ParquetFrame
High-performance data analytics with AI/ML capabilities
ParquetFrame is a unified data platform combining SQL, time series, geospatial, financial analysis, and AI/ML capabilities - all with familiar DataFrame interfaces.
✨ Features
- SQL Engine: Query DataFrames with SQL (DataFusion/DuckDB)
- Time Series:
.tsaccessor for resampling, rolling windows - GeoSpatial:
.geoaccessor for spatial operations - Financial:
.finaccessor for technical indicators - AI/ML: Tetnus ML framework + RAG with Knowlogy knowledge graph
- Cloud: S3, GCS, Azure Blob Storage support
- Interactive CLI: Rich REPL with syntax highlighting
🚀 Quick Start
pip install parquetframe
import pandas as pd
import parquetframe as pf
import parquetframe.sql
import parquetframe.time
import parquetframe.finance
# SQL queries
result = pf.sql("SELECT * FROM df WHERE value > 100", df=df)
# Time series
daily = df.ts.resample('1D', agg='mean')
# Financial indicators
rsi = df.fin.rsi('close', 14)
macd = df.fin.macd('close')
📚 Documentation
🎯 Use Cases
Financial Analysis
import parquetframe.finance
prices = pd.read_csv("stock.csv", index_col='date', parse_dates=True)
prices['SMA_20'] = prices.fin.sma('close', 20)
prices['RSI'] = prices.fin.rsi('close', 14)
Time Series Forecasting
import parquetframe.time
sensor_data = df.ts.resample('1H', agg='mean')
smoothed = sensor_data.ts.rolling('24H', agg='mean')
GeoSpatial Analysis
import geopandas as gpd
import parquetframe.geo
cities = gpd.read_file("cities.geojson")
buffered = cities.geo.buffer(1000)
AI-Powered RAG
from parquetframe.ai import SimpleRagPipeline
from parquetframe import knowlogy
# Query knowledge graph
formula = knowlogy.get_formula("variance")
# RAG with formula grounding
result = pipeline.run_query("Explain variance", user_context="analyst")
🏗️ Architecture
ParquetFrame combines:
- Rust Core: High-performance kernels (pf-time-core, pf-geo-core, pf-fin-core)
- Python API: Familiar pandas-style accessors
- AI/ML: Tetnus framework + Knowlogy knowledge graph
- Cloud: Multi-cloud storage integration
🔗 Project Links
📄 License
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License
🙏 Acknowledgments
Built on top of:
- Apache Arrow / Polars / pandas
- DataFusion / DuckDB
- GeoPandas / Shapely
- PyTorch (Tetnus)
Metadata
Release files for parquetframe 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| parquetframe-2.0.0.tar.gz | 436.3 kB | Details |
Built distributions (wheels)
Total release size: 314.1 MB
Release files / parquetframe-2.0.0.tar.gz
| Download URL | parquetframe-2.0.0.tar.gz |
|---|---|
| Size | 436.3 kB |
| Tags | Source |
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| Size | 24.1 MB |
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