Breast-cancer-classification-using-DNA-Sequencing/requirements.txt at main · tech-aakash/Breast-cancer-classification-using-DNA-Sequencing · GitHub

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# Core Python Dependencies for Breast Cancer DNA Classification Project
# Python 3.9.21 recommended

# Deep Learning & Transformers
torch>=1.11.0
transformers>=4.20.0
tokenizers>=0.12.0

# Bioinformatics & Genomics
biopython>=1.79
pysam>=0.19.0

# Data Processing & Analysis
pandas>=1.5.0
numpy>=1.21.0
pyarrow>=8.0.0
fastparquet>=0.8.0

# Machine Learning
scikit-learn>=1.1.0
optuna>=3.0.0
joblib>=1.1.0

# Deep Learning Framework Support
tensorflow>=2.9.0
keras>=2.9.0

# Data Visualization & Dimensionality Reduction
matplotlib>=3.5.0
seaborn>=0.11.0
plotly>=5.0.0
umap-learn>=0.5.3
bokeh>=2.4.0

# Database & Query Tools
duckdb>=0.5.0
sqlalchemy>=1.4.0

# Experiment Tracking & Monitoring
wandb>=0.13.0
mlflow>=1.28.0

# Progress Bars & UI
tqdm>=4.64.0
ipywidgets>=7.7.0

# Jupyter Notebook Support
jupyter>=1.0.0
jupyterlab>=3.4.0
notebook>=6.4.0
ipykernel>=6.15.0

# Statistical Analysis
scipy>=1.9.0
statsmodels>=0.13.0

# Memory & System Monitoring
psutil>=5.9.0
memory-profiler>=0.60.0

# Configuration Management
pyyaml>=6.0
python-dotenv>=0.19.0
hydra-core>=1.2.0

# Cloud & Remote Access (for Azure VM)
azure-storage-blob>=12.12.0
paramiko>=2.11.0

# Genomic Data Formats
h5py>=3.7.0
zarr>=2.12.0

# Parallel Processing
dask>=2022.7.0
ray>=2.0.0

# Development & Testing
pytest>=7.1.0
pytest-cov>=3.0.0
black>=22.6.0
flake8>=5.0.0
pre-commit>=2.20.0

# Documentation
sphinx>=5.0.0
sphinx-rtd-theme>=1.0.0

# Utilities
click>=8.1.0
rich>=12.5.0
pathlib2>=2.3.0

# Scientific Computing
numba>=0.56.0
cupy>=11.0.0  # For GPU acceleration (optional)

# Specific versions for reproducibility (critical dependencies)
torch==1.12.1
transformers==4.21.1
scikit-learn==1.1.2
pandas==1.4.4
numpy==1.21.6

# Optional: For working with compressed genomic files
gzip>=1.0.0
lz4>=4.0.0

# Optional: For advanced genomic analysis
pybedtools>=0.9.0
genomepy>=0.14.0