# =============================================================================
#  VibeQuant (vquant) — AI-Powered Financial Intelligence Platform
# -----------------------------------------------------------------------------
#  File:      requirements.txt
#
#  Author:    Simon-Pierre Boucher
#  Contact:   contact@spboucher.ai
#  Website:   https://www.spboucher.ai
#  Demo:      https://www.vquant.ai
#  License:   MIT (see LICENSE)
#
#  Copyright © 2026 Simon-Pierre Boucher. All rights reserved.
# =============================================================================

# ==================== CORE SCIENTIFIC COMPUTING ====================
numpy>=2.0.0
pandas>=2.0.0
scipy>=1.10.0

# ==================== VISUALIZATION ====================
matplotlib>=3.8.0
seaborn>=0.13.0
plotly>=5.18.0
bokeh>=3.3.0

# ==================== FINANCIAL DATA & APIs ====================
yfinance>=0.2.35
pandas-datareader>=0.10.0
requests>=2.31.0
beautifulsoup4>=4.12.0
lxml>=5.0.0

# ==================== FINANCIAL ANALYSIS ====================
# Volatility modeling
arch>=7.0.0
# Technical indicators
ta>=0.11.0
ta-lib>=0.4.0  # Note: Might need system dependencies
# Financial metrics
pyfolio>=0.9.2
empyrical>=0.5.5
quantstats>=0.0.62

# ==================== STATISTICS & ECONOMETRICS ====================
statsmodels>=0.14.0
scikit-learn>=1.4.0
pmdarima>=2.0.4  # ARIMA models

# ==================== MACHINE LEARNING ====================
scikit-learn>=1.4.0
xgboost>=2.0.3
lightgbm>=4.3.0
catboost>=1.2.2

# ==================== OPTIMIZATION ====================
cvxpy>=1.4.0  # Convex optimization (for portfolio optimization)
pulp>=2.8.0  # Linear programming

# ==================== TIME SERIES ====================
prophet>=1.1.5  # Facebook Prophet for forecasting
statsforecast>=1.6.0

# ==================== BACKTESTING ====================
backtrader>=1.9.78
vectorbt>=0.26.0
bt>=0.2.9

# ==================== RISK ANALYSIS ====================
riskfolio-lib>=5.0.0  # Portfolio optimization & risk
pyportfolioopt>=1.5.5

# ==================== UTILITIES ====================
openpyxl>=3.1.2  # Excel files
python-docx>=1.1.0  # Word documents
xlrd>=2.0.1  # Excel files (older format)
python-dateutil>=2.8.2
pytz>=2024.1

# ==================== ADVANCED ANALYTICS ====================
networkx>=3.2  # Graph analysis
sympy>=1.12  # Symbolic mathematics
numba>=0.59.0  # JIT compilation for speed

# ==================== DATA PROCESSING ====================
polars>=0.20.0  # Fast DataFrame library
dask>=2024.1.0  # Parallel computing