Excel Requests – HTTP for Humans

Written by Bjoern Stiel
APIs are the lifeblood of the internet, providing access to bits and bytes that make our personal and professional worlds work.
For example, Quandl provide a vast amount of financial and economic data through their API, while GitHub and StackOverflow let you pull out all sort of user and repo data through their API.
But how do we communicate with these APIs… from Excel?
Working with HTTP with all its different authentication methods and custom headers can be painful. Plus, Excel doesn’t play nicely with Json. Sure, VBA is always an option (VBA-Web seems a very decent project) and Power Query has been a huge leap forward, but neither of them are ideal if you need something quick or programmatic.
As a seasoned Pythonista, I am a big fan of Kenneth Reitz’ Requests package as it massively simplifies HTTP communication in the Python world. This inspired me to write Excel Requests, a dead simple Excel Addin to make Json over HTTP from Excel a walk in the park.

Installation

Installing Excel Requests is fairly simple, download the PowerShell installation script from the docs and run it (right click, Run with PowerShell).

Making your first Request

Start a new Excel (in case you haven’t already done so after the installation) and let’s make a GET request to get the Facebook share price history from Quandl.
 

>>> =REQUESTS.GET("https://www.quandl.com/api/v3/datasets/WIKI/FB.json")
    "https://www.quandl.com/api/v3/datasets/WIKI/FB.json"

Now, this function simply returns the URL which might be a bit surprising. This URL represents the Quandl server response. It is a (nested) Json dictionary that we cannot represent easily in our two dimensional grid system. So instead we return a “handle” to the cached dictionary, which we can access through two other Excel functions.
Let’s see what data the response dictionary contains:

>>> =REQUESTS.DICT.KEYS("https://www.quandl.com/api/v3/datasets/WIKI/FB.json")
    {"Text";"StatusCode";"StatusDescription";"ContentType";"Method";"Json"}

REQUEST.DICT.KEYS gives us the list of dictionary fields. In this case it is the response dictionary with meta information on StatusCode, StatusDescription, ContentType and Method and the actual response in the “Text” field. And, in the Json case, the actual response parsed as… you guessed it, another dictionary.
If we go back to https://www.quandl.com/api/v3/datasets/WIKI/FB.json we can see, that the timeseries data we are after is in dataset/data, so let’s pull it out (you can see from the Json representation that it is an array, so bear in mind to do it as an Excel array formula):

>>> =REQUESTS.DICT.GET("https://www.quandl.com/api/v3/datasets/WIKI/FB.json", "Json/dataset/data")
    {"2016-09-12",125.96;"2016-09-09",129.71; ...}

Authentication

You might often need to pass authentication. If you happen to have a GitHub account, you need to authenticate to pull information about yourself. A quick look at the GitHub API docs reveals that we can use basic authentication whereby the authentication string is simply <username>:<token>:

>>> =REQUESTS.GET("https://api.github.com/user",,,"<username>:<token>")
    https://api.github.com/user

Custom Headers

If you’d like to add HTTP headers to a request, simply pass in a two-column range to the headers parameter (column one refers to the header name and column two to the header value).
For example, Appveyor uses a (very slightly) different authentication method, usually referred to as Bearer Token Authentication

>>> =REQUESTS.GET("https://ci.appveyor.com/api/projects",,{"Authorization","Bearer <token>"})
    https://ci.appveyor.com/api/projects

 
Excel Requests is an open source Addin for Excel written in C#
To get started, check out the docs – http://excel-requests.pathio.com/en/latest/
If you need help, contact me [email protected]
 
Written by Bjoern Stiel
Minimalist, Ex-Investment Banker, Founder of Pathio – Version control for Excel
Email me [email protected], follow me @bjoernstiel
 
 

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Jordan Goldmeier

Jordan Goldmeier is an accomplished data professional with a wealth of experience across various industries. He currently serves as a consultant at Anarchy Data, where he assists businesses in maximizing the capabilities of Excel for financial planning and analysis. Jordan is also an instructor at Full Stack Modeller and a former Adjunct Instructor in Analytics at Wake Forest University. His extensive career has seen him hold positions as the Chief Operations Officer at Excel.TV, Data Science Manager at DataKind, Data Scientist at Dealer Tire and EY, Analytics & Data Vis Developer at The Perduco Group, and Operations Research Analyst at Booz Allen Hamilton. Jordan's background in data analytics and his passion for Excel make him a valuable resource for businesses seeking to improve their data-driven decision-making processes.

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