New Launches & Specification Mapping from CarWale & Yalla Motors – A Complete Technical Guide

Introduction

Automotive intelligence depends heavily on timely data about new launches, variant specifications, on-road pricing, and feature mapping across regions.

Platforms like:

• CarWale (India)
• Yalla Motors (UAE + GCC)

…publish real-time information on:

• new model launches
• engine types
• transmission options
• mileage
• power/torque
• features & safety tech
• price ranges
• available variants
• color options

This tutorial shows you exactly how to scrape:

• New car launches
• Detailed specifications
• Variant-level features
• Price comparisons
• Region-wise differences
• Image extraction

…using Python, Selenium, Requests & BeautifulSoup.

This is the same framework Actowiz Solutions deploys for automotive OEMs, market research agencies, and mobility analytics platforms.

Let’s begin.

Step 1: Install Required Libraries

pip install selenium
pip install requests
pip install beautifulsoup4
pip install pandas
pip install lxml
pip install undetected-chromedriver

Step 2: Scraping New Car Launches from CarWale (India)

CarWale new launches page:

https://www.carwale.com/new-cars/

This page lists:

• Launch date
• Expected price
• Model name
• Engine & transmission summary
• Teaser images
• Category (SUV, sedan, hatchback)

2.1 Launch Undetected Chrome

import undetected_chromedriver as uc
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from time import sleep

browser = uc.Chrome()
browser.get("https://www.carwale.com/new-cars/")
sleep(4)

2.2 Scroll to Load More Launches

for _ in range(6):
    browser.find_element(By.TAG_NAME, "body").send_keys(Keys.END)
    sleep(2)

2.3 Extract Car Launch Cards

launch_cards = browser.find_elements(By.XPATH, '//div[contains(@class,"newcar-launch-card")]')

carwale_launches = []

2.4 Extract Launch Information

for card in launch_cards:
    try:
        name = card.find_element(By.CLASS_NAME, "o-bkmzIL").text
    except:
        name = ""

    try:
        price = card.find_element(By.CLASS_NAME, "o-bkzfWJ").text
    except:
        price = ""

    try:
        launch_date = card.find_element(By.CLASS_NAME, "o-cpnuEd").text
    except:
        launch_date = ""

    try:
        url = card.find_element(By.TAG_NAME, "a").get_attribute("href")
    except:
        url = ""

    carwale_launches.append({
        "platform": "CarWale",
        "model_name": name,
        "expected_price": price,
        "launch_date": launch_date,
        "url": url
    })

Step 3: Scrape Variant Specifications from CarWale

Every model’s detail page contains:

• engine
• power
• torque
• mileage
• fuel type
• transmission
• seating capacity
• body type
• safety rating

3.1 Helper Function to Scrape Specs

import requests
from bs4 import BeautifulSoup

def scrape_carwale_specs(url):
    try:
        html = requests.get(url, timeout=10).text
        soup = BeautifulSoup(html, "lxml")

        spec_block = soup.find("div", {"id": "specifications"})
        if not spec_block:
            return {}

        specs = {}

        rows = spec_block.find_all("tr")
        for row in rows:
            cols = row.find_all("td")
            if len(cols) == 2:
                key = cols[0].text.strip()
                val = cols[1].text.strip()
                specs[key] = val

        return specs
    except:
        return {}

3.2 Attach Specifications to Every Model

for car in carwale_launches:
    car["specifications"] = scrape_carwale_specs(car["url"])

Step 4: Scraping New Launches from Yalla Motors (UAE)

Yalla Motors new car page:

https://uae.yallamotor.com/new-cars

Yalla Motors lists:

• model
• starting price
• engine specs
• body type
• detailed variant list

4.1 Open Yalla Motors Page

browser.get("https://uae.yallamotor.com/new-cars")
sleep(4)

4.2 Scroll Down

for _ in range(10):
    browser.find_element(By.TAG_NAME, "body").send_keys(Keys.END)
    sleep(2)

4.3 Extract Model Cards

yalla_records = []

cards = browser.find_elements(By.XPATH, '//div[contains(@class,"newcars-card")]')

