A data science toolkit for scalable data processing and analysis.
Project description
SIBI-DST
Data Science Toolkit built with Python, Pandas, Dask, OpenStreetMaps, NetworkX, SQLAlchemy, GeoPandas, and Folium.
Example Use Cases
- Build DataCubes, DataSets, and DataObjects from diverse data sources, including relational databases, Parquet files, Excel (
.xlsx), delimited tables (.csv,.tsv), JSON, and RESTful APIs. - Comprehensive DataFrame Management utilities for efficient data handling, transformation, and optimization using Pandas and Dask.
- Flexible Data Sharing with client applications by writing to Data Warehouses in Clickhouse, local filesystems, and cloud storage platforms such as S3.
- Microservices for Data Access – Build scalable API-driven services using RESTful APIs (
Django REST Framework,FastAPI) for high-performance data exchange. - Geospatial Analysis – Utilize OpenStreetMaps and GeoPandas for advanced geospatial data processing and visualization.
Supported Technologies
- Data Processing: Pandas, Dask
- Databases & Storage: SQLAlchemy, Parquet, S3, Clickhouse
- Mapping & Geospatial Analysis: OpenStreetMaps, OSMnx, Geopy
- API Development: Django REST Framework, FastAPI
Installation
# with pip
pip install sibi-dst # Install only the main package
pip install sibi-dst[geospatial] # Install with geospatial dependencies
pip install sibi-dst[dev,test,geospatial] # Install all optional dependencies
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