{ "info": { "author": "Scott Robertson", "author_email": "scott@triv.io", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Topic :: Software Development" ], "description": "Splicer [![Build Status](https://travis-ci.org/trivio/splicer.png)](https://travis-ci.org/trivio/splicer)\n======================\n\n``splicer`` makes the entire world look like a SQL database. \nIt is a python module for working with data from disparate sources \nusing commands to those familiar with SQL. It aims to make quick \none off queries and ETL scripts more declarative rather than procedural.\n\n\nInspired by projects like BigQuery, Postgres Foreign Data Wrappers\nand Multicorn, except no database is required.\n\n``splicer`` enables:\n\n* Analysts to create Datasets linking various\n foreign tables together along with User Defined Functions written in python. \n Once defined, the datasets can be queried via SQL Select statements to create \n new Views of the Data.\n\n* Extension Developers to create extensions that make various data sources\n REST endpoints, log files, NoSQL Servers, traditional Databases,\n CSV Files to behave like tables.\n\n ``splicer`` will take advantage of these various sources' capabilities where \n appropriate and will compensate for sources that lack basic\n features. \n\n For example if a database supports joins and you want to query\n two tables within that database, ``splicer`` will have that system\n perform the join for you. If however you're working with a less\n sophisticated source, like plain files, ``splicer`` will perform the\n operations for you locally.\n\n\nEnough reading! 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