requirements.txt

# ─────────────────────────────────────────────────────────────────────────────
# requirements.txt
# All Python packages needed for the Amazon Video Games Recommendation System
# Install with:  pip install -r requirements.txt
# ─────────────────────────────────────────────────────────────────────────────

# ── Data handling ─────────────────────────────────────────────────────────────
pandas==2.2.2          # DataFrames — our main tool for storing/manipulating data
numpy==1.26.4          # Numerical operations (fast array math)

# ── Machine Learning — Recommendation ────────────────────────────────────────
scikit-surprise==1.1.5 # The Surprise library — SVD, KNN, NMF for RecSys
scikit-learn==1.5.0    # LabelEncoder, train/test split utilities

# ── Visualization ─────────────────────────────────────────────────────────────
matplotlib==3.9.0      # Base plotting library
seaborn==0.13.2        # Beautiful statistical plots built on matplotlib

# ── Jupyter Notebook (for EDA) ────────────────────────────────────────────────
jupyter==1.0.0         # Jupyter notebook server
ipykernel==6.29.4      # Allows Jupyter to run Python

# ── Web App ───────────────────────────────────────────────────────────────────
streamlit==1.35.0      # Our web app framework — no HTML/CSS needed!

# ── Data Download (Hugging Face) ─────────────────────────────────────────────
datasets==2.19.2       # Download Amazon dataset directly from Hugging Face
huggingface-hub==0.23.2

# ── Utilities ─────────────────────────────────────────────────────────────────
tqdm==4.66.4           # Progress bars so we can see long operations
joblib==1.4.2          # Parallel processing and model saving (used by sklearn)