Keith 7b059ca1d3 | 8 лет назад | |
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server | 8 лет назад | |
README.md | 8 лет назад |
This demo is inspired by the work in the Connexion Example Service. The goal of this demo is to show how to quickly prop up an API to make use of data that you’ve been holding on to -- and to impress upon you how easy it is to liberate your data, no matter what form it may be in. This example, will create endpoints over a MS Excel file!
Sound interesting? Read on!
The data for the first part of the demo comes from the National Center for Education Statistics. In particular, we’re going to make an API over some of the data in the Integrated Postsecondary Data System (IPEDS) which keeps track of a number of interesting statistics on higher education data.
There is a wealth of information in the data that we’d like to expose, but the files are all in Excel. What’s more, we don’t exactly have time (or energy just yet) to convert the files to CSV, import them into a database, etc. For the AccessDB folks, this might be a simple problem to solve, but I’d rather just take the data and expose it as fast as possible.
Though it’d be nice to demo exposing all of this, I’ve only got an hour (remember), so the data I’d really like to start with are :
Seems simple enough, but there is a little hitch -- this data lives in two separate files.
We’re going to use the survey data from IPEDS in this example and you can check out the [methodology for the data here]. In particular, there’s a data set for the “Student charges for academic year programs” which contains a number of data points on the costs students pay to attend 4-year colleges. These costs include the amount of tuituion and fees, the amount of room and board, and so on. We’d like to just expose the averages of a few of these amounts to get the exercise started. While the raw data to calculate these averages is in the core data files, once we browse around a bit, we’ll see that the “Dictionary” has a summary of the averages data we’re looking for.
We going to work with two files:
Examining these files a little more closely, we can see the follow table gives us a mapping of where we can find what we’re looking for:
Data | Location Notes |
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Average published in-state tuition and fees (2007-10) | ic2010_ay.xls StatisticsRV sheet; cells E87-E98 |
Average published in-state tuition and fees (2010-14) | ic2014_ay.xls Statistics sheet; cells E72-E81 |
Average books and supplies costs (2007-10) | ic2010_ay.xls StatisticsRV sheet; cells E101-E104 |
Average books and supplies costs (2011-14) | ic2014_ay.xls Statistics sheet; cells E98-E101 |
Average room and board (2007-10) | ic2010_ay.xls StatisticsRV sheet; cells E105-E108 |
Average room and board (2011-14) | ic2014_ay.xls Statistics sheet; cells E102-105 |
The API we’re going to develop will return JSON (by default and as a nicety of the Connexion library), and we will wrap the Excel file to demonstrate how it can be done. This is done only out of convenience, and is_not_ necessarily recommended practice - except in special cases that might actually warrant it.
For the sake of this example, we are going to have three endpoints listed in the table below:
Endpoint | Description |
---|---|
/ |
Provides the server root information. |
/summary/costs |
Provides the links to the endpoints to obtain all the costs data in the API. |
/summary/costs/{year} |
Provides the costs return data for the supplied year (e.g. tuition+fees, room and board, books and supplies) |
The core implementation can be found in server file.
The API specification can be found in apispec. For more information about YAML, go here, and of course, here for the OpenAPI Specification.