4.4 Extract Basic Model Info

for item in cards:
    try:
        name = item.find_element(By.CLASS_NAME, "model-title").text
    except:
        name = ""

    try:
        price = item.find_element(By.CLASS_NAME, "model-price").text
    except:
        price = ""

    try:
        url = item.find_element(By.TAG_NAME, "a").get_attribute("href")
    except:
        url = ""

    yalla_records.append({
        "platform": "Yalla Motors",
        "model_name": name,
        "price": price,
        "url": url
    })

Step 5: Scrape Variant-Level Specifications from Yalla Motors

Variant specifications include:

• engine displacement
• horsepower
• torque
• fuel economy
• transmission
• drivetrain
• acceleration
• top speed

5.1 Variant Scraper Function

def scrape_yalla_specs(url):
    try:
        html = requests.get(url, timeout=10).text
        soup = BeautifulSoup(html, "lxml")

        specs_table = soup.find("table", {"class": "specs-table"})
        if not specs_table:
            return {}

        specs = {}
        rows = specs_table.find_all("tr")

        for row in rows:
            cols = row.find_all("td")
            if len(cols) == 2:
                specs[cols[0].text.strip()] = cols[1].text.strip()

        return specs
    except:
        return {}

5.2 Attach Specs to Each Yalla Motors Model

for car in yalla_records:
    car["specifications"] = scrape_yalla_specs(car["url"])

Step 6: Merge CarWale + Yalla Motors Data

import pandas as pd

df = pd.DataFrame(carwale_launches + yalla_records)
df.head()

Step 7: Normalize Key Fields (Engine, Power, Mileage, etc.)

Example: extract engine cc from specs.

import re

def extract_engine(val):
    match = re.search(r"(\d+)\s?cc", val.lower())
    return int(match.group(1)) if match else None
Apply:
df["engine_cc"] = df["specifications"].apply(lambda x: extract_engine(x.get("Engine", "")) if isinstance(x, dict) else None)

Extract power (hp / bhp)
def extract_hp(val):
    match = re.search(r"(\d+)\s?(hp|bhp)", val.lower())
    return int(match.group(1)) if match else None

Extract mileage / fuel economy
def extract_mileage(val):
    match = re.search(r"(\d+\.?\d*)\s?(km\/l|mpg)", val.lower())
    return float(match.group(1)) if match else None

Step 8: Create a Car Specification Mapping Table

Final table includes:

• Model Name
• Engine CC
• Power HP
• Body Type
• Expected Price
• Region
• Launch Date
• Specs

Step 9: Export as CSV / JSON

df.to_csv("car_spec_mapping.csv", index=False)

Step 10: Build a Launch Trends Dashboard (Optional)

Using Plotly:

import plotly.express as px

fig = px.histogram(df, x="engine_cc", color="platform", title="Engine Distribution Across New Launches")
fig.show()

Challenges in Scraping CarWale & Yalla Motors

• Heavy JavaScript
• Pages render dynamically → Selenium required.
• Spec tables may differ per model
• Requires flexible parsing.
• Some models hide variants behind tabs
• Need clicks in Selenium.
• Price values often contain formatting
• Need cleaning.
• Yalla Motors blocks rapid requests
• Use time delays + session headers.

When Should You Use Actowiz Solutions?

Use Actowiz when you need:

• 10,000+ car model data points
• Real-time automotive spec updates
• Daily price tracking for all Gulf + India
• Model-year changes
• Variant mapping
• Market-share dashboards
• Fuel type / EV trend tracking
• Regional price comparison (India vs UAE vs KSA)

We support:

• CarWale
• ZigWheels
• Gaadi
• Yalla Motors
• Cars24
• DubiCars
• AutoTrader
• CarsGuide

With full spec, pricing, variant & image extraction.

Conclusion

In this tutorial, you learned how to:

• scrape new car launches from CarWale
• extract variant-level specs
• scrape model specs from Yalla Motors
• normalize engine, power, mileage fields
• merge datasets
• generate a spec mapping table
• export analytics-ready data

This becomes your foundation for:

• automotive dashboards
• competitor benchmarking
• dealership insights
• EV trend analysis
• launch monitoring
• price comparison analytics

Actowiz Solutions can deploy a complete automotive data intelligence engine across India + UAE + GCC.

You can also reach us for all your mobile app scraping, data collection, web scraping, and instant data scraper service requirements!