In this example, we walk through a sample use case of extracting data from a database using an API and then structuring that data in a cohesive manner that allows us to create a relational database that we can then query with SQL statements. The database we will create with the extracted data will use Postgresql. The Python libraries that will be used in this example are poetpy, a Python wrapper for the PoetryDB API written by yours truly, pandas for transforming and cleansing the data as needed, and sqlalchemy for handling the SQL side of things.
Introduction to Rpoet
The Rpoet package is a wrapper of the PoetryDB API, which enables developers and other users to extract a vast amount of English-language poetry from nearly 130 authors. The package provides a simple R interface for interacting and accessing the PoetryDB database. This vignette will introduce the basic functionality of Rpoet and some example usages of the package.
Introduction to poetpy
The poetpy library is a Python wrapper for the PoetryDB API. The library provides a Pythonic interface for interacting with and extracting information from the PoetryDB database. In this introductory example, we will explore some of the basic functionality of the poetpy library for interacting with the PoetryDB database.
PetfindeR, R Wrapper for the Petfinder API, Introduction Part Two
The first post introduced and explored the basic usage of the PetfindeR library. In this post, we take a quick look at some of the additional uses of the library and its methods to extract data from the Petfinder database.
PetfindeR, R Wrapper for the Petfinder API, Introduction Part One
The goal of the PetfindeR package is to provide a simple and straightforward interface for interacting with the Petfinder API through R. The Petfinder database contains approximately 300,000 adoptable pet records and 11,000 animal welfare organization records, which makes it a handy and valuable source of data for those in the animal welfare community. However, the outputs from the Petfinder API are in messy JSON format and thus it makes it more time-consuming and often frustrating to coerce the output data into a form that is workable with R.
Introduction to petpy
Introduction to using the petpy Python library for interacting with the Petfinder API.
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