Quick answer: IMDb's conditions of use prohibit scraping and data mining, so pointing a crawler at imdb.com is both fragile and against its terms. The compliant answer for movie and TV data is to use IMDb's own downloadable datasets for non-commercial use, the TMDB (The Movie Database) API, or the OMDb API. These are built for programmatic access, return clean data, and keep you inside the rules.
Why not just scrape IMDb
IMDb is the definitive catalog for film and TV, so the temptation to scrape it is obvious. The problem is that the IMDb conditions of use explicitly forbid data mining, robots, scraping, and similar automated collection. That is not a technicality you can wave away; it is the site owner telling you no.
On top of the terms, IMDb is a large commercial site with anti-bot measures, so a scraper is a maintenance burden even before you consider whether you should. The good news is that you rarely need to, because IMDb itself publishes datasets, and two solid APIs cover the rest.
The compliant options
| Source | What you get | Auth | Commercial use | Notes |
|---|---|---|---|---|
| IMDb Datasets | Titles, names, ratings, crew, episodes | None (file download) | Non-commercial only | Official, bulk TSV files |
| TMDB API | Rich metadata, images, credits, search | API key / token | Allowed per their terms | Community-driven, well documented |
| OMDb API | Movie/TV lookup by title or IMDb ID | API key | Free and paid tiers | Simple, includes IMDb ratings |
Always confirm current terms and limits on each provider's own site, especially the line between non-commercial and commercial use.
IMDb's official datasets
IMDb publishes bulk datasets for personal and non-commercial use. These are gzipped TSV files covering titles, names, ratings, principals, and episodes. If you want to do offline analysis (ratings distributions, crew graphs, release-year trends), this is the cleanest and most authoritative source, straight from IMDb.
import pandas as pd
# IMDb's official title.ratings dataset (non-commercial use)
ratings = pd.read_csv(
"https://datasets.imdbws.com/title.ratings.tsv.gz",
sep="\t",
compression="gzip",
na_values="\\N",
)
print(ratings.sort_values("numVotes", ascending=False).head())
Read IMDb's terms for these datasets before you use them; the non-commercial restriction is the key constraint.
TMDB API
The Movie Database is a community-maintained catalog with a genuinely good API: search, full metadata, credits, images, and more. It is the workhorse for most movie and TV apps. TMDB uses a bearer token or API key; that token belongs to TMDB, not link.sc.
import requests
resp = requests.get(
"https://api.themoviedb.org/3/search/movie",
params={"query": "Dune", "api_key": "YOUR_TMDB_KEY"},
)
for movie in resp.json()["results"][:5]:
print(movie["release_date"], movie["title"], movie["vote_average"])
OMDb API
OMDb is a small, simple API for looking up a title or an IMDb ID and getting back a tidy JSON object, including IMDb ratings. It is perfect when you just need to enrich a title you already know.
import requests
resp = requests.get(
"https://www.omdbapi.com/",
params={"i": "tt0816692", "apikey": "YOUR_OMDB_KEY"}, # Interstellar
)
data = resp.json()
print(data["Title"], data["Year"], data["imdbRating"])
A note on auth headers
TMDB and OMDb pass their keys as tokens or query parameters. That is their convention. When you use link.sc for the fetching cases below, the header is x-api-key, and the base is https://api.link.sc/v1. link.sc never uses Authorization: Bearer. Keep the two straight.
When public-page fetching fits
The APIs above cover the vast majority of movie and TV data needs, and they do it inside the rules. The narrow legitimate fetching case is a public page that no film API models: an official studio press page, a public festival lineup, a distributor's public announcement. Reading that one public page is reasonable.
link.sc fetches the URL and returns clean markdown so you can hand it to an LLM instead of parsing HTML.
curl -X POST https://api.link.sc/v1/fetch \
-H "x-api-key: lsc_your_key" \
-H "Content-Type: application/json" \
-d '{
"url": "https://studio.example.com/press/2026-slate",
"format": "markdown"
}'
The response is { "content": "..." }. To find the right public source in the first place, a search that returns full page content helps:
curl -X POST https://api.link.sc/v1/search \
-H "x-api-key: lsc_your_key" \
-H "Content-Type: application/json" \
-d '{
"q": "studio official 2026 film slate announcement",
"engine": "google"
}'
The search field is q, and the response includes serpData. To note clearly: use this for public pages that no movie API covers, not to route around IMDb's no-scraping terms. Fetching IMDb pages themselves would still be against IMDb's conditions of use.
Legal and ethics note
IMDb's terms prohibit scraping, and that alone is a good reason to use the datasets and APIs instead. More broadly, whether scraping is lawful depends on the site's terms, whether you bypass access controls, the data type, and your jurisdiction; this is not legal advice. The reliable pattern: prefer the official data source, respect the terms, and do not evade anti-bot systems. For depth, see is web scraping legal and our ethical scraping and compliance best practices.
What I would build
- For bulk analysis, download IMDb's official datasets (non-commercial) and work offline.
- For a live app, use the TMDB API for metadata, search, and images.
- Use OMDb to enrich a known title or IMDb ID with ratings.
- Only for a public page no film API covers, fetch that single page with link.sc and extract fields with an LLM.
The APIs and datasets are the right answer for movie and TV data. Fetching is for the public-page gaps, and never for routing around IMDb's terms.
Need the public pages the movie APIs miss? link.sc turns any URL into clean, structured content. Start free.