The PoetryDB API stores its data in MongoDB, a popular NoSQL database. Indeed, a NoSQL database is a solid choice for the type of data that is stored in PoetryDB (unstructured text, for example). However, what if we wanted to create a more traditional SQL database with the PoetryDB API data for use in other projects where a relational database would be preferred? By extracting the data from the PoetryDB API using a combination of a few Python libraries, we can recreate the NoSQL PoetryDB database as a SQL database which will allow us more freedom to create additional data features and avoid the need to hit the PoetryDB database more than necessary.
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.
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 to explore nearly 130 poets and more than 3,200 poems. In this introductory notebook, we will explore some of the basic functionality for interacting with the PoetryDB database.
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.
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.
The following post introduces the
petpy package and its methods for interacting with the Petfinder API. The goal of the
petpy library is to enable other users to interact with the rich data available in the Petfinder database with an easy-to-use and straightforward Python interface. Methods for coercing the often messy JSON and XML API outputs into pandas DataFrame
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