Installation¶

Quick Install¶

The simplest way to install ParquetFrame is via pip:

pip install parquetframe

Installation Options¶

Standard Installation¶

pip install parquetframe

This installs ParquetFrame with all required dependencies: - pandas >= 2.0.0 - dask[dataframe] >= 2023.1.0 - pyarrow >= 10.0.0

Development Installation¶

For contributors or those wanting to run tests:

git clone https://github.com/leechristophermurray/parquetframe.git
cd parquetframe
pip install -e ".[dev]"

From Source¶

pip install git+https://github.com/leechristophermurray/parquetframe.git

Verify Installation¶

Test your installation:

import parquetframe as pqf
print(pqf.__version__)

# Create a simple test
import pandas as pd
test_df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})
pf = pqf.ParquetFrame(test_df)
print(f"Backend: {'Dask' if pf.islazy else 'pandas'}")
print("✅ ParquetFrame is working correctly!")

Requirements¶

Python Version¶

Python 3.9 or higher

Core Dependencies¶

pandas >= 2.0.0: DataFrame operations
dask[dataframe] >= 2023.1.0: Distributed computing
pyarrow >= 10.0.0: Parquet file format support

Optional Dependencies¶

For development: - pytest >= 7.0: Testing framework - pytest-cov >= 4.0: Coverage reporting - ruff >= 0.1.0: Code linting - black >= 23.0: Code formatting - mypy >= 1.0: Type checking

Platform Support¶

ParquetFrame is tested on: - Linux (Ubuntu, CentOS, Amazon Linux) - macOS (Intel and Apple Silicon) - Windows (Windows 10/11)

Troubleshooting¶

Common Installation Issues¶

ImportError: No module named 'parquetframe'¶

# Make sure pip installed to the correct environment
pip show parquetframe

# If using virtual environment, activate it first
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate     # Windows

pip install parquetframe

Version Conflicts¶

# Check for conflicting versions
pip list | grep -E "(pandas|dask|pyarrow)"

# Update conflicting packages
pip install --upgrade pandas dask[dataframe] pyarrow

Permission Errors¶

# Install for current user only
pip install --user parquetframe

# Or use virtual environment (recommended)
python -m venv parquetframe-env
source parquetframe-env/bin/activate  # Linux/Mac
pip install parquetframe

Environment-Specific Issues¶

Conda Environments¶

# Create new conda environment
conda create -n parquetframe python=3.11
conda activate parquetframe

# Install via pip (recommended)
pip install parquetframe

# Or install dependencies via conda first
conda install pandas dask pyarrow
pip install parquetframe

Docker¶

FROM python:3.11-slim

# Install ParquetFrame
RUN pip install parquetframe

# Your application code
COPY . /app
WORKDIR /app

Google Colab¶

# In a Colab notebook cell
!pip install parquetframe

# Restart runtime if needed
import parquetframe as pqf

Performance Optimization¶

Memory Requirements¶

Recommended minimum system requirements: - 4GB RAM: Basic usage with small datasets - 8GB RAM: Comfortable usage with medium datasets - 16GB+ RAM: Large dataset processing

Storage Requirements¶

Disk space: 100MB for ParquetFrame and dependencies
Temporary space: 2-3x your largest parquet file size for processing

Network Requirements¶

Initial installation requires internet access to download: - ParquetFrame package (~50KB) - Dependencies (~200MB total)

Once installed, ParquetFrame works offline.

Upgrading¶

Upgrade to Latest Version¶

pip install --upgrade parquetframe

Upgrade with Dependencies¶

pip install --upgrade parquetframe pandas dask[dataframe] pyarrow

Check Version¶

import parquetframe as pqf
print(f"ParquetFrame version: {pqf.__version__}")

Uninstalling¶

pip uninstall parquetframe

This removes ParquetFrame but keeps dependencies. To remove dependencies:

pip uninstall parquetframe pandas dask pyarrow

Next Steps: Once installed, check out the Quick Start Guide to start using ParquetFrame!