Generating reports for AUDL
- Markdown
tufte
Databases
- Database
- Hosts
- railway
- [vercel]
- Data Orchestration
- [airflow]
- [dagster]
- Data Observability
- [the great expectation]
M1:
- Computing in R with reticulate
- Outputing PDF directly
M2: [ THIS ]
- Generate csv in python
- 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
Supabase
Docker
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