Generating reports for AUDL

• Markdown
  • tufte Databases
• Database
  • planetscale
  • supabase
• Hosts
  • railway
  • [vercel]
• Data Orchestration
  • [airflow]
  • [dagster]
• Data Observability
  • [the great expectation]

M1:

1. Computing in R with reticulate
2. Outputing PDF directly

M2: [ THIS ]

1. Generate csv in python
2. Create PDF in RMarkdown with tufte

Requirements

• railway: nodejs, npm
• astro

Bundle 1: Game Descriptive Analysis

• Which player over/under/stable performed?
• Play by play (?)
• [ ]

Bundle 2: Player Profile - Scouting

• Summary
  • Full name
  • number
  • AUDL debut
  • accolades: top 10 in for ; all-stars; mvp
• Throws distributions
  • what types of throws player throws
  • what types of throws player receives
• Player distributions
  • to who player pass to
  • from who player receives from

Bundle 3: Team Profile - Scouting

• Top throwers/receivers
  • for each types of throw
• Connections to watch out
• Social Network Analysis

Bundle 4: Player/Team Optimization

• Lineup Optimization
• What path player A should emulate to become the best

Bundle 5: Meta Analysis (Free)

• Clustering: which player/teams are the most similar
• Learning optimal strategy through reinforcement learning
• Find you siamese player

Create .env file with SUPABASE_URL and SUPABASE_KEY

# astro installation
curl -sSL install.astronomer.io | sudo bash -s

# --- airflow installation
pip install "apache-airflow[celery]==2.8.1" --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.8.1/constraints-3.8.txt"
airflow db migrate

# export AIRFLOW_HOME
export AIRFLOW_HOME="/home/yukikongju/airflow/dags"

# create user login
airflow users  create --role Admin --username admin --email admin --firstname admin --lastname admin --password admin

# 
airflow scheduler
airflow webserver --port 8080

# create symbolic link to ~/airflow/dags/audl_reports_pipeline.py
ln -s audl_reports_pipeline.py ~/airflow/dags/audl_reports_pipeline.py

Tufte

• Tufte - RMarkdown

Supabase

• Supabase crashcourse for python dev

Docker

• build an AI app with fastAPI and Docker
• Supabase Functions

Apache Airflow

• Airflow - Fundamental Concepts
• A complete Apache Airflow tutorial
• Airflow Setup with Docker
• Airflow Installation with PyPi
• Data with Marc - Getting Started with Airflow for Beginners

Astro

• Astro Installation