bhojpur": "https://en.wikipedia.org/wiki/Bhojpur,_Madhya_Pradesh",

mrtushartiwari

cities_list= [
    "Port Blair",
    "Adoni",
    "Amaravati",
    "Anantapur",
    "Chandragiri",
    "Chittoor",
    "Dowlaiswaram",
    "Eluru",
    "Guntur",

mrtushartiwari

from fastapi import FastAPI
import requests
import json
host = '0.0.0.0:8001' # diffent API running  

app = FastAPI()


@app.get("/goodname")
async def root():

mrtushartiwari

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Fullname(BaseModel):
    first_name: str
    last_name : str

mrtushartiwari

import pandas as pd

FILE_PATH = 'WDISeries-Time.csv'
chunk_size = 50
parts_name = 'WDISeries-Time'
df = pd.read_csv(FILE_PATH,chunksize= chunk_size)

print(df, type(df))

for i,d in enumerate(df):

mrtushartiwari

"It now costs $1,200 on average to complete World Cup sticker album"
"Nancy Pelosi Taiwan visit Highlights: Taiwan scrambles jets as 30 Chinese fighters cross Taiwan Strait median line"
"China withdraws promise not to dispatch troops to Taiwan after unification"
"Google Fiber Is Coming To Five More US States"

mrtushartiwari

import requests
import json

API_URL = "http://127.0.0.1:5000/translate"

# Openning and reading a file with sample English Sentences.
try:
	file1 = open('sentence.txt', 'r')
	lines = file1.readlines()
except: