Netflix Tudum Top 10 Scraper
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Netflix Tudum Top 10 Scraper
Extract Netflix's official weekly Top 10 rankings across 90+ countries and globally. Pulls full historical data from Netflix Tudum's TSV files: all-weeks-global (hours viewed, views, runtime) and all-weeks-countries (since 2021). One record per ranked title per week.
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Extract Netflix's official weekly Top 10 rankings — films, TV, English and non-English — across 90+ countries and globally. This actor downloads the full historical time-series from Netflix Tudum's published TSV datasets and outputs one normalized record per ranked title per week per scope.
What data you get
Each record contains:
| Field | Description |
|---|---|
show_title | Title of the film or TV show |
season_title | Season label (N/A for films) |
week | Week ending date (Sunday, YYYY-MM-DD format) |
category | Content category — Films, TV, Films (English), TV (Non-English), etc. |
weekly_rank | Ranking position (1–10) within the category for that week |
cumulative_weeks_in_top_10 | Total weeks this title has appeared in the Top 10 |
scope | global or country |
country_name | Country name (country scope only) |
country_iso2 | ISO 3166-1 alpha-2 country code (country scope only) |
weekly_hours_viewed | Total hours viewed globally that week (global scope only) |
weekly_views | Total number of plays globally that week (global scope only) |
runtime | Title runtime in hours (global scope only) |
source_file | Source TSV filename |
Global scope includes over 10,000 weekly records (back to 2021) with hours viewed, views, and runtime. Country scope covers 90+ countries with over 470,000 weekly records — the full country-by-country breakdown since Netflix began publishing this data.
Use cases
- Media analysis: track which titles dominate in specific markets and categories over time
- Content strategy: identify patterns in what performs globally vs. regionally
- Entertainment market research: benchmark Netflix content performance for hedge fund TMT desks, trade press, and consultancies
- Data journalism: build weekly Top 10 trackers and trend stories
Input options
| Parameter | Type | Default | Description |
|---|---|---|---|
scope | string | both | Which dataset to fetch: global, countries, or both |
maxItems | integer | 0 (unlimited) | Cap the total number of records. Use 0 for full history |
How it works
Netflix publishes its official Top 10 as static TSV files at netflix.com/tudum/top10/data/:
all-weeks-global.tsv— global rankings with hours viewed, view counts, and runtimeall-weeks-countries.tsv— per-country rankings across 90+ countries
The actor fetches these files directly with a plain HTTP GET — no browser rendering, no proxy, no authentication. Each file is parsed in memory and normalized into a flat record format matching the output schema above.
Performance
| Scope | Records | Typical run time |
|---|---|---|
global | ~10,000 | Under 5 seconds |
countries | ~470,000 | Under 30 seconds |
both | ~480,000 | Under 35 seconds |
Memory usage is low (256 MB default). The datasets are updated weekly by Netflix — schedule a weekly run to keep your dataset current.
Example output
{"show_title": "Swapped","season_title": "N/A","week": "2026-05-10","category": "Films (English)","weekly_rank": 1,"cumulative_weeks_in_top_10": 2,"scope": "global","country_name": "","country_iso2": "","weekly_hours_viewed": 65800000,"weekly_views": 38700000,"runtime": 1.7,"source_file": "all-weeks-global.tsv"}
Scheduled runs
For continuous data collection, set up a scheduled run with scope: both and maxItems: 0. Netflix updates the TSV files weekly (typically Monday). A weekly schedule keeps your dataset current with minimal compute cost.