NRL Data Scraping Pipeline

I need a repeatable Python-based scraping pipeline that pulls historical data from nrl.com and then continues to run weekly. Scrapy is strongly preferred because I want to spin the whole thing up inside a GitHub Codespaces Docker container and keep deployment friction to a minimum.

Scope of data
• Players page first: full player-level stats are the initial priority.
• Draw page next: I specifically need match dates, kick-off times and the team & player stats embedded in each fixture.
• Ladder and any other public stats pages can follow once the core player and draw feeds are solid.

Data model & output
All raw HTML should be parsed into tidy, flat tables (CSV or Parquet). Please create sensible surrogate keys so that tables for players, matches, teams and ladder positions can be joined cleanly in a downstream warehouse.

Deliverables
• Scrapy project with clearly named spiders for Players, Draw, Ladder and Stats
• Dockerfile / devcontainer.json so the whole thing launches in a Codespace with one click
• README that shows me the command to run a full historical scrape and the command for an incremental weekly scrape
• Sample output files proving the schema and join keys work

Acceptance
I’ll run the spiders in a fresh Codespace: if they complete without errors, produce the stated tables as files and the keys line up across tables, the job is done.