R download file api

To do this, we first need to convert the raw Unicode into a character vector that resembles the JSON format shown above. The rawToChar function performs just this task, as shown below:. From a character vector, we can convert it into list data structure using the fromJSON function from the jsonlite library.

So, there's our answer: at the time of writing this blog post, there are 6 people in space. But if you try it for yourself, you'll likely get different names and a different number. That's one of the advantages of APIs — unlike downloadable data sets, they're generally updated in real-time or near-real-time, so they're a great way to get access to very current data. A data frame, like the one we see above, is how we would typically store structured data for further analysis in the tidyverse libraries that we learn in the Dataquest curriculum.

You can learn more about this in our Data Analyst in R Path if interested. Above, we've walked through a very straightforward API workflow. Most APIs will require you to follow this same general pattern, but they can be more complex. Some APIs require more information from the user. In the last part of this tutorial, we will cover how to provide additional information to the API with your request.

What if we wanted to know when the ISS was going to pass over a given location on earth? Specifically, we'll need to specify the latitude and longitude of the location we're asking about as part of our GET request. Once a latitude and longitude are specified, they are combined with the original URL as query parameters.

The vast majority of APIs you may want to access will have documentation that you can and should read to get a clear understanding of what parameters your request requires. One common parameter required by many APIs, although not the ones we're using for this tutorial, is an API key or some other form of authentication.

Anyway, now that we've made our request, including the location parameters, we can check out the response using the same functions we used earlier. Let's extract the data from the response:. The good news is that the data look like college degrees, so we can be confident the API request is working! How it works: The httr::content function uses the Content-Type data from httr::GET to determine the best way to parse the incoming data.

The JSON format is beneficial because 1 it's a plain text file, and 2 it doesn't need to be structured in a tabular data frame i. Now we've converted the contents of the API request to a data frame! Let's repeat this process, but with a slightly more complicated request from a different API. You can send more specific requests using API requests, too. To demonstrate this, we'll be using the opensecrets. This requires you to sign up for an access key here.

After you've signed up and have an API access key, you'll need to read up on the documentation for the available data.

For this example, I'll be downloading the data from the candContrib table, which contains information on the "top contributors to specified candidate for a House or Senate seat or member of Congress. In the documentation, an example API query is presented and I've represented each component in the figure below:.

API queries follow a general syntax called query parameters for accessing various resources on the web server. We will build a new request using the same method as above, but with a few additional specifications. The first portion of this should be familiar from the previous request we built--it contains the http and domain information.

You should find the downloaded data in csv format:. Figure 2: Downloaded csv File in Folder on Computer. Note: R allows for the download of any file format you want. In the previous example, we have downloaded a csv file. Furthermore, it is possible to download files from a sharepoint or a web application such as shiny.

Do you need further guidance for the downloading of files from the web? The video does not only show another example for the application of the download.

It also explains how to import this data to R or RStudio. Please accept YouTube cookies to play this video. In the responses section, the Swagger UI provides a link for downloading the returned file. Sometimes, the file type should be determined at runtime. Then in this case, we should set the contentType based on the file extension.

NET Core natively supports this kind of translation. An example implementation is as follows. StaticFiles refer to the using statement in line 1. NET Core Web projects, and it provides mappings between many commonly seen file extensions and content types. If the file extension is not in the mappings table, then you can add desired mappings in the following way.

If this utility is being used in many places, then you can extract it into a service class that focuses on content-type mapping. Web users have become used to clicking a hyperlink to download a file. There are many ways to implement the hyperlink. For example, we can create a blob data URL, use a third-party JavaScript library, or serve files directly from a web server. In this article, we are going to use the simplest way to create an anchor element without any JavaScript.