Installation¶

Prerequisites¶

Python 3.10+
Polars 0.46+

Installing with pip¶

pip install polars-cv

Installing with uv¶

uv add polars-cv

Installing from Source¶

If you want to build from source (e.g., for development):

# Clone the repository
git clone https://github.com/heshamdar/polars-cv.git
cd polars-cv

# Install with uv (recommended)
uv sync

# Or install with pip in development mode
pip install -e .

Verifying Installation¶

import polars as pl
from polars_cv import Pipeline

# Create a simple test pipeline
pipe = Pipeline().source("image_bytes").grayscale()
print("polars-cv installed successfully!")

Optional Dependencies¶

For Cloud Storage (S3, GCS, Azure)¶

Cloud storage support is built into polars-cv by default. For optimal performance, ensure your cloud credentials are configured:

AWS S3:

export AWS_ACCESS_KEY_ID=your_key
export AWS_SECRET_ACCESS_KEY=your_secret
export AWS_REGION=us-east-1

Google Cloud Storage:

export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

Azure Blob Storage:

export AZURE_STORAGE_ACCOUNT=your_account
export AZURE_STORAGE_ACCESS_KEY=your_key

For Documentation (development only)¶

When working in the project repository, install the docs dependency group:

uv sync --group docs

For PyTorch Integration¶

PyTorch is not a required dependency, but polars-cv integrates seamlessly with it:

import torch
from polars_cv import Pipeline, numpy_from_struct

# Pipeline with torch-compatible output
pipe = Pipeline().source("image_bytes").normalize()

# Convert to PyTorch tensor (result is a struct with data, dtype, shape fields)
tensor = torch.from_numpy(numpy_from_struct(result))