Quick Start

The Data Retriever is written in Python and has a Python interface, a command line interface or an associated R package. It installs publicly available data into a variety of databases (MySQL, PostgreSQL, SQLite) and flat file formats (csv, json, xml).


Using conda:

$ conda install retriever -c conda-forge

or pip:

$ pip install retriever

To install the associated R package:

$ install.packages('rdataretriever')

Python interface


$ import retriever as rt

List available datasets:

$ rt.dataset_names()

Load data on GDP from the World bank:

$ rt.fetch('gdp')

Install the World Bank data on GDP into an SQLite databased named “gdp.sqlite”:

$ rt.install_sqlite('gdp', file='gdp.sqlite)

Command line interface

List available datasets:

$ retriever ls

Install the Portal dataset into a set of json files:

$ retriever install json portal

Install the Portal dataset into an SQLite database named “portal.sqlite”:

$ retriever install sqlite portal -f portal.sqlite

R interface

List available datasets:

$ rdataretriever::datasets()

Load data on GDP from the World bank:

$ rdataretriever::fetch(dataset = 'gdp')

Install the GDP dataset into SQLite:

$ rdataretriever::install('gdp', 'sqlite')

Learn more

Check out the rest of the documentation for more commands, details, and datasets.

Available install formats for all interfaces are: mysql, postgres, sqlite, csv, json, and xml.