shardate 2025.9.9

A lightweight Python library for efficiently reading year-month-day partitioned Parquet datasets.

shardate

A lightweight Python library for efficiently reading year-month-day partitioned Parquet datasets with PySpark.

Installation

pip install shardate

Features

• Read Parquet data partitioned by year/month/day structure
• Efficient date-based filtering
• Built on PySpark for scalable data processing
• Simple and intuitive API

Quick Start

from datetime import date
from shardate import read_by_date, read_between, read_by_dates

# Read data for a specific date
df = read_by_date("/path/to/data", date(2025, 1, 15))

# Read data between two dates
df = read_between("/path/to/data", date(2025, 1, 1), date(2025, 1, 31))

# Read data for specific dates
dates = [date(2025, 1, 1), date(2025, 1, 15), date(2025, 1, 31)]
df = read_by_dates("/path/to/data", dates)

Requirements

• Python 3.12+
• PySpark 4.0+

License

MIT