How to Scrape IMDB Movie Data

IMDB is the definitive source for movie and TV show data. While they offer a commercial API, scraping the public website is a common approach for research and personal projects.

What You Can Extract

• Movie titles, release years, and genres
• Ratings and vote counts
• Cast and crew information
• Plot summaries and reviews
• Box office data
• Episode guides for TV series

Method 1: ScraperAPI (Recommended)

IMDB uses some anti-bot measures. ScraperAPI handles them automatically.

import requests
from bs4 import BeautifulSoup

API_KEY = "YOUR_SCRAPERAPI_KEY"

def scrape_movie(imdb_id):
    response = requests.get(
        "http://api.scraperapi.com",
        params={
            "api_key": API_KEY,
            "url": f"https://www.imdb.com/title/{imdb_id}/"
        }
    )
    soup = BeautifulSoup(response.text, "html.parser")

    # Extract JSON-LD structured data (most reliable)
    import json
    ld_script = soup.find("script", type="application/ld+json")
    if ld_script:
        data = json.loads(ld_script.string)
        return {
            "title": data.get("name"),
            "rating": data.get("aggregateRating", {}).get("ratingValue"),
            "votes": data.get("aggregateRating", {}).get("ratingCount"),
            "genre": data.get("genre"),
            "director": data.get("director", [{}])[0].get("name") if isinstance(data.get("director"), list) else None,
            "description": data.get("description")
        }

movie = scrape_movie("tt1375666")  # Inception
print(f"Title: {movie['title']}")
print(f"Rating: {movie['rating']}/10 ({movie['votes']} votes)")

Method 2: IMDB's Top 250 List

import requests
from bs4 import BeautifulSoup
import json

API_KEY = "YOUR_SCRAPERAPI_KEY"

response = requests.get(
    "http://api.scraperapi.com",
    params={
        "api_key": API_KEY,
        "url": "https://www.imdb.com/chart/top/"
    }
)

soup = BeautifulSoup(response.text, "html.parser")

# IMDB embeds structured data in the page
ld_data = soup.find("script", type="application/ld+json")
if ld_data:
    data = json.loads(ld_data.string)
    items = data.get("itemListElement", [])
    for item in items[:10]:
        movie = item.get("item", {})
        print(f"{item['position']}. {movie['name']} - Rating: {movie.get('aggregateRating', {}).get('ratingValue')}")

Method 3: IMDB Datasets (Free Official Data)

IMDB provides free downloadable datasets for non-commercial use at https://datasets.imdbws.com/.

import pandas as pd

# Download and load IMDB's title basics dataset
ratings = pd.read_csv(
    "https://datasets.imdbws.com/title.ratings.tsv.gz",
    sep="\t",
    compression="gzip"
)

basics = pd.read_csv(
    "https://datasets.imdbws.com/title.basics.tsv.gz",
    sep="\t",
    compression="gzip",
    na_values="\\N"
)

# Merge and filter for top-rated movies
movies = basics.merge(ratings, on="tconst")
top_movies = movies[
    (movies["titleType"] == "movie") &
    (movies["numVotes"] > 100000)
].sort_values("averageRating", ascending=False)

print(top_movies[["primaryTitle", "startYear", "averageRating", "numVotes"]].head(10))

Best Strategy

Start with the free IMDB datasets for bulk data. Use web scraping only for data not available in the datasets (like reviews, box office data, or real-time updates). Always use the JSON-LD structured data embedded in IMDB pages as it is the most reliable extraction target.